By Vijay Ganesh, Adam Kieżun, Shay Artzi, Philip J. Guo (auth.), Ganesh Gopalakrishnan, Shaz Qadeer (eds.)
This ebook constitutes the refereed court cases of the twenty third overseas convention on desktop Aided Verification, CAV 2011, held in Snowbird, UT, united states, in July 2011.The 35 revised complete papers provided including 20 software papers have been rigorously reviewed and chosen from 161 submissions. The papers are equipped in topical sections at the following workshops: 4th overseas Workshop on Numerical software program Verification (NSV 2011), tenth foreign Workshop on Parallel and disbursed tools in Verifications (PDMC 2011), 4th foreign Workshop on Exploiting Concurrency successfully and properly (EC2 2011), Frontiers in Analog Circuit Synthesis and Verification (FAC 2011), overseas Workshop on Satisfiability Modulo Theories, together with SMTCOMP (SMT 2011), 18th foreign SPIN Workshop on version Checking of software program (SPIN 2011), Formal tools for Robotics and Automation (FM-R 2011), and sensible Synthesis for Concurrent platforms (PSY 2011).
Read or Download Computer Aided Verification: 23rd International Conference, CAV 2011, Snowbird, UT, USA, July 14-20, 2011. Proceedings PDF
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Extra info for Computer Aided Verification: 23rd International Conference, CAV 2011, Snowbird, UT, USA, July 14-20, 2011. Proceedings
Example text
5 Related Work Decision procedures have received widespread attention within the context of program analysis, testing, and verification. Decision procedures exist for theories such as Boolean satisfiability [20] and bit-vectors [8]. In contrast, until recently there has been relatively little work on practical and expressive solvers that reason about strings or sets of strings directly. Since this is a tutorial paper we do not discuss related work in detail. Instead we point the reader to our ISSTA 2009 paper [16] for a detailed overview of previous work on decision procedures for theories of strings and practical string solvers.
2 that has been constructed from a hybrid automaton. The natural hybrid program has the same behavior as the hybrid automaton and its corresponding hybrid program, but the natural hybrid program in (2) is significantly easier to understand and also simplifies verification. Finally, the natural hybrid program in (2) is the same as the following hybrid program when resolving abbreviations according to Table 2. z < SB; a := A)); z = v, v = a & v ≥ 0 ∗ This representational flexibility gives hybrid programs an edge over hybrid automata.
Continuous evolution in the system dynamics is represented using differential equation systems as evolution constraints. For example the (second-order) differential equation z = −b describes deceleration with braking force b and z = v, v = −b & v ≥ 0 expresses that the evolution only applies as long as the speed is v ≥ 0. , to stop braking before v < 0. Such an evolution can stop at any time within v ≥ 0, it could even continue with transient grazing along the border v = 0, but it is never allowed to enter v < 0.