{"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_updated":"2022-08-05T09:02:56Z","external_id":{"arxiv":["2105.02013"]},"author":[{"full_name":"Bartocci, Ezio","first_name":"Ezio","last_name":"Bartocci"},{"full_name":"Ferrere, Thomas","first_name":"Thomas","orcid":"0000-0001-5199-3143","last_name":"Ferrere","id":"40960E6E-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Henzinger, Thomas A","orcid":"0000-0002-2985-7724","id":"40876CD8-F248-11E8-B48F-1D18A9856A87","last_name":"Henzinger","first_name":"Thomas A"},{"first_name":"Dejan","id":"41BCEE5C-F248-11E8-B48F-1D18A9856A87","last_name":"Nickovic","full_name":"Nickovic, Dejan"},{"first_name":"Ana Oliveira","last_name":"Da Costa","full_name":"Da Costa, Ana Oliveira"}],"alternative_title":["LNCS"],"quality_controlled":"1","doi":"10.1007/978-3-030-94583-1_1","year":"2022","_id":"10774","publication":"Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)","month":"01","citation":{"mla":"Bartocci, Ezio, et al. “Flavors of Sequential Information Flow.” <i>Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)</i>, vol. 13182, Springer Nature, 2022, pp. 1–19, doi:<a href=\"https://doi.org/10.1007/978-3-030-94583-1_1\">10.1007/978-3-030-94583-1_1</a>.","ista":"Bartocci E, Ferrere T, Henzinger TA, Nickovic D, Da Costa AO. 2022. Flavors of sequential information flow. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). VMCAI: Verifcation, Model Checking, and Abstract Interpretation, LNCS, vol. 13182, 1–19.","short":"E. Bartocci, T. Ferrere, T.A. Henzinger, D. Nickovic, A.O. Da Costa, in:, Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer Nature, 2022, pp. 1–19.","ieee":"E. Bartocci, T. Ferrere, T. A. Henzinger, D. Nickovic, and A. O. Da Costa, “Flavors of sequential information flow,” in <i>Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)</i>, Philadelphia, PA, United States, 2022, vol. 13182, pp. 1–19.","ama":"Bartocci E, Ferrere T, Henzinger TA, Nickovic D, Da Costa AO. Flavors of sequential information flow. In: <i>Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)</i>. Vol 13182. Springer Nature; 2022:1-19. doi:<a href=\"https://doi.org/10.1007/978-3-030-94583-1_1\">10.1007/978-3-030-94583-1_1</a>","chicago":"Bartocci, Ezio, Thomas Ferrere, Thomas A Henzinger, Dejan Nickovic, and Ana Oliveira Da Costa. “Flavors of Sequential Information Flow.” In <i>Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)</i>, 13182:1–19. Springer Nature, 2022. <a href=\"https://doi.org/10.1007/978-3-030-94583-1_1\">https://doi.org/10.1007/978-3-030-94583-1_1</a>.","apa":"Bartocci, E., Ferrere, T., Henzinger, T. A., Nickovic, D., &#38; Da Costa, A. O. (2022). Flavors of sequential information flow. In <i>Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)</i> (Vol. 13182, pp. 1–19). Philadelphia, PA, United States: Springer Nature. <a href=\"https://doi.org/10.1007/978-3-030-94583-1_1\">https://doi.org/10.1007/978-3-030-94583-1_1</a>"},"volume":13182,"main_file_link":[{"open_access":"1","url":" https://doi.org/10.48550/arXiv.2105.02013"}],"scopus_import":"1","publication_status":"published","acknowledgement":"This work was funded in part by the Wittgenstein Award Z211-N23 of the Austrian Science Fund (FWF) and by the FWF project W1255-N23.","status":"public","article_processing_charge":"No","title":"Flavors of sequential information flow","date_created":"2022-02-20T23:01:34Z","language":[{"iso":"eng"}],"publication_identifier":{"isbn":["9783030945824"],"eissn":["16113349"],"issn":["03029743"]},"intvolume":"     13182","project":[{"call_identifier":"FWF","name":"The Wittgenstein Prize","_id":"25F42A32-B435-11E9-9278-68D0E5697425","grant_number":"Z211"}],"day":"14","page":"1-19","publisher":"Springer Nature","type":"conference","conference":{"location":"Philadelphia, PA, United States","end_date":"2022-01-18","start_date":"2022-01-16","name":"VMCAI: Verifcation, Model Checking, and Abstract Interpretation"},"oa_version":"Preprint","date_published":"2022-01-14T00:00:00Z","oa":1,"abstract":[{"text":"We study the problem of specifying sequential information-flow properties of systems. Information-flow properties are hyperproperties, as they compare different traces of a system. Sequential information-flow properties can express changes, over time, in the information-flow constraints. For example, information-flow constraints during an initialization phase of a system may be different from information-flow constraints that are required during the operation phase. We formalize several variants of interpreting sequential information-flow constraints, which arise from different assumptions about what can be observed of the system. For this purpose, we introduce a first-order logic, called Hypertrace Logic, with both trace and time quantifiers for specifying linear-time hyperproperties. We prove that HyperLTL, which corresponds to a fragment of Hypertrace Logic with restricted quantifier prefixes, cannot specify the majority of the studied variants of sequential information flow, including all variants in which the transition between sequential phases (such as initialization and operation) happens asynchronously. Our results rely on new equivalences between sets of traces that cannot be distinguished by certain classes of formulas from Hypertrace Logic. This presents a new approach to proving inexpressiveness results for HyperLTL.","lang":"eng"}],"department":[{"_id":"ToHe"}]}