GoTube: Scalable statistical verification of continuous-depth models - Gruenbacher, Sophie A.; Lechner, Mathias; Hasani, Ramin; Rus, Daniela; Henzinger, Thomas A; Smolka, Scott A.; Grosu, Radu (Proceedings of the AAAI Conference on Artificial Intelligence)
We introduce a new statistical verification algorithm that formally quantifies the behavioral robustness of any time-continuous process formulated as a continuous-depth model. Our algorithm solves a set of global optimization (Go) problems over a given time horizon to construct a tight enclosure (Tube) of the set of all process executions starting from a ball of initial states. We call our algorithm GoTube. Through its construction, GoTube ensures that the bounding tube is conservative up to a desired probability and up to a desired tightness. GoTube is implemented in JAX and optimized to scale to complex continuous-depth neural network models. Compared to advanced reachability analysis tools for time-continuous neural networks, GoTube does not accumulate overapproximation errors between time steps and avoids the infamous wrapping effect inherent in symbolic techniques. We show that GoTube substantially outperforms state-of-the-art verification tools in terms of the size of the initial ball, speed, time-horizon, task completion, and scalability on a large set of experiments. GoTube is stable and sets the state-of-the-art in terms of its ability to scale to time horizons well beyond what has been previously possible.
Keywords: General Medicine

Stability verification in stochastic control systems via neural network supermartingales - Lechner, Mathias; Zikelic, Dorde; Chatterjee, Krishnendu; Henzinger, Thomas A (Proceedings of the AAAI Conference on Artificial Intelligence)
We consider the problem of formally verifying almost-sure (a.s.) asymptotic stability in discrete-time nonlinear stochastic control systems. While verifying stability in deterministic control systems is extensively studied in the literature, verifying stability in stochastic control systems is an open problem. The few existing works on this topic either consider only specialized forms of stochasticity or make restrictive assumptions on the system, rendering them inapplicable to learning algorithms with neural network policies. In this work, we present an approach for general nonlinear stochastic control problems with two novel aspects: (a) instead of classical stochastic extensions of Lyapunov functions, we use ranking supermartingales (RSMs) to certify a.s. asymptotic stability, and (b) we present a method for learning neural network RSMs. We prove that our approach guarantees a.s. asymptotic stability of the system and provides the first method to obtain bounds on the stabilization time, which stochastic Lyapunov functions do not. Finally, we validate our approach experimentally on a set of nonlinear stochastic reinforcement learning environments with neural network policies.
Keywords: General Medicine

Learning stabilizing policies in stochastic control systems - Zikelic, Dorde; Lechner, Mathias; Chatterjee, Krishnendu; Henzinger, Thomas A (arXiv)
In this work, we address the problem of learning provably stable neural network policies for stochastic control systems. While recent work has demonstrated the feasibility of certifying given policies using martingale theory, the problem of how to learn such policies is little explored. Here, we study the effectiveness of jointly learning a policy together with a martingale certificate that proves its stability using a single learning algorithm. We observe that the joint optimization problem becomes easily stuck in local minima when starting from a randomly initialized policy. Our results suggest that some form of pre-training of the policy is required for the joint optimization to repair and verify the policy successfully.

Learning control policies for stochastic systems with reach-avoid guarantees - Zikelic, Dorde; Lechner, Mathias; Henzinger, Thomas A; Chatterjee, Krishnendu (arXiv)
We study the problem of learning controllers for discrete-time non-linear stochastic dynamical systems with formal reach-avoid guarantees. This work presents the first method for providing formal reach-avoid guarantees, which combine and generalize stability and safety guarantees, with a tolerable probability threshold $p\in[0,1]$ over the infinite time horizon. Our method leverages advances in machine learning literature and it represents formal certificates as neural networks. In particular, we learn a certificate in the form of a reach-avoid supermartingale (RASM), a novel notion that we introduce in this work. Our RASMs provide reachability and avoidance guarantees by imposing constraints on what can be viewed as a stochastic extension of level sets of Lyapunov functions for deterministic systems. Our approach solves several important problems -- it can be used to learn a control policy from scratch, to verify a reach-avoid specification for a fixed control policy, or to fine-tune a pre-trained policy if it does not satisfy the reach-avoid specification. We validate our approach on $3$ stochastic non-linear reinforcement learning tasks.

Transitioning from structural to nominal code with efficient gradual typing - Mühlböck, Fabian; Tate, Ross (Proceedings of the ACM on Programming Languages)
Gradual typing is a principled means for mixing typed and untyped code. But typed and untyped code often exhibit different programming patterns. There is already substantial research investigating gradually giving types to code exhibiting typical untyped patterns, and some research investigating gradually removing types from code exhibiting typical typed patterns. This paper investigates how to extend these established gradual-typing concepts to give formal guarantees not only about how to change types as code evolves but also about how to change such programming patterns as well. In particular, we explore mixing untyped "structural" code with typed "nominal" code in an object-oriented language. But whereas previous work only allowed "nominal" objects to be treated as "structural" objects, we also allow "structural" objects to dynamically acquire certain nominal types, namely interfaces. We present a calculus that supports such "cross-paradigm" code migration and interoperation in a manner satisfying both the static and dynamic gradual guarantees, and demonstrate that the calculus can be implemented efficiently.
Keywords: gradual typing; gradual guarantee; nominal; structural; call tags

On the verification of neural ODEs with stochastic guarantees - Grunbacher, Sophie; Hasani, Ramin; Lechner, Mathias; Cyranka, Jacek; Smolka, Scott A; Grosu, Radu (Proceedings of the AAAI Conference on Artificial Intelligence)
We show that Neural ODEs, an emerging class of timecontinuous neural networks, can be verified by solving a set of global-optimization problems. For this purpose, we introduce Stochastic Lagrangian Reachability (SLR), an abstraction-based technique for constructing a tight Reachtube (an over-approximation of the set of reachable states over a given time-horizon), and provide stochastic guarantees in the form of confidence intervals for the Reachtube bounds. SLR inherently avoids the infamous wrapping effect (accumulation of over-approximation errors) by performing local optimization steps to expand safe regions instead of repeatedly forward-propagating them as is done by deterministic reachability methods. To enable fast local optimizations, we introduce a novel forward-mode adjoint sensitivity method to compute gradients without the need for backpropagation. Finally, we establish asymptotic and non-asymptotic convergence rates for SLR.

Liquid time-constant networks - Hasani, Ramin; Lechner, Mathias; Amini, Alexander; Rus, Daniela; Grosu, Radu (Proceedings of the AAAI Conference on Artificial Intelligence)
We introduce a new class of time-continuous recurrent neural network models. Instead of declaring a learning system’s dynamics by implicit nonlinearities, we construct networks of linear first-order dynamical systems modulated via nonlinear interlinked gates. The resulting models represent dynamical systems with varying (i.e., liquid) time-constants coupled to their hidden state, with outputs being computed by numerical differential equation solvers. These neural networks exhibit stable and bounded behavior, yield superior expressivity within the family of neural ordinary differential equations, and give rise to improved performance on time-series prediction tasks. To demonstrate these properties, we first take a theoretical approach to find bounds over their dynamics, and compute their expressive power by the trajectory length measure in a latent trajectory space. We then conduct a series of time-series prediction experiments to manifest the approximation capability of Liquid Time-Constant Networks (LTCs) compared to classical and modern RNNs.

On-off center-surround receptive fields for accurate and robust image classification - Babaiee, Zahra; Hasani, Ramin; Lechner, Mathias; Rus, Daniela; Grosu, Radu (Proceedings of the 38th International Conference on Machine Learning)
Robustness to variations in lighting conditions is a key objective for any deep vision system. To this end, our paper extends the receptive field of convolutional neural networks with two residual components, ubiquitous in the visual processing system of vertebrates: On-center and off-center pathways, with an excitatory center and inhibitory surround; OOCS for short. The On-center pathway is excited by the presence of a light stimulus in its center, but not in its surround, whereas the Off-center pathway is excited by the absence of a light stimulus in its center, but not in its surround. We design OOCS pathways via a difference of Gaussians, with their variance computed analytically from the size of the receptive fields. OOCS pathways complement each other in their response to light stimuli, ensuring this way a strong edge-detection capability, and as a result an accurate and robust inference under challenging lighting conditions. We provide extensive empirical evidence showing that networks supplied with OOCS pathways gain accuracy and illumination-robustness from the novel edge representation, compared to other baselines.

Causal navigation by continuous-time neural networks - Vorbach, Charles J; Hasani, Ramin; Amini, Alexander; Lechner, Mathias; Rus, Daniela (35th Conference on Neural Information Processing Systems)
Imitation learning enables high-fidelity, vision-based learning of policies within rich, photorealistic environments. However, such techniques often rely on traditional discrete-time neural models and face difficulties in generalizing to domain shifts by failing to account for the causal relationships between the agent and the environment. In this paper, we propose a theoretical and experimental framework for learning causal representations using continuous-time neural networks, specifically over their discrete-time counterparts. We evaluate our method in the context of visual-control learning of drones over a series of complex tasks, ranging from short- and long-term navigation, to chasing static and dynamic objects through photorealistic environments. Our results demonstrate that causal continuous-time deep models can perform robust navigation tasks, where advanced recurrent models fail. These models learn complex causal control representations directly from raw visual inputs and scale to solve a variety of tasks using imitation learning.

The Civl verifier - Kragl, Bernhard; Qadeer, Shaz (Proceedings of the 21st Conference on Formal Methods in Computer-Aided Design)
Civl is a static verifier for concurrent programs designed around the conceptual framework of layered refinement, which views the task of verifying a program as a sequence of program simplification steps each justified by its own invariant. Civl verifies a layered concurrent program that compactly expresses all the programs in this sequence and the supporting invariants. This paper presents the design and implementation of the Civl verifier.

Formal verification of Zagier's one-sentence proof - Dubach, Guillaume; Mühlböck, Fabian (arXiv)
We comment on two formal proofs of Fermat's sum of two squares theorem, written using the Mathematical Components libraries of the Coq proof assistant. The first one follows Zagier's celebrated one-sentence proof; the second follows David Christopher's recent new proof relying on partition-theoretic arguments. Both formal proofs rely on a general property of involutions of finite sets, of independent interest. The proof technique consists for the most part of automating recurrent tasks (such as case distinctions and computations on natural numbers) via ad hoc tactics.

Scalable verification of quantized neural networks - Henzinger, Thomas A; Lechner, Mathias; Zikelic, Dorde (Proceedings of the AAAI Conference on Artificial Intelligence)
Formal verification of neural networks is an active topic of research, and recent advances have significantly increased the size of the networks that verification tools can handle. However, most methods are designed for verification of an idealized model of the actual network which works over real arithmetic and ignores rounding imprecisions. This idealization is in stark contrast to network quantization, which is a technique that trades numerical precision for computational efficiency and is, therefore, often applied in practice. Neglecting rounding errors of such low-bit quantized neural networks has been shown to lead to wrong conclusions about the network’s correctness. Thus, the desired approach for verifying quantized neural networks would be one that takes these rounding errors into account. In this paper, we show that verifying the bitexact implementation of quantized neural networks with bitvector specifications is PSPACE-hard, even though verifying idealized real-valued networks and satisfiability of bit-vector specifications alone are each in NP. Furthermore, we explore several practical heuristics toward closing the complexity gap between idealized and bit-exact verification. In particular, we propose three techniques for making SMT-based verification of quantized neural networks more scalable. Our experiments demonstrate that our proposed methods allow a speedup of up to three orders of magnitude over existing approaches.

Infinite time horizon safety of Bayesian neural networks - Lechner, Mathias; Žikelić, Ðorđe; Chatterjee, Krishnendu; Henzinger, Thomas A (35th Conference on Neural Information Processing Systems)
Bayesian neural networks (BNNs) place distributions over the weights of a neural network to model uncertainty in the data and the network's prediction. We consider the problem of verifying safety when running a Bayesian neural network policy in a feedback loop with infinite time horizon systems. Compared to the existing sampling-based approaches, which are inapplicable to the infinite time horizon setting, we train a separate deterministic neural network that serves as an infinite time horizon safety certificate. In particular, we show that the certificate network guarantees the safety of the system over a subset of the BNN weight posterior's support. Our method first computes a safe weight set and then alters the BNN's weight posterior to reject samples outside this set. Moreover, we show how to extend our approach to a safe-exploration reinforcement learning setting, in order to avoid unsafe trajectories during the training of the policy. We evaluate our approach on a series of reinforcement learning benchmarks, including non-Lyapunovian safety specifications.

Boosting expensive synchronizing heuristics - Sarac, Naci E; Altun, Ömer Faruk; Atam, Kamil Tolga; Karahoda, Sertac; Kaya, Kamer; Yenigün, Hüsnü (Expert Systems with Applications)
For automata, synchronization, the problem of bringing an automaton to a particular state regardless of its initial state, is important. It has several applications in practice and is related to a fifty-year-old conjecture on the length of the shortest synchronizing word. Although using shorter words increases the effectiveness in practice, finding a shortest one (which is not necessarily unique) is NP-hard. For this reason, there exist various heuristics in the literature. However, high-quality heuristics such as SynchroP producing relatively shorter sequences are very expensive and can take hours when the automaton has tens of thousands of states. The SynchroP heuristic has been frequently used as a benchmark to evaluate the performance of the new heuristics. In this work, we first improve the runtime of SynchroP and its variants by using algorithmic techniques. We then focus on adapting SynchroP for many-core architectures, and overall, we obtain more than 1000× speedup on GPUs compared to naive sequential implementation that has been frequently used as a benchmark to evaluate new heuristics in the literature. We also propose two SynchroP variants and evaluate their performance.

Synthesis of hybrid automata with affine dynamics from time-series data - Garcia Soto, Miriam; Henzinger, Thomas A; Schilling, Christian (HSCC '21: Proceedings of the 24th International Conference on Hybrid Systems: Computation and Control)
Formal design of embedded and cyber-physical systems relies on mathematical modeling. In this paper, we consider the model class of hybrid automata whose dynamics are defined by affine differential equations. Given a set of time-series data, we present an algorithmic approach to synthesize a hybrid automaton exhibiting behavior that is close to the data, up to a specified precision, and changes in synchrony with the data. A fundamental problem in our synthesis algorithm is to check membership of a time series in a hybrid automaton. Our solution integrates reachability and optimization techniques for affine dynamical systems to obtain both a sufficient and a necessary condition for membership, combined in a refinement framework. The algorithm processes one time series at a time and hence can be interrupted, provide an intermediate result, and be resumed. We report experimental results demonstrating the applicability of our synthesis approach.
Keywords: hybrid automaton; membership; system identification

Bidding mechanisms in graph games - Avni, Guy; Henzinger, Thomas A; Žikelić, Đorđe (Journal of Computer and System Sciences)
A graph game proceeds as follows: two players move a token through a graph to produce a finite or infinite path, which determines the payoff of the game. We study bidding games in which in each turn, an auction determines which player moves the token. Bidding games were largely studied in combination with two variants of first-price auctions called “Richman” and “poorman” bidding. We study taxman bidding, which span the spectrum between the two. The game is parameterized by a constant : portion τ of the winning bid is paid to the other player, and portion to the bank. While finite-duration (reachability) taxman games have been studied before, we present, for the first time, results on infinite-duration taxman games: we unify, generalize, and simplify previous equivalences between bidding games and a class of stochastic games called random-turn games.

Quantitative and approximate monitoring - Henzinger, Thomas A; Sarac, Naci E (Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science)
In runtime verification, a monitor watches a trace of a system and, if possible, decides after observing each finite prefix whether or not the unknown infinite trace satisfies a given specification. We generalize the theory of runtime verification to monitors that attempt to estimate numerical values of quantitative trace properties (instead of attempting to conclude boolean values of trace specifications), such as maximal or average response time along a trace. Quantitative monitors are approximate: with every finite prefix, they can improve their estimate of the infinite trace's unknown property value. Consequently, quantitative monitors can be compared with regard to a precision-cost trade-off: better approximations of the property value require more monitor resources, such as states (in the case of finite-state monitors) or registers, and additional resources yield better approximations. We introduce a formal framework for quantitative and approximate monitoring, show how it conservatively generalizes the classical boolean setting for monitoring, and give several precision-cost trade-offs for monitors. For example, we prove that there are quantitative properties for which every additional register improves monitoring precision.

Long lived transients in gene regulation - Petrov, Tatjana; Igler, Claudia; Sezgin, Ali; Henzinger, Thomas A; Guet, Calin C (Theoretical Computer Science)
Gene expression is regulated by the set of transcription factors (TFs) that bind to the promoter. The ensuing regulating function is often represented as a combinational logic circuit, where output (gene expression) is determined by current input values (promoter bound TFs) only. However, the simultaneous arrival of TFs is a strong assumption, since transcription and translation of genes introduce intrinsic time delays and there is no global synchronisation among the arrival times of different molecular species at their targets. We present an experimentally implementable genetic circuit with two inputs and one output, which in the presence of small delays in input arrival, exhibits qualitatively distinct population-level phenotypes, over timescales that are longer than typical cell doubling times. From a dynamical systems point of view, these phenotypes represent long-lived transients: although they converge to the same value eventually, they do so after a very long time span. The key feature of this toy model genetic circuit is that, despite having only two inputs and one output, it is regulated by twenty-three distinct DNA-TF configurations, two of which are more stable than others (DNA looped states), one promoting and another blocking the expression of the output gene. Small delays in input arrival time result in a majority of cells in the population quickly reaching the stable state associated with the first input, while exiting of this stable state occurs at a slow timescale. In order to mechanistically model the behaviour of this genetic circuit, we used a rule-based modelling language, and implemented a grid-search to find parameter combinations giving rise to long-lived transients. Our analysis shows that in the absence of feedback, there exist path-dependent gene regulatory mechanisms based on the long timescale of transients. The behaviour of this toy model circuit suggests that gene regulatory networks can exploit event timing to create phenotypes, and it opens the possibility that they could use event timing to memorise events, without regulatory feedback. The model reveals the importance of (i) mechanistically modelling the transitions between the different DNA-TF states, and (ii) employing transient analysis thereof.

Differential monitoring - Mühlböck, Fabian; Henzinger, Thomas A (International Conference on Runtime Verification)
We argue that the time is ripe to investigate differential monitoring, in which the specification of a program's behavior is implicitly given by a second program implementing the same informal specification. Similar ideas have been proposed before, and are currently implemented in restricted form for testing and specialized run-time analyses, aspects of which we combine. We discuss the challenges of implementing differential monitoring as a general-purpose, black-box run-time monitoring framework, and present promising results of a preliminary implementation, showing low monitoring overheads for diverse programs.
Keywords: run-time verification; software engineering; implicit specification

Differential monitoring - Mühlböck, Fabian; Henzinger, Thomas A
We argue that the time is ripe to investigate differential monitoring, in which the specification of a program's behavior is implicitly given by a second program implementing the same informal specification. Similar ideas have been proposed before, and are currently implemented in restricted form for testing and specialized run-time analyses, aspects of which we combine. We discuss the challenges of implementing differential monitoring as a general-purpose, black-box run-time monitoring framework, and present promising results of a preliminary implementation, showing low monitoring overheads for diverse programs.
Keywords: run-time verification; software engineering; implicit specification

Interactive analysis of CNN robustness - Sietzen, Stefan; Lechner, Mathias; Borowski, Judy; Hasani, Ramin; Waldner, Manuela (Computer Graphics Forum)
While convolutional neural networks (CNNs) have found wide adoption as state-of-the-art models for image-related tasks, their predictions are often highly sensitive to small input perturbations, which the human vision is robust against. This paper presents Perturber, a web-based application that allows users to instantaneously explore how CNN activations and predictions evolve when a 3D input scene is interactively perturbed. Perturber offers a large variety of scene modifications, such as camera controls, lighting and shading effects, background modifications, object morphing, as well as adversarial attacks, to facilitate the discovery of potential vulnerabilities. Fine-tuned model versions can be directly compared for qualitative evaluation of their robustness. Case studies with machine learning experts have shown that Perturber helps users to quickly generate hypotheses about model vulnerabilities and to qualitatively compare model behavior. Using quantitative analyses, we could replicate users’ insights with other CNN architectures and input images, yielding new insights about the vulnerability of adversarially trained models.

Determinacy in discrete-bidding infinite-duration games - Aghajohari, Milad; Avni, Guy; Henzinger, Thomas A (Logical Methods in Computer Science)
In two-player games on graphs, the players move a token through a graph to produce an infinite path, which determines the winner of the game. Such games are central in formal methods since they model the interaction between a non-terminating system and its environment. In bidding games the players bid for the right to move the token: in each round, the players simultaneously submit bids, and the higher bidder moves the token and pays the other player. Bidding games are known to have a clean and elegant mathematical structure that relies on the ability of the players to submit arbitrarily small bids. Many applications, however, require a fixed granularity for the bids, which can represent, for example, the monetary value expressed in cents. We study, for the first time, the combination of discrete-bidding and infinite-duration games. Our most important result proves that these games form a large determined subclass of concurrent games, where determinacy is the strong property that there always exists exactly one player who can guarantee winning the game. In particular, we show that, in contrast to non-discrete bidding games, the mechanism with which tied bids are resolved plays an important role in discrete-bidding games. We study several natural tie-breaking mechanisms and show that, while some do not admit determinacy, most natural mechanisms imply determinacy for every pair of initial budgets.
Keywords: computer science; computer science and game theory; logic in computer science

Adversarial training is not ready for robot learning - Lechner, Mathias; Hasani, Ramin; Grosu, Radu; Rus, Daniela; Henzinger, Thomas A (2021 IEEE International Conference on Robotics and Automation)
Adversarial training is an effective method to train deep learning models that are resilient to norm-bounded perturbations, with the cost of nominal performance drop. While adversarial training appears to enhance the robustness and safety of a deep model deployed in open-world decision-critical applications, counterintuitively, it induces undesired behaviors in robot learning settings. In this paper, we show theoretically and experimentally that neural controllers obtained via adversarial training are subjected to three types of defects, namely transient, systematic, and conditional errors. We first generalize adversarial training to a safety-domain optimization scheme allowing for more generic specifications. We then prove that such a learning process tends to cause certain error profiles. We support our theoretical results by a thorough experimental safety analysis in a robot-learning task. Our results suggest that adversarial training is not yet ready for robot learning.

Into the unknown: active monitoring of neural networks - Lukina, Anna; Schilling, Christian; Henzinger, Thomas A (21st International Conference on Runtime Verification)
Neural-network classifiers achieve high accuracy when predicting the class of an input that they were trained to identify. Maintaining this accuracy in dynamic environments, where inputs frequently fall outside the fixed set of initially known classes, remains a challenge. The typical approach is to detect inputs from novel classes and retrain the classifier on an augmented dataset. However, not only the classifier but also the detection mechanism needs to adapt in order to distinguish between newly learned and yet unknown input classes. To address this challenge, we introduce an algorithmic framework for active monitoring of a neural network. A monitor wrapped in our framework operates in parallel with the neural network and interacts with a human user via a series of interpretable labeling queries for incremental adaptation. In addition, we propose an adaptive quantitative monitor to improve precision. An experimental evaluation on a diverse set of benchmarks with varying numbers of classes confirms the benefits of our active monitoring framework in dynamic scenarios.
Keywords: monitoring; neural networks; novelty detection

A natural lottery ticket winner: Reinforcement learning with ordinary neural circuits - Hasani, Ramin; Lechner, Mathias; Amini, Alexander; Rus, Daniela; Grosu, Radu (Proceedings of the 37th International Conference on Machine Learning)
We propose a neural information processing system obtained by re-purposing the function of a biological neural circuit model to govern simulated and real-world control tasks. Inspired by the structure of the nervous system of the soil-worm, C. elegans, we introduce ordinary neural circuits (ONCs), defined as the model of biological neural circuits reparameterized for the control of alternative tasks. We first demonstrate that ONCs realize networks with higher maximum flow compared to arbitrary wired networks. We then learn instances of ONCs to control a series of robotic tasks, including the autonomous parking of a real-world rover robot. For reconfiguration of the purpose of the neural circuit, we adopt a search-based optimization algorithm. Ordinary neural circuits perform on par and, in some cases, significantly surpass the performance of contemporary deep learning models. ONC networks are compact, 77% sparser than their counterpart neural controllers, and their neural dynamics are fully interpretable at the cell-level.

Monitoring event frequencies - Ferrere, Thomas; Henzinger, Thomas A; Kragl, Bernhard (28th EACSL Annual Conference on Computer Science Logic)
The monitoring of event frequencies can be used to recognize behavioral anomalies, to identify trends, and to deduce or discard hypotheses about the underlying system. For example, the performance of a web server may be monitored based on the ratio of the total count of requests from the least and most active clients. Exact frequency monitoring, however, can be prohibitively expensive; in the above example it would require as many counters as there are clients. In this paper, we propose the efficient probabilistic monitoring of common frequency properties, including the mode (i.e., the most common event) and the median of an event sequence. We define a logic to express composite frequency properties as a combination of atomic frequency properties. Our main contribution is an algorithm that, under suitable probabilistic assumptions, can be used to monitor these important frequency properties with four counters, independent of the number of different events. Our algorithm samples longer and longer subwords of an infinite event sequence. We prove the almost-sure convergence of our algorithm by generalizing ergodic theory from increasing-length prefixes to increasing-length subwords of an infinite sequence. A similar algorithm could be used to learn a connected Markov chain of a given structure from observing its outputs, to arbitrary precision, for a given confidence.

ARCH-COMP20 Category Report: Continuous and hybrid systems with linear dynamics - Althoff, Matthias; Bak, Stanley; Bao, Zongnan; Forets, Marcelo; Frehse, Goran; Freire, Daniel; Kochdumper, Niklas; Li, Yangge; Mitra, Sayan; Ray, Rajarshi; Schilling, Christian; Schupp, Stefan; et al. (EPiC Series in Computing)
We present the results of the ARCH 2020 friendly competition for formal verification of continuous and hybrid systems with linear continuous dynamics. In its fourth edition, eight tools have been applied to solve eight different benchmark problems in the category for linear continuous dynamics (in alphabetical order): CORA, C2E2, HyDRA, Hylaa, Hylaa-Continuous, JuliaReach, SpaceEx, and XSpeed. This report is a snapshot of the current landscape of tools and the types of benchmarks they are particularly suited for. Due to the diversity of problems, we are not ranking tools, yet the presented results provide one of the most complete assessments of tools for the safety verification of continuous and hybrid systems with linear continuous dynamics up to this date.

ARCH-COMP20 Category Report: Continuous and hybrid systems with nonlinear dynamics - Geretti, Luca; Alexandre Dit Sandretto, Julien; Althoff, Matthias; Benet, Luis; Chapoutot, Alexandre; Chen, Xin; Collins, Pieter; Forets, Marcelo; Freire, Daniel; Immler, Fabian; Kochdumper, Niklas; Sanders, David; et al. (EPiC Series in Computing)
We present the results of a friendly competition for formal verification of continuous and hybrid systems with nonlinear continuous dynamics. The friendly competition took place as part of the workshop Applied Verification for Continuous and Hybrid Systems (ARCH) in 2020. This year, 6 tools Ariadne, CORA, DynIbex, Flow*, Isabelle/HOL, and JuliaReach (in alphabetic order) participated. These tools are applied to solve reachability analysis problems on six benchmark problems, two of them featuring hybrid dynamics. We do not rank the tools based on the results, but show the current status and discover the potential advantages of different tools.

Multi-dimensional long-run average problems for vector addition systems with states - Chatterjee, Krishnendu; Henzinger, Thomas A; Otop, Jan (31st International Conference on Concurrency Theory)
A vector addition system with states (VASS) consists of a finite set of states and counters. A transition changes the current state to the next state, and every counter is either incremented, or decremented, or left unchanged. A state and value for each counter is a configuration; and a computation is an infinite sequence of configurations with transitions between successive configurations. A probabilistic VASS consists of a VASS along with a probability distribution over the transitions for each state. Qualitative properties such as state and configuration reachability have been widely studied for VASS. In this work we consider multi-dimensional long-run average objectives for VASS and probabilistic VASS. For a counter, the cost of a configuration is the value of the counter; and the long-run average value of a computation for the counter is the long-run average of the costs of the configurations in the computation. The multi-dimensional long-run average problem given a VASS and a threshold value for each counter, asks whether there is a computation such that for each counter the long-run average value for the counter does not exceed the respective threshold. For probabilistic VASS, instead of the existence of a computation, we consider whether the expected long-run average value for each counter does not exceed the respective threshold. Our main results are as follows: we show that the multi-dimensional long-run average problem (a) is NP-complete for integer-valued VASS; (b) is undecidable for natural-valued VASS (i.e., nonnegative counters); and (c) can be solved in polynomial time for probabilistic integer-valued VASS, and probabilistic natural-valued VASS when all computations are non-terminating.

A survey of bidding games on graphs - Avni, Guy; Henzinger, Thomas A (31st International Conference on Concurrency Theory)
A graph game is a two-player zero-sum game in which the players move a token throughout a graph to produce an infinite path, which determines the winner or payoff of the game. In bidding games, both players have budgets, and in each turn, we hold an "auction" (bidding) to determine which player moves the token. In this survey, we consider several bidding mechanisms and study their effect on the properties of the game. Specifically, bidding games, and in particular bidding games of infinite duration, have an intriguing equivalence with random-turn games in which in each turn, the player who moves is chosen randomly. We show how minor changes in the bidding mechanism lead to unexpected differences in the equivalence with random-turn games.

Formal methods with a touch of magic - Alamdari, Par Alizadeh; Avni, Guy; Henzinger, Thomas A; Lukina, Anna (Proceedings of the 20th Conference on Formal Methods in Computer-Aided Design)
Machine learning and formal methods have complimentary benefits and drawbacks. In this work, we address the controller-design problem with a combination of techniques from both fields. The use of black-box neural networks in deep reinforcement learning (deep RL) poses a challenge for such a combination. Instead of reasoning formally about the output of deep RL, which we call the wizard, we extract from it a decision-tree based model, which we refer to as the magic book. Using the extracted model as an intermediary, we are able to handle problems that are infeasible for either deep RL or formal methods by themselves. First, we suggest, for the first time, a synthesis procedure that is based on a magic book. We synthesize a stand-alone correct-by-design controller that enjoys the favorable performance of RL. Second, we incorporate a magic book in a bounded model checking (BMC) procedure. BMC allows us to find numerous traces of the plant under the control of the wizard, which a user can use to increase the trustworthiness of the wizard and direct further training.

WoodFisher: Efficient second-order approximation for neural network compression - Singh, Sidak Pal; Alistarh, Dan-Adrian (Advances in Neural Information Processing Systems)
Second-order information, in the form of Hessian- or Inverse-Hessian-vector products, is a fundamental tool for solving optimization problems. Recently, there has been significant interest in utilizing this information in the context of deep neural networks; however, relatively little is known about the quality of existing approximations in this context. Our work examines this question, identifies issues with existing approaches, and proposes a method called WoodFisher to compute a faithful and efficient estimate of the inverse Hessian. Our main application is to neural network compression, where we build on the classic Optimal Brain Damage/Surgeon framework. We demonstrate that WoodFisher significantly outperforms popular state-of-the-art methods for oneshot pruning. Further, even when iterative, gradual pruning is allowed, our method results in a gain in test accuracy over the state-of-the-art approaches, for standard image classification datasets such as ImageNet ILSVRC. We examine how our method can be extended to take into account first-order information, as well as illustrate its ability to automatically set layer-wise pruning thresholds and perform compression in the limited-data regime. The code is available at the following link, https://github.com/IST-DASLab/WoodFisher.

Lagrangian reachtubes: The next generation - Gruenbacher, Sophie; Cyranka, Jacek; Lechner, Mathias; Islam, Md Ariful; Smolka, Scott A.; Grosu, Radu (Proceedings of the 59th IEEE Conference on Decision and Control)
We introduce LRT-NG, a set of techniques and an associated toolset that computes a reachtube (an over-approximation of the set of reachable states over a given time horizon) of a nonlinear dynamical system. LRT-NG significantly advances the state-of-the-art Langrangian Reachability and its associated tool LRT. From a theoretical perspective, LRT-NG is superior to LRT in three ways. First, it uses for the first time an analytically computed metric for the propagated ball which is proven to minimize the ball’s volume. We emphasize that the metric computation is the centerpiece of all bloating-based techniques. Secondly, it computes the next reachset as the intersection of two balls: one based on the Cartesian metric and the other on the new metric. While the two metrics were previously considered opposing approaches, their joint use considerably tightens the reachtubes. Thirdly, it avoids the "wrapping effect" associated with the validated integration of the center of the reachset, by optimally absorbing the interval approximation in the radius of the next ball. From a tool-development perspective, LRT-NG is superior to LRT in two ways. First, it is a standalone tool that no longer relies on CAPD. This required the implementation of the Lohner method and a Runge-Kutta time-propagation method. Secondly, it has an improved interface, allowing the input model and initial conditions to be provided as external input files. Our experiments on a comprehensive set of benchmarks, including two Neural ODEs, demonstrates LRT-NG’s superior performance compared to LRT, CAPD, and Flow*.

Learning representations for binary-classification without backpropagation - Lechner, Mathias (8th International Conference on Learning Representations)
The family of feedback alignment (FA) algorithms aims to provide a more biologically motivated alternative to backpropagation (BP), by substituting the computations that are unrealistic to be implemented in physical brains. While FA algorithms have been shown to work well in practice, there is a lack of rigorous theory proofing their learning capabilities. Here we introduce the first feedback alignment algorithm with provable learning guarantees. In contrast to existing work, we do not require any assumption about the size or depth of the network except that it has a single output neuron, i.e., such as for binary classification tasks. We show that our FA algorithm can deliver its theoretical promises in practice, surpassing the learning performance of existing FA methods and matching backpropagation in binary classification tasks. Finally, we demonstrate the limits of our FA variant when the number of output neurons grows beyond a certain quantity.

How many bits does it take to quantize your neural network? - Giacobbe, Mirco; Henzinger, Thomas A; Lechner, Mathias (International Conference on Tools and Algorithms for the Construction and Analysis of Systems)
Quantization converts neural networks into low-bit fixed-point computations which can be carried out by efficient integer-only hardware, and is standard practice for the deployment of neural networks on real-time embedded devices. However, like their real-numbered counterpart, quantized networks are not immune to malicious misclassification caused by adversarial attacks. We investigate how quantization affects a network’s robustness to adversarial attacks, which is a formal verification question. We show that neither robustness nor non-robustness are monotonic with changing the number of bits for the representation and, also, neither are preserved by quantization from a real-numbered network. For this reason, we introduce a verification method for quantized neural networks which, using SMT solving over bit-vectors, accounts for their exact, bit-precise semantics. We built a tool and analyzed the effect of quantization on a classifier for the MNIST dataset. We demonstrate that, compared to our method, existing methods for the analysis of real-numbered networks often derive false conclusions about their quantizations, both when determining robustness and when detecting attacks, and that existing methods for quantized networks often miss attacks. Furthermore, we applied our method beyond robustness, showing how the number of bits in quantization enlarges the gender bias of a predictor for students’ grades.

Dynamic resource allocation games - Avni, Guy; Henzinger, Thomas A; Kupferman, Orna (Theoretical Computer Science)
In resource allocation games, selfish players share resources that are needed in order to fulfill their objectives. The cost of using a resource depends on the load on it. In the traditional setting, the players make their choices concurrently and in one-shot. That is, a strategy for a player is a subset of the resources. We introduce and study dynamic resource allocation games. In this setting, the game proceeds in phases. In each phase each player chooses one resource. A scheduler dictates the order in which the players proceed in a phase, possibly scheduling several players to proceed concurrently. The game ends when each player has collected a set of resources that fulfills his objective. The cost for each player then depends on this set as well as on the load on the resources in it – we consider both congestion and cost-sharing games. We argue that the dynamic setting is the suitable setting for many applications in practice. We study the stability of dynamic resource allocation games, where the appropriate notion of stability is that of subgame perfect equilibrium, study the inefficiency incurred due to selfish behavior, and also study problems that are particular to the dynamic setting, like constraints on the order in which resources can be chosen or the problem of finding a scheduler that achieves stability.

Outside the box: Abstraction-based monitoring of neural networks - Henzinger, Thomas A; Lukina, Anna; Schilling, Christian (24th European Conference on Artificial Intelligence)
Neural networks have demonstrated unmatched performance in a range of classification tasks. Despite numerous efforts of the research community, novelty detection remains one of the significant limitations of neural networks. The ability to identify previously unseen inputs as novel is crucial for our understanding of the decisions made by neural networks. At runtime, inputs not falling into any of the categories learned during training cannot be classified correctly by the neural network. Existing approaches treat the neural network as a black box and try to detect novel inputs based on the confidence of the output predictions. However, neural networks are not trained to reduce their confidence for novel inputs, which limits the effectiveness of these approaches. We propose a framework to monitor a neural network by observing the hidden layers. We employ a common abstraction from program analysis - boxes - to identify novel behaviors in the monitored layers, i.e., inputs that cause behaviors outside the box. For each neuron, the boxes range over the values seen in training. The framework is efficient and flexible to achieve a desired trade-off between raising false warnings and detecting novel inputs. We illustrate the performance and the robustness to variability in the unknown classes on popular image-classification benchmarks.

An SMT theory of fixed-point arithmetic - Baranowski, Marek; He, Shaobo; Lechner, Mathias; Nguyen, Thanh Son; Rakamarić, Zvonimir (Automated Reasoning)
Fixed-point arithmetic is a popular alternative to floating-point arithmetic on embedded systems. Existing work on the verification of fixed-point programs relies on custom formalizations of fixed-point arithmetic, which makes it hard to compare the described techniques or reuse the implementations. In this paper, we address this issue by proposing and formalizing an SMT theory of fixed-point arithmetic. We present an intuitive yet comprehensive syntax of the fixed-point theory, and provide formal semantics for it based on rational arithmetic. We also describe two decision procedures for this theory: one based on the theory of bit-vectors and the other on the theory of reals. We implement the two decision procedures, and evaluate our implementations using existing mature SMT solvers on a benchmark suite we created. Finally, we perform a case study of using the theory we propose to verify properties of quantized neural networks.

Neural circuit policies enabling auditable autonomy - Lechner, Mathias; Hasani, Ramin; Amini, Alexander; Henzinger, Thomas A; Rus, Daniela; Grosu, Radu (Nature Machine Intelligence)
A central goal of artificial intelligence in high-stakes decision-making applications is to design a single algorithm that simultaneously expresses generalizability by learning coherent representations of their world and interpretable explanations of its dynamics. Here, we combine brain-inspired neural computation principles and scalable deep learning architectures to design compact neural controllers for task-specific compartments of a full-stack autonomous vehicle control system. We discover that a single algorithm with 19 control neurons, connecting 32 encapsulated input features to outputs by 253 synapses, learns to map high-dimensional inputs into steering commands. This system shows superior generalizability, interpretability and robustness compared with orders-of-magnitude larger black-box learning systems. The obtained neural agents enable high-fidelity autonomy for task-specific parts of a complex autonomous system.

Gershgorin loss stabilizes the recurrent neural network compartment of an end-to-end robot learning scheme - Lechner, Mathias; Hasani, Ramin; Rus, Daniela; Grosu, Radu (Proceedings - IEEE International Conference on Robotics and Automation)
Traditional robotic control suits require profound task-specific knowledge for designing, building and testing control software. The rise of Deep Learning has enabled end-to-end solutions to be learned entirely from data, requiring minimal knowledge about the application area. We design a learning scheme to train end-to-end linear dynamical systems (LDS)s by gradient descent in imitation learning robotic domains. We introduce a new regularization loss component together with a learning algorithm that improves the stability of the learned autonomous system, by forcing the eigenvalues of the internal state updates of an LDS to be negative reals. We evaluate our approach on a series of real-life and simulated robotic experiments, in comparison to linear and nonlinear Recurrent Neural Network (RNN) architectures. Our results show that our stabilizing method significantly improves test performance of LDS, enabling such linear models to match the performance of contemporary nonlinear RNN architectures. A video of the obstacle avoidance performance of our method on a mobile robot, in unseen environments, compared to other methods can be viewed at https://youtu.be/mhEsCoNao5E.

Efficient reachability analysis of parametric linear hybrid systems with time-triggered transitions - Forets, Marcelo; Freire, Daniel; Schilling, Christian (18th ACM-IEEE International Conference on Formal Methods and Models for System Design)
Efficiently handling time-triggered and possibly nondeterministic switches for hybrid systems reachability is a challenging task. In this paper we present an approach based on conservative set-based enclosure of the dynamics that can handle systems with uncertain parameters and inputs, where the uncertainties are bound to given intervals. The method is evaluated on the plant model of an experimental electro-mechanical braking system with periodic controller. In this model, the fast-switching controller dynamics requires simulation time scales of the order of nanoseconds. Accurate set-based computations for relatively large time horizons are known to be expensive. However, by appropriately decoupling the time variable with respect to the spatial variables, and enclosing the uncertain parameters using interval matrix maps acting on zonotopes, we show that the computation time can be lowered to 5000 times faster with respect to previous works. This is a step forward in formal verification of hybrid systems because reduced run-times allow engineers to introduce more expressiveness in their models with a relatively inexpensive computational cost.

Reachability analysis of linear hybrid systems via block decomposition - Bogomolov, Sergiy; Forets, Marcelo; Frehse, Goran; Potomkin, Kostiantyn; Schilling, Christian (Proceedings of the International Conference on Embedded Software)
Reachability analysis aims at identifying states reachable by a system within a given time horizon. This task is known to be computationally expensive for linear hybrid systems. Reachability analysis works by iteratively applying continuous and discrete post operators to compute states reachable according to continuous and discrete dynamics, respectively. In this paper, we enhance both of these operators and make sure that most of the involved computations are performed in low-dimensional state space. In particular, we improve the continuous-post operator by performing computations in high-dimensional state space only for time intervals relevant for the subsequent application of the discrete-post operator. Furthermore, the new discrete-post operator performs low-dimensional computations by leveraging the structure of the guard and assignment of a considered transition. We illustrate the potential of our approach on a number of challenging benchmarks.
Keywords: reachability; hybrid systems; decomposition

Reachability analysis of linear hybrid systems via block decomposition - Bogomolov, Sergiy; Forets, Marcelo; Frehse, Goran; Potomkin, Kostiantyn; Schilling, Christian (IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems)
Reachability analysis aims at identifying states reachable by a system within a given time horizon. This task is known to be computationally expensive for linear hybrid systems. Reachability analysis works by iteratively applying continuous and discrete post operators to compute states reachable according to continuous and discrete dynamics, respectively. In this article, we enhance both of these operators and make sure that most of the involved computations are performed in low-dimensional state space. In particular, we improve the continuous-post operator by performing computations in high-dimensional state space only for time intervals relevant for the subsequent application of the discrete-post operator. Furthermore, the new discrete-post operator performs low-dimensional computations by leveraging the structure of the guard and assignment of a considered transition. We illustrate the potential of our approach on a number of challenging benchmarks.

All-pay bidding games on graphs - Avni, Guy; Ibsen-Jensen, Rasmus; Tkadlec, Josef (Proceedings of the AAAI Conference on Artificial Intelligence)
In this paper we introduce and study all-pay bidding games, a class of two player, zero-sum games on graphs. The game proceeds as follows. We place a token on some vertex in the graph and assign budgets to the two players. Each turn, each player submits a sealed legal bid (non-negative and below their remaining budget), which is deducted from their budget and the highest bidder moves the token onto an adjacent vertex. The game ends once a sink is reached, and Player 1 pays Player 2 the outcome that is associated with the sink. The players attempt to maximize their expected outcome. Our games model settings where effort (of no inherent value) needs to be invested in an ongoing and stateful manner. On the negative side, we show that even in simple games on DAGs, optimal strategies may require a distribution over bids with infinite support. A central quantity in bidding games is the ratio of the players budgets. On the positive side, we show a simple FPTAS for DAGs, that, for each budget ratio, outputs an approximation for the optimal strategy for that ratio. We also implement it, show that it performs well, and suggests interesting properties of these games. Then, given an outcome c, we show an algorithm for finding the necessary and sufficient initial ratio for guaranteeing outcome c with probability 1 and a strategy ensuring such. Finally, while the general case has not previously been studied, solving the specific game in which Player 1 wins iff he wins the first two auctions, has been long stated as an open question, which we solve.

Monitorability under assumptions - Henzinger, Thomas A; Sarac, Naci E (Runtime Verification)
We introduce the monitoring of trace properties under assumptions. An assumption limits the space of possible traces that the monitor may encounter. An assumption may result from knowledge about the system that is being monitored, about the environment, or about another, connected monitor. We define monitorability under assumptions and study its theoretical properties. In particular, we show that for every assumption A, the boolean combinations of properties that are safe or co-safe relative to A are monitorable under A. We give several examples and constructions on how an assumption can make a non-monitorable property monitorable, and how an assumption can make a monitorable property monitorable with fewer resources, such as integer registers.

Refinement for structured concurrent programs - Kragl, Bernhard; Qadeer, Shaz; Henzinger, Thomas A (Computer Aided Verification)
This paper presents a foundation for refining concurrent programs with structured control flow. The verification problem is decomposed into subproblems that aid interactive program development, proof reuse, and automation. The formalization in this paper is the basis of a new design and implementation of the Civl verifier.

Inductive sequentialization of asynchronous programs - Kragl, Bernhard; Enea, Constantin; Henzinger, Thomas A; Mutluergil, Suha Orhun; Qadeer, Shaz (Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation)
Asynchronous programs are notoriously difficult to reason about because they spawn computation tasks which take effect asynchronously in a nondeterministic way. Devising inductive invariants for such programs requires understanding and stating complex relationships between an unbounded number of computation tasks in arbitrarily long executions. In this paper, we introduce inductive sequentialization, a new proof rule that sidesteps this complexity via a sequential reduction, a sequential program that captures every behavior of the original program up to reordering of coarse-grained commutative actions. A sequential reduction of a concurrent program is easy to reason about since it corresponds to a simple execution of the program in an idealized synchronous environment, where processes act in a fixed order and at the same speed. We have implemented and integrated our proof rule in the CIVL verifier, allowing us to provably derive fine-grained implementations of asynchronous programs. We have successfully applied our proof rule to a diverse set of message-passing protocols, including leader election protocols, two-phase commit, and Paxos.

AMT 2.0: Qualitative and quantitative trace analysis with extended signal temporal logic - Nickovic, Dejan; Lebeltel, Olivier; Maler, Oded; Ferrere, Thomas; Ulus, Dogan (International Journal on Software Tools for Technology Transfer)
We introduce in this paper AMT2.0, a tool for qualitative and quantitative analysis of hybrid continuous and Boolean signals that combine numerical values and discrete events. The evaluation of the signals is based on rich temporal specifications expressed in extended signal temporal logic, which integrates timed regular expressions within signal temporal logic. The tool features qualitative monitoring (property satisfaction checking), trace diagnostics for explaining and justifying property violations and specification-driven measurement of quantitative features of the signal. We demonstrate the tool functionality on several running examples and case studies, and evaluate its performance.
Keywords: Information Systems; Software

Verifying concurrent programs: Refinement, synchronization, sequentialization - Kragl, Bernhard
Designing and verifying concurrent programs is a notoriously challenging, time consuming, and error prone task, even for experts. This is due to the sheer number of possible interleavings of a concurrent program, all of which have to be tracked and accounted for in a formal proof. Inventing an inductive invariant that captures all interleavings of a low-level implementation is theoretically possible, but practically intractable. We develop a refinement-based verification framework that provides mechanisms to simplify proof construction by decomposing the verification task into smaller subtasks. In a first line of work, we present a foundation for refinement reasoning over structured concurrent programs. We introduce layered concurrent programs as a compact notation to represent multi-layer refinement proofs. A layered concurrent program specifies a sequence of connected concurrent programs, from most concrete to most abstract, such that common parts of different programs are written exactly once. Each program in this sequence is expressed as structured concurrent program, i.e., a program over (potentially recursive) procedures, imperative control flow, gated atomic actions, structured parallelism, and asynchronous concurrency. This is in contrast to existing refinement-based verifiers, which represent concurrent systems as flat transition relations. We present a powerful refinement proof rule that decomposes refinement checking over structured programs into modular verification conditions. Refinement checking is supported by a new form of modular, parameterized invariants, called yield invariants, and a linear permission system to enhance local reasoning. In a second line of work, we present two new reduction-based program transformations that target asynchronous programs. These transformations reduce the number of interleavings that need to be considered, thus reducing the complexity of invariants. Synchronization simplifies the verification of asynchronous programs by introducing the fiction, for proof purposes, that asynchronous operations complete synchronously. Synchronization summarizes an asynchronous computation as immediate atomic effect. Inductive sequentialization establishes sequential reductions that captures every behavior of the original program up to reordering of coarse-grained commutative actions. A sequential reduction of a concurrent program is easy to reason about since it corresponds to a simple execution of the program in an idealized synchronous environment, where processes act in a fixed order and at the same speed. Our approach is implemented the CIVL verifier, which has been successfully used for the verification of several complex concurrent programs. In our methodology, the overall correctness of a program is established piecemeal by focusing on the invariant required for each refinement step separately. While the programmer does the creative work of specifying the chain of programs and the inductive invariant justifying each link in the chain, the tool automatically constructs the verification conditions underlying each refinement step.

Hybridization for stability verification of nonlinear switched systems - Garcia Soto, Miriam; Prabhakar, Pavithra (2020 IEEE Real-Time Systems Symposium)
We propose a novel hybridization method for stability analysis that over-approximates nonlinear dynamical systems by switched systems with linear inclusion dynamics. We observe that existing hybridization techniques for safety analysis that over-approximate nonlinear dynamical systems by switched affine inclusion dynamics and provide fixed approximation error, do not suffice for stability analysis. Hence, we propose a hybridization method that provides a state-dependent error which converges to zero as the state tends to the equilibrium point. The crux of our hybridization computation is an elegant recursive algorithm that uses partial derivatives of a given function to obtain upper and lower bound matrices for the over-approximating linear inclusion. We illustrate our method on some examples to demonstrate the application of the theory for stability analysis. In particular, our method is able to establish stability of a nonlinear system which does not admit a polynomial Lyapunov function.

Abstraction based verification of stability of polyhedral switched systems - Garcia Soto, Miriam; Prabhakar, Pavithra (Nonlinear Analysis: Hybrid Systems)
This paper presents a novel abstraction technique for analyzing Lyapunov and asymptotic stability of polyhedral switched systems. A polyhedral switched system is a hybrid system in which the continuous dynamics is specified by polyhedral differential inclusions, the invariants and guards are specified by polyhedral sets and the switching between the modes do not involve reset of variables. A finite state weighted graph abstracting the polyhedral switched system is constructed from a finite partition of the state–space, such that the satisfaction of certain graph conditions, such as the absence of cycles with product of weights on the edges greater than (or equal) to 1, implies the stability of the system. However, the graph is in general conservative and hence, the violation of the graph conditions does not imply instability. If the analysis fails to establish stability due to the conservativeness in the approximation, a counterexample (cycle with product of edge weights greater than or equal to 1) indicating a potential reason for the failure is returned. Further, a more precise approximation of the switched system can be constructed by considering a finer partition of the state–space in the construction of the finite weighted graph. We present experimental results on analyzing stability of switched systems using the above method.

ARCH-COMP19 Category Report: Hybrid systems with piecewise constant dynamics - Frehse, Goran; Abate, Alessandro; Adzkiya, Dieky; Becchi, Anna; Bu, Lei; Cimatti, Alessandro; Giacobbe, Mirco; Griggio, Alberto; Mover, Sergio; Mufid, Muhammad Syifa'ul; Riouak, Idriss; Tonetta, Stefano; et al. (ARCH19. 6th International Workshop on Applied Verification of Continuous and Hybrid Systems)
This report presents the results of a friendly competition for formal verification of continuous and hybrid systems with piecewise constant dynamics. The friendly competition took place as part of the workshop Applied Verification for Continuous and Hybrid Systems (ARCH) in 2019. In this third edition, six tools have been applied to solve five different benchmark problems in the category for piecewise constant dynamics: BACH, Lyse, Hy- COMP, PHAVer/SX, PHAVerLite, and VeriSiMPL. Compared to last year, a new tool has participated (HyCOMP) and PHAVerLite has replaced PHAVer-lite. The result is a snap- shot of the current landscape of tools and the types of benchmarks they are particularly suited for. Due to the diversity of problems, we are not ranking tools, yet the presented results probably provide the most complete assessment of tools for the safety verification of continuous and hybrid systems with piecewise constant dynamics up to this date.

Formal synthesis of stabilizing controllers for periodically controlled linear switched systems - Kundu, Atreyee; Garcia Soto, Miriam; Prabhakar, Pavithra (5th Indian Control Conference Proceedings)
In this paper, we address the problem of synthesizing periodic switching controllers for stabilizing a family of linear systems. Our broad approach consists of constructing a finite game graph based on the family of linear systems such that every winning strategy on the game graph corresponds to a stabilizing switching controller for the family of linear systems. The construction of a (finite) game graph, the synthesis of a winning strategy and the extraction of a stabilizing controller are all computationally feasible. We illustrate our method on an example.

Bidding games on Markov decision processes - Avni, Guy; Henzinger, Thomas A; Ibsen-Jensen, Rasmus; Novotny, Petr (Proceedings of the 13th International Conference of Reachability Problems)
In two-player games on graphs, the players move a token through a graph to produce an infinite path, which determines the qualitative winner or quantitative payoff of the game. In bidding games, in each turn, we hold an auction between the two players to determine which player moves the token. Bidding games have largely been studied with concrete bidding mechanisms that are variants of a first-price auction: in each turn both players simultaneously submit bids, the higher bidder moves the token, and pays his bid to the lower bidder in Richman bidding, to the bank in poorman bidding, and in taxman bidding, the bid is split between the other player and the bank according to a predefined constant factor. Bidding games are deterministic games. They have an intriguing connection with a fragment of stochastic games called randomturn games. We study, for the first time, a combination of bidding games with probabilistic behavior; namely, we study bidding games that are played on Markov decision processes, where the players bid for the right to choose the next action, which determines the probability distribution according to which the next vertex is chosen. We study parity and meanpayoff bidding games on MDPs and extend results from the deterministic bidding setting to the probabilistic one.

Designing worm-inspired neural networks for interpretable robotic control - Lechner, Mathias; Hasani, Ramin; Zimmer, Manuel; Henzinger, Thomas A; Grosu, Radu (Proceedings - IEEE International Conference on Robotics and Automation)
In this paper, we design novel liquid time-constant recurrent neural networks for robotic control, inspired by the brain of the nematode, C. elegans. In the worm's nervous system, neurons communicate through nonlinear time-varying synaptic links established amongst them by their particular wiring structure. This property enables neurons to express liquid time-constants dynamics and therefore allows the network to originate complex behaviors with a small number of neurons. We identify neuron-pair communication motifs as design operators and use them to configure compact neuronal network structures to govern sequential robotic tasks. The networks are systematically designed to map the environmental observations to motor actions, by their hierarchical topology from sensory neurons, through recurrently-wired interneurons, to motor neurons. The networks are then parametrized in a supervised-learning scheme by a search-based algorithm. We demonstrate that obtained networks realize interpretable dynamics. We evaluate their performance in controlling mobile and arm robots, and compare their attributes to other artificial neural network-based control agents. Finally, we experimentally show their superior resilience to environmental noise, compared to the existing machine learning-based methods.

Determinacy in discrete-bidding infinite-duration games - Aghajohari, Milad; Avni, Guy; Henzinger, Thomas A
In two-player games on graphs, the players move a token through a graph to produce an infinite path, which determines the winner of the game. Such games are central in formal methods since they model the interaction between a non-terminating system and its environment. In bidding games the players bid for the right to move the token: in each round, the players simultaneously submit bids, and the higher bidder moves the token and pays the other player. Bidding games are known to have a clean and elegant mathematical structure that relies on the ability of the players to submit arbitrarily small bids. Many applications, however, require a fixed granularity for the bids, which can represent, for example, the monetary value expressed in cents. We study, for the first time, the combination of discrete-bidding and infinite-duration games. Our most important result proves that these games form a large determined subclass of concurrent games, where determinacy is the strong property that there always exists exactly one player who can guarantee winning the game. In particular, we show that, in contrast to non-discrete bidding games, the mechanism with which tied bids are resolved plays an important role in discrete-bidding games. We study several natural tie-breaking mechanisms and show that, while some do not admit determinacy, most natural mechanisms imply determinacy for every pair of initial budgets.

Long-run average behavior of vector addition systems with states - Chatterjee, Krishnendu; Henzinger, Thomas A; Otop, Jan
A vector addition system with states (VASS) consists of a finite set of states and counters. A configuration is a state and a value for each counter; a transition changes the state and each counter is incremented, decremented, or left unchanged. While qualitative properties such as state and configuration reachability have been studied for VASS, we consider the long-run average cost of infinite computations of VASS. The cost of a configuration is for each state, a linear combination of the counter values. In the special case of uniform cost functions, the linear combination is the same for all states. The (regular) long-run emptiness problem is, given a VASS, a cost function, and a threshold value, if there is a (lasso-shaped) computation such that the long-run average value of the cost function does not exceed the threshold. For uniform cost functions, we show that the regular long-run emptiness problem is (a) decidable in polynomial time for integer-valued VASS, and (b) decidable but nonelementarily hard for natural-valued VASS (i.e., nonnegative counters). For general cost functions, we show that the problem is (c) NP-complete for integer-valued VASS, and (d) undecidable for natural-valued VASS. Our most interesting result is for (c) integer-valued VASS with general cost functions, where we establish a connection between the regular long-run emptiness problem and quadratic Diophantine inequalities. The general (nonregular) long-run emptiness problem is equally hard as the regular problem in all cases except (c), where it remains open.

Response characterization for auditing cell dynamics in long short-term memory networks - Hasani, Ramin; Amini, Alexander; Lechner, Mathias; Naser, Felix; Grosu, Radu; Rus, Daniela (Proceedings of the International Joint Conference on Neural Networks)
In this paper, we introduce a novel method to interpret recurrent neural networks (RNNs), particularly long short-term memory networks (LSTMs) at the cellular level. We propose a systematic pipeline for interpreting individual hidden state dynamics within the network using response characterization methods. The ranked contribution of individual cells to the network's output is computed by analyzing a set of interpretable metrics of their decoupled step and sinusoidal responses. As a result, our method is able to uniquely identify neurons with insightful dynamics, quantify relationships between dynamical properties and test accuracy through ablation analysis, and interpret the impact of network capacity on a network's dynamical distribution. Finally, we demonstrate the generalizability and scalability of our method by evaluating a series of different benchmark sequential datasets.

Continuous-time models for system design and analysis - Alur, Rajeev; Giacobbe, Mirco; Henzinger, Thomas A; Larsen, Kim G.; Mikučionis, Marius (Computing and Software Science)
We illustrate the ingredients of the state-of-the-art of model-based approach for the formal design and verification of cyber-physical systems. To capture the interaction between a discrete controller and its continuously evolving environment, we use the formal models of timed and hybrid automata. We explain the steps of modeling and verification in the tools Uppaal and SpaceEx using a case study based on a dual-chamber implantable pacemaker monitoring a human heart. We show how to design a model as a composition of components, how to construct models at varying levels of detail, how to establish that one model is an abstraction of another, how to specify correctness requirements using temporal logic, and how to verify that a model satisfies a logical requirement.

ARCH-COMP19 Category Report: Continuous and hybrid systems with nonlinear dynamics - Immler, Fabian; Althoff, Matthias; Benet, Luis; Chapoutot, Alexandre; Chen, Xin; Forets, Marcelo; Geretti, Luca; Kochdumper, Niklas; Sanders, David P.; Schilling, Christian (EPiC Series in Computing)
We present the results of a friendly competition for formal verification of continuous and hybrid systems with nonlinear continuous dynamics. The friendly competition took place as part of the workshop Applied Verification for Continuous and Hybrid Systems (ARCH) in 2019. In this year, 6 tools Ariadne, CORA, DynIbex, Flow*, Isabelle/HOL, and JuliaReach (in alphabetic order) participated. They are applied to solve reachability analysis problems on four benchmark problems, one of them with hybrid dynamics. We do not rank the tools based on the results, but show the current status and discover the potential advantages of different tools.

ARCH-COMP19 Category Report: Continuous and hybrid systems with linear continuous dynamics - Althoff, Matthias; Bak, Stanley; Forets, Marcelo; Frehse, Goran; Kochdumper, Niklas; Ray, Rajarshi; Schilling, Christian; Schupp, Stefan (EPiC Series in Computing)
This report presents the results of a friendly competition for formal verification of continuous and hybrid systems with linear continuous dynamics. The friendly competition took place as part of the workshop Applied Verification for Continuous and Hybrid Systems (ARCH) in 2019. In its third edition, seven tools have been applied to solve six different benchmark problems in the category for linear continuous dynamics (in alphabetical order): CORA, CORA/SX, HyDRA, Hylaa, JuliaReach, SpaceEx, and XSpeed. This report is a snapshot of the current landscape of tools and the types of benchmarks they are particularly suited for. Due to the diversity of problems, we are not ranking tools, yet the presented results provide one of the most complete assessments of tools for the safety verification of continuous and hybrid systems with linear continuous dynamics up to this date.

Bidding mechanisms in graph games - Avni, Guy; Henzinger, Thomas A; Zikelic, Dorde
In two-player games on graphs, the players move a token through a graph to produce a finite or infinite path, which determines the qualitative winner or quantitative payoff of the game. We study bidding games in which the players bid for the right to move the token. Several bidding rules were studied previously. In Richman bidding, in each round, the players simultaneously submit bids, and the higher bidder moves the token and pays the other player. Poorman bidding is similar except that the winner of the bidding pays the "bank" rather than the other player. Taxman bidding spans the spectrum between Richman and poorman bidding. They are parameterized by a constant tau in [0,1]: portion tau of the winning bid is paid to the other player, and portion 1-tau to the bank. While finite-duration (reachability) taxman games have been studied before, we present, for the first time, results on infinite-duration taxman games. It was previously shown that both Richman and poorman infinite-duration games with qualitative objectives reduce to reachability games, and we show a similar result here. Our most interesting results concern quantitative taxman games, namely mean-payoff games, where poorman and Richman bidding differ significantly. A central quantity in these games is the ratio between the two players' initial budgets. While in poorman mean-payoff games, the optimal payoff of a player depends on the initial ratio, in Richman bidding, the payoff depends only on the structure of the game. In both games the optimal payoffs can be found using (different) probabilistic connections with random-turn games in which in each turn, instead of bidding, a coin is tossed to determine which player moves. While the value with Richman bidding equals the value of a random-turn game with an un-biased coin, with poorman bidding, the bias in the coin is the initial ratio of the budgets. We give a complete classification of mean-payoff taxman games that is based on a probabilistic connection: the value of a taxman bidding game with parameter tau and initial ratio r, equals the value of a random-turn game that uses a coin with bias F(tau, r) = (r+tau * (1-r))/(1+tau). Thus, we show that Richman bidding is the exception; namely, for every tau <1, the value of the game depends on the initial ratio. Our proof technique simplifies and unifies the previous proof techniques for both Richman and poorman bidding.

Semantic fault localization and suspiciousness ranking - Christakis, Maria; Heizmann, Matthias; Mansur, Muhammad Numair; Schilling, Christian; Wüstholz, Valentin (25th International Conference on Tools and Algorithms for the Construction and Analysis of Systems)
Static program analyzers are increasingly effective in checking correctness properties of programs and reporting any errors found, often in the form of error traces. However, developers still spend a significant amount of time on debugging. This involves processing long error traces in an effort to localize a bug to a relatively small part of the program and to identify its cause. In this paper, we present a technique for automated fault localization that, given a program and an error trace, efficiently narrows down the cause of the error to a few statements. These statements are then ranked in terms of their suspiciousness. Our technique relies only on the semantics of the given program and does not require any test cases or user guidance. In experiments on a set of C benchmarks, we show that our technique is effective in quickly isolating the cause of error while out-performing other state-of-the-art fault-localization techniques.

JuliaReach: A toolbox for set-based reachability - Bogomolov, Sergiy; Forets, Marcelo; Frehse, Goran; Potomkin, Kostiantyn; Schilling, Christian (Proceedings of the 22nd International Conference on Hybrid Systems: Computation and Control)
We present JuliaReach, a toolbox for set-based reachability analysis of dynamical systems. JuliaReach consists of two main packages: Reachability, containing implementations of reachability algorithms for continuous and hybrid systems, and LazySets, a standalone library that implements state-of-the-art algorithms for calculus with convex sets. The library offers both concrete and lazy set representations, where the latter stands for the ability to delay set computations until they are needed. The choice of the programming language Julia and the accompanying documentation of our toolbox allow researchers to easily translate set-based algorithms from mathematics to software in a platform-independent way, while achieving runtime performance that is comparable to statically compiled languages. Combining lazy operations in high dimensions and explicit computations in low dimensions, JuliaReach can be applied to solve complex, large-scale problems.
Keywords: reachability analysis; hybrid systems; lazy computation

Interface-aware signal temporal logic - Ferrere, Thomas; Nickovic, Dejan; Donzé, Alexandre; Ito, Hisahiro; Kapinski, James (Proceedings of the 2019 22nd ACM International Conference on Hybrid Systems: Computation and Control)
Safety and security are major concerns in the development of Cyber-Physical Systems (CPS). Signal temporal logic (STL) was proposedas a language to specify and monitor the correctness of CPS relativeto formalized requirements. Incorporating STL into a developmentprocess enables designers to automatically monitor and diagnosetraces, compute robustness estimates based on requirements, andperform requirement falsification, leading to productivity gains inverification and validation activities; however, in its current formSTL is agnostic to the input/output classification of signals, andthis negatively impacts the relevance of the analysis results.In this paper we propose to make the interface explicit in theSTL language by introducing input/output signal declarations. Wethen define new measures of input vacuity and output robustnessthat better reflect the nature of the system and the specification in-tent. The resulting framework, which we call interface-aware signaltemporal logic (IA-STL), aids verification and validation activities.We demonstrate the benefits of IA-STL on several CPS analysisactivities: (1) robustness-driven sensitivity analysis, (2) falsificationand (3) fault localization. We describe an implementation of our en-hancement to STL and associated notions of robustness and vacuityin a prototype extension of Breach, a MATLAB®/Simulink®toolboxfor CPS verification and validation. We explore these methodologi-cal improvements and evaluate our results on two examples fromthe automotive domain: a benchmark powertrain control systemand a hydrogen fuel cell system.

Run-time optimization for learned controllers through quantitative games - Avni, Guy; Bloem, Roderick; Chatterjee, Krishnendu; Henzinger, Thomas A; Konighofer, Bettina; Pranger, Stefan (31st International Conference on Computer-Aided Verification)
A controller is a device that interacts with a plant. At each time point,it reads the plant’s state and issues commands with the goal that the plant oper-ates optimally. Constructing optimal controllers is a fundamental and challengingproblem. Machine learning techniques have recently been successfully applied totrain controllers, yet they have limitations. Learned controllers are monolithic andhard to reason about. In particular, it is difficult to add features without retraining,to guarantee any level of performance, and to achieve acceptable performancewhen encountering untrained scenarios. These limitations can be addressed bydeploying quantitative run-timeshieldsthat serve as a proxy for the controller.At each time point, the shield reads the command issued by the controller andmay choose to alter it before passing it on to the plant. We show how optimalshields that interfere as little as possible while guaranteeing a desired level ofcontroller performance, can be generated systematically and automatically usingreactive synthesis. First, we abstract the plant by building a stochastic model.Second, we consider the learned controller to be a black box. Third, we mea-surecontroller performanceandshield interferenceby two quantitative run-timemeasures that are formally defined using weighted automata. Then, the problemof constructing a shield that guarantees maximal performance with minimal inter-ference is the problem of finding an optimal strategy in a stochastic2-player game“controller versus shield” played on the abstract state space of the plant with aquantitative objective obtained from combining the performance and interferencemeasures. We illustrate the effectiveness of our approach by automatically con-structing lightweight shields for learned traffic-light controllers in various roadnetworks. The shields we generate avoid liveness bugs, improve controller per-formance in untrained and changing traffic situations, and add features to learnedcontrollers, such as giving priority to emergency vehicles.

Membership-based synthesis of linear hybrid automata - Garcia Soto, Miriam; Henzinger, Thomas A; Schilling, Christian; Zeleznik, Luka (31st International Conference on Computer-Aided Verification)
We present two algorithmic approaches for synthesizing linear hybrid automata from experimental data. Unlike previous approaches, our algorithms work without a template and generate an automaton with nondeterministic guards and invariants, and with an arbitrary number and topology of modes. They thus construct a succinct model from the data and provide formal guarantees. In particular, (1) the generated automaton can reproduce the data up to a specified tolerance and (2) the automaton is tight, given the first guarantee. Our first approach encodes the synthesis problem as a logical formula in the theory of linear arithmetic, which can then be solved by an SMT solver. This approach minimizes the number of modes in the resulting model but is only feasible for limited data sets. To address scalability, we propose a second approach that does not enforce to find a minimal model. The algorithm constructs an initial automaton and then iteratively extends the automaton based on processing new data. Therefore the algorithm is well-suited for online and synthesis-in-the-loop applications. The core of the algorithm is a membership query that checks whether, within the specified tolerance, a given data set can result from the execution of a given automaton. We solve this membership problem for linear hybrid automata by repeated reachability computations. We demonstrate the effectiveness of the algorithm on synthetic data sets and on cardiac-cell measurements.
Keywords: Synthesis; Linear hybrid automaton; Membership

Infinite-duration bidding games - Avni, Guy; Henzinger, Thomas A; Chonev, Ventsislav K (Journal of the ACM)
Two-player games on graphs are widely studied in formal methods, as they model the interaction between a system and its environment. The game is played by moving a token throughout a graph to produce an infinite path. There are several common modes to determine how the players move the token through the graph; e.g., in turn-based games the players alternate turns in moving the token. We study the bidding mode of moving the token, which, to the best of our knowledge, has never been studied in infinite-duration games. The following bidding rule was previously defined and called Richman bidding. Both players have separate budgets, which sum up to 1. In each turn, a bidding takes place: Both players submit bids simultaneously, where a bid is legal if it does not exceed the available budget, and the higher bidder pays his bid to the other player and moves the token. The central question studied in bidding games is a necessary and sufficient initial budget for winning the game: a threshold budget in a vertex is a value t ∈ [0, 1] such that if Player 1’s budget exceeds t, he can win the game; and if Player 2’s budget exceeds 1 − t, he can win the game. Threshold budgets were previously shown to exist in every vertex of a reachability game, which have an interesting connection with random-turn games—a sub-class of simple stochastic games in which the player who moves is chosen randomly. We show the existence of threshold budgets for a qualitative class of infinite-duration games, namely parity games, and a quantitative class, namely mean-payoff games. The key component of the proof is a quantitative solution to strongly connected mean-payoff bidding games in which we extend the connection with random-turn games to these games, and construct explicit optimal strategies for both players.

From real-time logic to timed automata - Ferrere, Thomas; Maler, Oded; Ničković, Dejan; Pnueli, Amir (Journal of the ACM)
We show how to construct temporal testers for the logic MITL, a prominent linear-time logic for real-time systems. A temporal tester is a transducer that inputs a signal holding the Boolean value of atomic propositions and outputs the truth value of a formula along time. Here we consider testers over continuous-time Boolean signals that use clock variables to enforce duration constraints, as in timed automata. We first rewrite the MITL formula into a “simple” formula using a limited set of temporal modalities. We then build testers for these specific modalities and show how to compose testers for simple formulae into complex ones. Temporal testers can be turned into acceptors, yielding a compositional translation from MITL to timed automata. This construction is much simpler than previously known and remains asymptotically optimal. It supports both past and future operators and can easily be extended.

Transient memory in gene regulation - Guet, Calin C; Henzinger, Thomas A; Igler, Claudia; Petrov, Tatjana; Sezgin, Ali (17th International Conference on Computational Methods in Systems Biology)
The expression of a gene is characterised by its transcription factors and the function processing them. If the transcription factors are not affected by gene products, the regulating function is often represented as a combinational logic circuit, where the outputs (product) are determined by current input values (transcription factors) only, and are hence independent on their relative arrival times. However, the simultaneous arrival of transcription factors (TFs) in genetic circuits is a strong assumption, given that the processes of transcription and translation of a gene into a protein introduce intrinsic time delays and that there is no global synchronisation among the arrival times of different molecular species at molecular targets. In this paper, we construct an experimentally implementable genetic circuit with two inputs and a single output, such that, in presence of small delays in input arrival, the circuit exhibits qualitatively distinct observable phenotypes. In particular, these phenotypes are long lived transients: they all converge to a single value, but so slowly, that they seem stable for an extended time period, longer than typical experiment duration. We used rule-based language to prototype our circuit, and we implemented a search for finding the parameter combinations raising the phenotypes of interest. The behaviour of our prototype circuit has wide implications. First, it suggests that GRNs can exploit event timing to create phenotypes. Second, it opens the possibility that GRNs are using event timing to react to stimuli and memorise events, without explicit feedback in regulation. From the modelling perspective, our prototype circuit demonstrates the critical importance of analysing the transient dynamics at the promoter binding sites of the DNA, before applying rapid equilibrium assumptions.

Shape expressions for specifying and extracting signal features - Ničković, Dejan; Qin, Xin; Ferrere, Thomas; Mateis, Cristinel; Deshmukh, Jyotirmoy (19th International Conference on Runtime Verification)
Cyber-physical systems (CPS) and the Internet-of-Things (IoT) result in a tremendous amount of generated, measured and recorded time-series data. Extracting temporal segments that encode patterns with useful information out of these huge amounts of data is an extremely difficult problem. We propose shape expressions as a declarative formalism for specifying, querying and extracting sophisticated temporal patterns from possibly noisy data. Shape expressions are regular expressions with arbitrary (linear, exponential, sinusoidal, etc.) shapes with parameters as atomic predicates and additional constraints on these parameters. We equip shape expressions with a novel noisy semantics that combines regular expression matching semantics with statistical regression. We characterize essential properties of the formalism and propose an efficient approximate shape expression matching procedure. We demonstrate the wide applicability of this technique on two case studies.

Piecewise robust barrier tubes for nonlinear hybrid systems with uncertainty - Kong, Hui; Bartocci, Ezio; Jiang, Yu; Henzinger, Thomas A (17th International Conference on Formal Modeling and Analysis of Timed Systems)
Piecewise Barrier Tubes (PBT) is a new technique for flowpipe overapproximation for nonlinear systems with polynomial dynamics, which leverages a combination of barrier certificates. PBT has advantages over traditional time-step based methods in dealing with those nonlinear dynamical systems in which there is a large difference in speed between trajectories, producing an overapproximation that is time independent. However, the existing approach for PBT is not efficient due to the application of interval methods for enclosure-box computation, and it can only deal with continuous dynamical systems without uncertainty. In this paper, we extend the approach with the ability to handle both continuous and hybrid dynamical systems with uncertainty that can reside in parameters and/or noise. We also improve the efficiency of the method significantly, by avoiding the use of interval-based methods for the enclosure-box computation without loosing soundness. We have developed a C++ prototype implementing the proposed approach and we evaluate it on several benchmarks. The experiments show that our approach is more efficient and precise than other methods in the literature.

Mixed-time signal temporal logic - Ferrere, Thomas; Maler, Oded; Nickovic, Dejan (17th International Conference on Formal Modeling and Analysis of Timed Systems)
We present Mixed-time Signal Temporal Logic (STL−MX), a specification formalism which extends STL by capturing the discrete/ continuous time duality found in many cyber-physical systems (CPS), as well as mixed-signal electronic designs. In STL−MX, properties of components with continuous dynamics are expressed in STL, while specifications of components with discrete dynamics are written in LTL. To combine the two layers, we evaluate formulas on two traces, discrete- and continuous-time, and introduce two interface operators that map signals, properties and their satisfaction signals across the two time domains. We show that STL-mx has the expressive power of STL supplemented with an implicit T-periodic clock signal. We develop and implement an algorithm for monitoring STL-mx formulas and illustrate the approach using a mixed-signal example.

Automatic time-unbounded reachability analysis of hybrid systems - Giacobbe, Mirco
Hybrid automata combine finite automata and dynamical systems, and model the interaction of digital with physical systems. Formal analysis that can guarantee the safety of all behaviors or rigorously witness failures, while unsolvable in general, has been tackled algorithmically using, e.g., abstraction, bounded model-checking, assisted theorem proving. Nevertheless, very few methods have addressed the time-unbounded reachability analysis of hybrid automata and, for current sound and automatic tools, scalability remains critical. We develop methods for the polyhedral abstraction of hybrid automata, which construct coarse overapproximations and tightens them incrementally, in a CEGAR fashion. We use template polyhedra, i.e., polyhedra whose facets are normal to a given set of directions. While, previously, directions were given by the user, we introduce (1) the first method for computing template directions from spurious counterexamples, so as to generalize and eliminate them. The method applies naturally to convex hybrid automata, i.e., hybrid automata with (possibly non-linear) convex constraints on derivatives only, while for linear ODE requires further abstraction. Specifically, we introduce (2) the conic abstractions, which, partitioning the state space into appropriate (possibly non-uniform) cones, divide curvy trajectories into relatively straight sections, suitable for polyhedral abstractions. Finally, we introduce (3) space-time interpolation, which, combining interval arithmetic and template refinement, computes appropriate (possibly non-uniform) time partitioning and template directions along spurious trajectories, so as to eliminate them. We obtain sound and automatic methods for the reachability analysis over dense and unbounded time of convex hybrid automata and hybrid automata with linear ODE. We build prototype tools and compare—favorably—our methods against the respective state-of-the-art tools, on several benchmarks.

Handbook of Model Checking - Clarke, Edmund M.; Henzinger, Thomas A; Veith, Helmut; Bloem, Roderick
This book first explores the origins of this idea, grounded in theoretical work on temporal logic and automata. The editors and authors are among the world's leading researchers in this domain, and they contributed 32 chapters representing a thorough view of the development and application of the technique. Topics covered include binary decision diagrams, symbolic model checking, satisfiability modulo theories, partial-order reduction, abstraction, interpolation, concurrency, security protocols, games, probabilistic model checking, and process algebra, and chapters on the transfer of theory to industrial practice, property specification languages for hardware, and verification of real-time systems and hybrid systems. The book will be valuable for researchers and graduate students engaged with the development of formal methods and verification tools.

Introduction to model checking - Clarke, Edmund; Henzinger, Thomas A; Veith, Helmut (Handbook of Model Checking)
Model checking is a computer-assisted method for the analysis of dynamical systems that can be modeled by state-transition systems. Drawing from research traditions in mathematical logic, programming languages, hardware design, and theoretical computer science, model checking is now widely used for the verification of hardware and software in industry. This chapter is an introduction and short survey of model checking. The chapter aims to motivate and link the individual chapters of the handbook, and to provide context for readers who are not familiar with model checking.

Computing average response time - Chatterjee, Krishnendu; Henzinger, Thomas A; Otop, Jan (Principles of Modeling)
Responsiveness—the requirement that every request to a system be eventually handled—is one of the fundamental liveness properties of a reactive system. Average response time is a quantitative measure for the responsiveness requirement used commonly in performance evaluation. We show how average response time can be computed on state-transition graphs, on Markov chains, and on game graphs. In all three cases, we give polynomial-time algorithms.

Timed network games with clocks - Avni, Guy; Guha, Shibashis; Kupferman, Orna
Network games are widely used as a model for selfish resource-allocation problems. In the classicalmodel, each player selects a path connecting her source and target vertices. The cost of traversingan edge depends on theload; namely, number of players that traverse it. Thus, it abstracts the factthat different users may use a resource at different times and for different durations, which playsan important role in determining the costs of the users in reality. For example, when transmittingpackets in a communication network, routing traffic in a road network, or processing a task in aproduction system, actual sharing and congestion of resources crucially depends on time.In [13], we introducedtimed network games, which add a time component to network games.Each vertexvin the network is associated with a cost function, mapping the load onvto theprice that a player pays for staying invfor one time unit with this load. Each edge in thenetwork is guarded by the time intervals in which it can be traversed, which forces the players tospend time in the vertices. In this work we significantly extend the way time can be referred toin timed network games. In the model we study, the network is equipped withclocks, and, as intimed automata, edges are guarded by constraints on the values of the clocks, and their traversalmay involve a reset of some clocks. We argue that the stronger model captures many realisticnetworks. The addition of clocks breaks the techniques we developed in [13] and we developnew techniques in order to show that positive results on classic network games carry over to thestronger timed setting.

Synchronizing the asynchronous - Kragl, Bernhard; Qadeer, Shaz; Henzinger, Thomas A
Synchronous programs are easy to specify because the side effects of an operation are finished by the time the invocation of the operation returns to the caller. Asynchronous programs, on the other hand, are difficult to specify because there are side effects due to pending computation scheduled as a result of the invocation of an operation. They are also difficult to verify because of the large number of possible interleavings of concurrent computation threads. We present synchronization, a new proof rule that simplifies the verification of asynchronous programs by introducing the fiction, for proof purposes, that asynchronous operations complete synchronously. Synchronization summarizes an asynchronous computation as immediate atomic effect. Modular verification is enabled via pending asynchronous calls in atomic summaries, and a complementary proof rule that eliminates pending asynchronous calls when components and their specifications are composed. We evaluate synchronization in the context of a multi-layer refinement verification methodology on a collection of benchmark programs.

AMT 2.0: Qualitative and quantitative trace analysis with extended signal temporal logic - Nickovic, Dejan; Lebeltel, Olivier; Maler, Oded; Ferrere, Thomas; Ulus, Dogan
We introduce in this paper AMT 2.0 , a tool for qualitative and quantitative analysis of hybrid continuous and Boolean signals that combine numerical values and discrete events. The evaluation of the signals is based on rich temporal specifications expressed in extended Signal Temporal Logic (xSTL), which integrates Timed Regular Expressions (TRE) within Signal Temporal Logic (STL). The tool features qualitative monitoring (property satisfaction checking), trace diagnostics for explaining and justifying property violations and specification-driven measurement of quantitative features of the signal.

A theory of register monitors - Ferrere, Thomas; Henzinger, Thomas A; Saraç, Ege
The task of a monitor is to watch, at run-time, the execution of a reactive system, and signal the occurrence of a safety violation in the observed sequence of events. While finite-state monitors have been studied extensively, in practice, monitoring software also makes use of unbounded memory. We define a model of automata equipped with integer-valued registers which can execute only a bounded number of instructions between consecutive events, and thus can form the theoretical basis for the study of infinite-state monitors. We classify these register monitors according to the number k of available registers, and the type of register instructions. In stark contrast to the theory of computability for register machines, we prove that for every k 1, monitors with k + 1 counters (with instruction set 〈+1, =〉) are strictly more expressive than monitors with k counters. We also show that adder monitors (with instruction set 〈1, +, =〉) are strictly more expressive than counter monitors, but are complete for monitoring all computable safety -languages for k = 6. Real-time monitors are further required to signal the occurrence of a safety violation as soon as it occurs. The expressiveness hierarchy for counter monitors carries over to real-time monitors. We then show that 2 adders cannot simulate 3 counters in real-time. Finally, we show that real-time adder monitors with inequalities are as expressive as real-time Turing machines.

Efficient parametric identification for STL - Bakhirkin, Alexey; Ferrere, Thomas; Maler, Oded (Proceedings of the 21st International Conference on Hybrid Systems)
We describe a new algorithm for the parametric identification problem for signal temporal logic (STL), stated as follows. Given a densetime real-valued signal w and a parameterized temporal logic formula φ, compute the subset of the parameter space that renders the formula satisfied by the signal. Unlike previous solutions, which were based on search in the parameter space or quantifier elimination, our procedure works recursively on φ and computes the evolution over time of the set of valid parameter assignments. This procedure is similar to that of monitoring or computing the robustness of φ relative to w. Our implementation and experiments demonstrate that this approach can work well in practice.

Infinite-duration poorman-bidding games - Avni, Guy; Henzinger, Thomas A; Ibsen-Jensen, Rasmus
In two-player games on graphs, the players move a token through a graph to produce an infinite path, which determines the winner or payoff of the game. Such games are central in formal verification since they model the interaction between a non-terminating system and its environment. We study bidding games in which the players bid for the right to move the token. Two bidding rules have been defined. In Richman bidding, in each round, the players simultaneously submit bids, and the higher bidder moves the token and pays the other player. Poorman bidding is similar except that the winner of the bidding pays the “bank” rather than the other player. While poorman reachability games have been studied before, we present, for the first time, results on infinite-duration poorman games. A central quantity in these games is the ratio between the two players’ initial budgets. The questions we study concern a necessary and sufficient ratio with which a player can achieve a goal. For reachability objectives, such threshold ratios are known to exist for both bidding rules. We show that the properties of poorman reachability games extend to complex qualitative objectives such as parity, similarly to the Richman case. Our most interesting results concern quantitative poorman games, namely poorman mean-payoff games, where we construct optimal strategies depending on the initial ratio, by showing a connection with random-turn based games. The connection in itself is interesting, because it does not hold for reachability poorman games. We also solve the complexity problems that arise in poorman bidding games.

Layered Concurrent Programs - Kragl, Bernhard; Qadeer, Shaz
We present layered concurrent programs, a compact and expressive notation for specifying refinement proofs of concurrent programs. A layered concurrent program specifies a sequence of connected concurrent programs, from most concrete to most abstract, such that common parts of different programs are written exactly once. These programs are expressed in the ordinary syntax of imperative concurrent programs using gated atomic actions, sequencing, choice, and (recursive) procedure calls. Each concurrent program is automatically extracted from the layered program. We reduce refinement to the safety of a sequence of concurrent checker programs, one each to justify the connection between every two consecutive concurrent programs. These checker programs are also automatically extracted from the layered program. Layered concurrent programs have been implemented in the CIVL verifier which has been successfully used for the verification of several complex concurrent programs.

Localizing faults in simulink/stateflow models with STL - Bartocci, Ezio; Ferrere, Thomas; Manjunath, Niveditha; Nickovic, Dejan
Fault-localization is considered to be a very tedious and time-consuming activity in the design of complex Cyber-Physical Systems (CPS). This laborious task essentially requires expert knowledge of the system in order to discover the cause of the fault. In this context, we propose a new procedure that AIDS designers in debugging Simulink/Stateflow hybrid system models, guided by Signal Temporal Logic (STL) specifications. The proposed method relies on three main ingredients: (1) a monitoring and a trace diagnostics procedure that checks whether a tested behavior satisfies or violates an STL specification, localizes time segments and interfaces variables contributing to the property violations; (2) a slicing procedure that maps these observable behavior segments to the internal states and transitions of the Simulink model; and (3) a spectrum-based fault-localization method that combines the previous analysis from multiple tests to identify the internal states and/or transitions that are the most likely to explain the fault. We demonstrate the applicability of our approach on two Simulink models from the automotive and the avionics domain.

Monitoring temporal logic with clock variables - Elgyütt, Adrian; Ferrere, Thomas; Henzinger, Thomas A
We solve the offline monitoring problem for timed propositional temporal logic (TPTL), interpreted over dense-time Boolean signals. The variant of TPTL we consider extends linear temporal logic (LTL) with clock variables and reset quantifiers, providing a mechanism to specify real-time constraints. We first describe a general monitoring algorithm based on an exhaustive computation of the set of satisfying clock assignments as a finite union of zones. We then propose a specialized monitoring algorithm for the one-variable case using a partition of the time domain based on the notion of region equivalence, whose complexity is linear in the length of the signal, thereby generalizing a known result regarding the monitoring of metric temporal logic (MTL). The region and zone representations of time constraints are known from timed automata verification and can also be used in the discrete-time case. Our prototype implementation appears to outperform previous discrete-time implementations of TPTL monitoring,

Online timed pattern matching using automata - Bakhirkin, Alexey; Ferrere, Thomas; Nickovic, Dejan; Maler, Oded; Asarin, Eugene
We provide a procedure for detecting the sub-segments of an incrementally observed Boolean signal ω that match a given temporal pattern ϕ. As a pattern specification language, we use timed regular expressions, a formalism well-suited for expressing properties of concurrent asynchronous behaviors embedded in metric time. We construct a timed automaton accepting the timed language denoted by ϕ and modify it slightly for the purpose of matching. We then apply zone-based reachability computation to this automaton while it reads ω, and retrieve all the matching segments from the results. Since the procedure is automaton based, it can be applied to patterns specified by other formalisms such as timed temporal logics reducible to timed automata or directly encoded as timed automata. The procedure has been implemented and its performance on synthetic examples is demonstrated.

Parameter-independent strategies for pMDPs via POMDPs - Arming, Sebastian; Bartocci, Ezio; Chatterjee, Krishnendu; Katoen, Joost P; Sokolova, Ana
Markov Decision Processes (MDPs) are a popular class of models suitable for solving control decision problems in probabilistic reactive systems. We consider parametric MDPs (pMDPs) that include parameters in some of the transition probabilities to account for stochastic uncertainties of the environment such as noise or input disturbances. We study pMDPs with reachability objectives where the parameter values are unknown and impossible to measure directly during execution, but there is a probability distribution known over the parameter values. We study for the first time computing parameter-independent strategies that are expectation optimal, i.e., optimize the expected reachability probability under the probability distribution over the parameters. We present an encoding of our problem to partially observable MDPs (POMDPs), i.e., a reduction of our problem to computing optimal strategies in POMDPs. We evaluate our method experimentally on several benchmarks: a motivating (repeated) learner model; a series of benchmarks of varying configurations of a robot moving on a grid; and a consensus protocol.

Reachable set over-approximation for nonlinear systems using piecewise barrier tubes - Kong, Hui; Bartocci, Ezio; Henzinger, Thomas A
We address the problem of analyzing the reachable set of a polynomial nonlinear continuous system by over-approximating the flowpipe of its dynamics. The common approach to tackle this problem is to perform a numerical integration over a given time horizon based on Taylor expansion and interval arithmetic. However, this method results to be very conservative when there is a large difference in speed between trajectories as time progresses. In this paper, we propose to use combinations of barrier functions, which we call piecewise barrier tube (PBT), to over-approximate flowpipe. The basic idea of PBT is that for each segment of a flowpipe, a coarse box which is big enough to contain the segment is constructed using sampled simulation and then in the box we compute by linear programming a set of barrier functions (called barrier tube or BT for short) which work together to form a tube surrounding the flowpipe. The benefit of using PBT is that (1) BT is independent of time and hence can avoid being stretched and deformed by time; and (2) a small number of BTs can form a tight over-approximation for the flowpipe, which means that the computation required to decide whether the BTs intersect the unsafe set can be reduced significantly. We implemented a prototype called PBTS in C++. Experiments on some benchmark systems show that our approach is effective.

Safety-assured model-driven design of the multifunction vehicle bus controller - Jiang, Yu; Liu, Han; Song, Huobing; Kong, Hui; Wang, Rui; Guan, Yong; Sha, Lui (IEEE Transactions on Intelligent Transportation Systems)
In this paper, we present a formal model-driven design approach to establish a safety-assured implementation of multifunction vehicle bus controller (MVBC), which controls the data transmission among the devices of the vehicle. First, the generic models and safety requirements described in International Electrotechnical Commission Standard 61375 are formalized as time automata and timed computation tree logic formulas, respectively. With model checking tool Uppaal, we verify whether or not the constructed timed automata satisfy the formulas and several logic inconsistencies in the original standard are detected and corrected. Then, we apply the code generation tool Times to generate C code from the verified model, which is later synthesized into a real MVBC chip, with some handwriting glue code. Furthermore, the runtime verification tool RMOR is applied on the integrated code, to verify some safety requirements that cannot be formalized on the timed automata. For evaluation, we compare the proposed approach with existing MVBC design methods, such as BeagleBone, Galsblock, and Simulink. Experiments show that more ambiguousness or bugs in the standard are detected during Uppaal verification, and the generated code of Times outperforms the C code generated by others in terms of the synthesized binary code size. The errors in the standard have been confirmed and the resulting MVBC has been deployed in the real train communication network.

Space-time interpolants - Frehse, Goran; Giacobbe, Mirco; Henzinger, Thomas A
Reachability analysis is difficult for hybrid automata with affine differential equations, because the reach set needs to be approximated. Promising abstraction techniques usually employ interval methods or template polyhedra. Interval methods account for dense time and guarantee soundness, and there are interval-based tools that overapproximate affine flowpipes. But interval methods impose bounded and rigid shapes, which make refinement expensive and fixpoint detection difficult. Template polyhedra, on the other hand, can be adapted flexibly and can be unbounded, but sound template refinement for unbounded reachability analysis has been implemented only for systems with piecewise constant dynamics. We capitalize on the advantages of both techniques, combining interval arithmetic and template polyhedra, using the former to abstract time and the latter to abstract space. During a CEGAR loop, whenever a spurious error trajectory is found, we compute additional space constraints and split time intervals, and use these space-time interpolants to eliminate the counterexample. Space-time interpolation offers a lazy, flexible framework for increasing precision while guaranteeing soundness, both for error avoidance and fixpoint detection. To the best of out knowledge, this is the first abstraction refinement scheme for the reachability analysis over unbounded and dense time of affine hybrid systems, which is both sound and automatic. We demonstrate the effectiveness of our algorithm with several benchmark examples, which cannot be handled by other tools.

Strategy representation by decision trees in reactive synthesis - Brázdil, Tomáš; Chatterjee, Krishnendu; Kretinsky, Jan; Toman, Viktor
Graph games played by two players over finite-state graphs are central in many problems in computer science. In particular, graph games with ω -regular winning conditions, specified as parity objectives, which can express properties such as safety, liveness, fairness, are the basic framework for verification and synthesis of reactive systems. The decisions for a player at various states of the graph game are represented as strategies. While the algorithmic problem for solving graph games with parity objectives has been widely studied, the most prominent data-structure for strategy representation in graph games has been binary decision diagrams (BDDs). However, due to the bit-level representation, BDDs do not retain the inherent flavor of the decisions of strategies, and are notoriously hard to minimize to obtain succinct representation. In this work we propose decision trees for strategy representation in graph games. Decision trees retain the flavor of decisions of strategies and allow entropy-based minimization to obtain succinct trees. However, decision trees work in settings (e.g., probabilistic models) where errors are allowed, and overfitting of data is typically avoided. In contrast, for strategies in graph games no error is allowed, and the decision tree must represent the entire strategy. We develop new techniques to extend decision trees to overcome the above obstacles, while retaining the entropy-based techniques to obtain succinct trees. We have implemented our techniques to extend the existing decision tree solvers. We present experimental results for problems in reactive synthesis to show that decision trees provide a much more efficient data-structure for strategy representation as compared to BDDs.

Synthesis from component libraries with costs - Avni, Guy; Kupferman, Orna (Theoretical Computer Science)
Synthesis is the automated construction of a system from its specification. In real life, hardware and software systems are rarely constructed from scratch. Rather, a system is typically constructed from a library of components. Lustig and Vardi formalized this intuition and studied LTL synthesis from component libraries. In real life, designers seek optimal systems. In this paper we add optimality considerations to the setting. We distinguish between quality considerations (for example, size - the smaller a system is, the better it is), and pricing (for example, the payment to the company who manufactured the component). We study the problem of designing systems with minimal quality-cost and price. A key point is that while the quality cost is individual - the choices of a designer are independent of choices made by other designers that use the same library, pricing gives rise to a resource-allocation game - designers that use the same component share its price, with the share being proportional to the number of uses (a component can be used several times in a design). We study both closed and open settings, and in both we solve the problem of finding an optimal design. In a setting with multiple designers, we also study the game-theoretic problems of the induced resource-allocation game.

The compound interest in relaxing punctuality - Ferrere, Thomas
Imprecision in timing can sometimes be beneficial: Metric interval temporal logic (MITL), disabling the expression of punctuality constraints, was shown to translate to timed automata, yielding an elementary decision procedure. We show how this principle extends to other forms of dense-time specification using regular expressions. By providing a clean, automaton-based formal framework for non-punctual languages, we are able to recover and extend several results in timed systems. Metric interval regular expressions (MIRE) are introduced, providing regular expressions with non-singular duration constraints. We obtain that MIRE are expressively complete relative to a class of one-clock timed automata, which can be determinized using additional clocks. Metric interval dynamic logic (MIDL) is then defined using MIRE as temporal modalities. We show that MIDL generalizes known extensions of MITL, while translating to timed automata at comparable cost.

Keynote: The first-order logic of signals - Bakhirkin, Alexey; Ferrere, Thomas; Henzinger, Thomas A; Nickovicl, Deian (2018 International Conference on Embedded Software)
Formalizing properties of systems with continuous dynamics is a challenging task. In this paper, we propose a formal framework for specifying and monitoring rich temporal properties of real-valued signals. We introduce signal first-order logic (SFO) as a specification language that combines first-order logic with linear-real arithmetic and unary function symbols interpreted as piecewise-linear signals. We first show that while the satisfiability problem for SFO is undecidable, its membership and monitoring problems are decidable. We develop an offline monitoring procedure for SFO that has polynomial complexity in the size of the input trace and the specification, for a fixed number of quantifiers and function symbols. We show that the algorithm has computation time linear in the size of the input trace for the important fragment of bounded-response specifications interpreted over input traces with finite variability. We can use our results to extend signal temporal logic with first-order quantifiers over time and value parameters, while preserving its efficient monitoring. We finally demonstrate the practical appeal of our logic through a case study in the micro-electronics domain.

Expectation optimization with probabilistic guarantees in POMDPs with discounted-sum objectives - Chatterjee, Krishnendu; Elgyütt, Adrian; Novotny, Petr; Rouillé, Owen
Partially-observable Markov decision processes (POMDPs) with discounted-sum payoff are a standard framework to model a wide range of problems related to decision making under uncertainty. Traditionally, the goal has been to obtain policies that optimize the expectation of the discounted-sum payoff. A key drawback of the expectation measure is that even low probability events with extreme payoff can significantly affect the expectation, and thus the obtained policies are not necessarily risk-averse. An alternate approach is to optimize the probability that the payoff is above a certain threshold, which allows obtaining risk-averse policies, but ignores optimization of the expectation. We consider the expectation optimization with probabilistic guarantee (EOPG) problem, where the goal is to optimize the expectation ensuring that the payoff is above a given threshold with at least a specified probability. We present several results on the EOPG problem, including the first algorithm to solve it.

An abstraction-refinement methodology for reasoning about network games - Avni, Guy; Guha, Shibashis; Kupferman, Orna (Games)
Network games (NGs) are played on directed graphs and are extensively used in network design and analysis. Search problems for NGs include finding special strategy profiles such as a Nash equilibrium and a globally-optimal solution. The networks modeled by NGs may be huge. In formal verification, abstraction has proven to be an extremely effective technique for reasoning about systems with big and even infinite state spaces. We describe an abstraction-refinement methodology for reasoning about NGs. Our methodology is based on an abstraction function that maps the state space of an NG to a much smaller state space. We search for a global optimum and a Nash equilibrium by reasoning on an under- and an over-approximation defined on top of this smaller state space. When the approximations are too coarse to find such profiles, we refine the abstraction function. We extend the abstraction-refinement methodology to labeled networks, where the objectives of the players are regular languages. Our experimental results demonstrate the effectiveness of the methodology.

Contracts for system design - Benveniste, Albert; Nickovic, Dejan; Caillaud, Benoît; Passerone, Roberto; Raclet, Jean Baptiste; Reinkemeier, Philipp; Sangiovanni-Vincentelli, Alberto; Damm, Werner; Henzinger, Thomas A; Larsen, Kim G. (Foundations and Trends in Electronic Design Automation)
Recently, contract-based design has been proposed as an “orthogonal” approach that complements system design methodologies proposed so far to cope with the complexity of system design. Contract-based design provides a rigorous scaffolding for verification, analysis, abstraction/refinement, and even synthesis. A number of results have been obtained in this domain but a unified treatment of the topic that can help put contract-based design in perspective was missing. This monograph intends to provide such a treatment where contracts are precisely defined and characterized so that they can be used in design methodologies with no ambiguity. In particular, this monograph identifies the essence of complex system design using contracts through a mathematical “meta-theory”, where all the properties of the methodology are derived from a very abstract and generic notion of contract. We show that the meta-theory provides deep and illuminating links with existing contract and interface theories, as well as guidelines for designing new theories. Our study encompasses contracts for both software and systems, with emphasis on the latter. We illustrate the use of contracts with two examples: requirement engineering for a parking garage management, and the development of contracts for timing and scheduling in the context of the Autosar methodology in use in the automotive sector.

A new proof rule for almost-sure termination - Mciver, Annabelle; Morgan, Carroll; Kaminski, Benjamin Lucien; Katoen, Joost P (Proceedings of the ACM on Programming Languages)
We present a new proof rule for proving almost-sure termination of probabilistic programs, including those that contain demonic non-determinism. An important question for a probabilistic program is whether the probability mass of all its diverging runs is zero, that is that it terminates "almost surely". Proving that can be hard, and this paper presents a new method for doing so. It applies directly to the program's source code, even if the program contains demonic choice. Like others, we use variant functions (a.k.a. "super-martingales") that are real-valued and decrease randomly on each loop iteration; but our key innovation is that the amount as well as the probability of the decrease are parametric. We prove the soundness of the new rule, indicate where its applicability goes beyond existing rules, and explain its connection to classical results on denumerable (non-demonic) Markov chains.

Faster statistical model checking for unbounded temporal properties - Daca, Przemyslaw; Henzinger, Thomas A; Kretinsky, Jan; Petrov, Tatjana (ACM Transactions on Computational Logic (TOCL))
We present a new algorithm for the statistical model checking of Markov chains with respect to unbounded temporal properties, including full linear temporal logic. The main idea is that we monitor each simulation run on the fly, in order to detect quickly if a bottom strongly connected component is entered with high probability, in which case the simulation run can be terminated early. As a result, our simulation runs are often much shorter than required by termination bounds that are computed a priori for a desired level of confidence on a large state space. In comparison to previous algorithms for statistical model checking our method is not only faster in many cases but also requires less information about the system, namely, only the minimum transition probability that occurs in the Markov chain. In addition, our method can be generalised to unbounded quantitative properties such as mean-payoff bounds.