A Prototype for Data Race Detection in CSeq 3

Section: Strengths and Weaknessesmentioning

confidence: 99%

“…1 ultimate.informatik.uni-freiburg.de and github.com/ultimate-pa/ultimate 2 www.gnu.org/licenses/lgpl-3.0.en.html 3 Z3 (github.com/Z3Prover/z3), CVC4 (cvc4.github.io/) and Mathsat (mathsat.fbk.eu) 4 github.com/sosy-lab/benchexec/blob/main/benchexec/tools/ultimatetaipan.py…”

Section: Architecture Setup Configuration and Projectmentioning

confidence: 99%

Ultimate Taipan and Race Detection in Ultimate

Dietsch

Heizmann

Klumpp

et al. 2023

“…CSeqC[73,120] Omar Inverso L'Aquila, Italy Dartagnan C [93, 163] Hernán Ponce de León Munich, Germany (continues on next page)…”

mentioning

confidence: 99%

Software Model Checking: 20 Years and Beyond

Beyer

Podelski

2022

We give an overview of the development of software model checking, a general approach to algorithmic program verification that integrates static analysis, model checking, and deduction. We start with a look backwards and briefly cover some of the important steps in the past decades. The general approach has become a research topic on its own, with a wide range of tools that are based on the approach. Therefore, we discuss the maturity of the research area of software model checking in terms of looking at competitions, at citations, and most importantly, at the tools that were build in this area: we count 76 verification systems for software written in C or Java. We conclude that software model checking has quickly grown to a significant field of research with a high impact on current research directions and tools in software verification.

Progress on Software Verification: SV-COMP 2022

Beyer

2022

The 11th edition of the Competition on Software Verification (SV-COMP 2022) provides the largest ever overview of tools for software verification. The competition is an annual comparative evaluation of fully automatic software verifiers for C and Java programs. The objective is to provide an overview of the state of the art in terms of effectiveness and efficiency of software verification, establish standards, provide a platform for exchange to developers of such tools, educate PhD students on reproducibility approaches and benchmarking, and provide computing resources to developers that do not have access to compute clusters. The competition consisted of 15 648 verification tasks for C programs and 586 verification tasks for Java programs. Each verification task consisted of a program and a property (reachability, memory safety, overflows, termination). The new category on data-race detection was introduced as demonstration category. SV-COMP 2022 had 47 participating verification systems from 33 teams from 11 countries.