---
res:
bibo_abstract:
- 'A fundamental algorithmic problem at the heart of static analysis is Dyck reachability.
The input is a graphwhere the edges are labeled with different types of opening
and closing parentheses, and the reachabilityinformation is computed via paths
whose parentheses are properly matched. We present new results for Dyckreachability
problems with applications to alias analysis and data-dependence analysis. Our
main contributions,that include improved upper bounds as well as lower bounds
that establish optimality guarantees, are asfollows:First, we consider Dyck reachability
on bidirected graphs, which is the standard way of performing field-sensitive
points-to analysis. Given a bidirected graph withnnodes andmedges, we present:
(i) an algorithmwith worst-case running timeO(m+n·α(n)), whereα(n)is the inverse
Ackermann function, improving thepreviously knownO(n2)time bound; (ii) a matching
lower bound that shows that our algorithm is optimalwrt to worst-case complexity;
and (iii) an optimal average-case upper bound ofO(m)time, improving thepreviously
knownO(m·logn)bound.Second, we consider the problem of context-sensitive data-dependence
analysis, where the task is to obtainanalysis summaries of library code in the
presence of callbacks. Our algorithm preprocesses libraries in almostlinear time,
after which the contribution of the library in the complexity of the client analysis
is only linear,and only wrt the number of call sites.Third, we prove that combinatorial
algorithms for Dyck reachability on general graphs with truly sub-cubic bounds
cannot be obtained without obtaining sub-cubic combinatorial algorithms for Boolean
MatrixMultiplication, which is a long-standing open problem. Thus we establish
that the existing combinatorialalgorithms for Dyck reachability are (conditionally)
optimal for general graphs. We also show that the samehardness holds for graphs
of constant treewidth.Finally, we provide a prototype implementation of our algorithms
for both alias analysis and data-dependenceanalysis. Our experimental evaluation
demonstrates that the new algorithms significantly outperform allexisting methods
on the two problems, over real-world benchmarks.@eng'
bibo_authorlist:
- foaf_Person:
foaf_givenName: Krishnendu
foaf_name: Chatterjee, Krishnendu
foaf_surname: Chatterjee
foaf_workInfoHomepage: http://www.librecat.org/personId=2E5DCA20-F248-11E8-B48F-1D18A9856A87
orcid: 0000-0002-4561-241X
- foaf_Person:
foaf_givenName: Bhavya
foaf_name: Choudhary, Bhavya
foaf_surname: Choudhary
- foaf_Person:
foaf_givenName: Andreas
foaf_name: Pavlogiannis, Andreas
foaf_surname: Pavlogiannis
foaf_workInfoHomepage: http://www.librecat.org/personId=49704004-F248-11E8-B48F-1D18A9856A87
orcid: 0000-0002-8943-0722
bibo_doi: 10.15479/AT:IST-2017-870-v1-1
dct_date: 2017^xs_gYear
dct_isPartOf:
- http://id.crossref.org/issn/2664-1690
dct_language: eng
dct_publisher: IST Austria@
dct_title: Optimal Dyck reachability for data-dependence and alias analysis@
...