Goblint: Thread-Modular Abstract Interpretation Using Side-Effecting Constraints

Saan, Simmo; Schwarz, Michael; Apinis, Kalmer; Erhard, Julian; Seidl, Helmut; Vogler, Ralf; Vojdani, Vesal

doi:10.1007/978-3-030-72013-1_28

Cited by 14 publications

(2 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Here, we detail some recent SV-COMP-related advances in Goblint. The previous competition tool paper [11] provides further details on the general approach.…”

Section: Verification Approachmentioning

confidence: 99%

Goblint: Autotuning Thread-Modular Abstract Interpretation

Saan

Schwarz

Erhard

et al. 2023

Lecture Notes in Computer Science

Self Cite

View full text Add to dashboard Cite

The static analyzer Goblint is dedicated to the analysis of multi-threaded C programs by abstract interpretation. It provides multiple techniques for increasing analysis precision, e.g., configurable context-sensitivity and a wide range of numerical analyses. As a rule of thumb, more precise analyses decrease scalability, while not always necessary for solving the task at hand. Therefore, Goblint has been enhanced with autotuning which, based on syntactical criteria, adapts analysis configuration to the given program such that relevant precision is obtained with acceptable effort.

show abstract

“…Here, we detail some recent SV-COMP-related advances in Goblint. The previous competition tool paper [11] provides further details on the general approach.…”

Section: Verification Approachmentioning

confidence: 99%

Goblint: Autotuning Thread-Modular Abstract Interpretation

Saan

Schwarz

Erhard

et al. 2023

Lecture Notes in Computer Science

Self Cite

View full text Add to dashboard Cite

show abstract

“…We plan to add this classic feature for SV-Comp's next edition. For an over-approximating analyzer, Mopsa is nevertheless quite precise: Mopsa is able to prove around 8% more tasks than Goblint [19,20] (the leading state-of-the-art abstract interpreter running in SV-Comp).…”

Section: Strengths and Weaknessesmentioning

confidence: 99%

Mopsa-C: Modular Domains and Relational Abstract Interpretation for C Programs (Competition Contribution)

Monat

Ouadjaout²,

Miné³

2023

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Mopsa is a multilanguage static analysis platform relying on abstract interpretation. It is able to analyze C, Python, and programs mixing these two languages; we focus on the C analysis here. It provides a novel way to combine abstract domains, in order to offer extensibility and cooperation between them, which is especially beneficial when relational numerical domains are used. The analyses are currently flow-sensitive and fully context-sensitive. We focus only on proving programs to be correct, as our analyses are designed to be sound and terminating but not complete. We present our first participation to SV-Comp, where Mopsa earned a bronze medal in the SoftwareSystems category.

show abstract

Software Verification: 10th Comparative Evaluation (SV-COMP 2021)

Beyer

2021

Tools and Algorithms for the Construction and Analysis of Systems

View full text Add to dashboard Cite

SV-COMP 2021 is the 10th edition of the Competition on Software Verification (SV-COMP), which is an annual comparative evaluation of fully automatic software verifiers for C and Java programs. The competition provides a snapshot of the current state of the art in the area, and has a strong focus on reproducibility of its results. The competition was based on 15 201 verification tasks for C programs and 473 verification tasks for Java programs. Each verification task consisted of a program and a property (reachability, memory safety, overflows, termination). SV-COMP 2021 had 30 participating verification systems from 27 teams from 11 countries.

show abstract

Goblint: Thread-Modular Abstract Interpretation Using Side-Effecting Constraints

Abstract: Goblint is a static analysis framework for C programs specializing in data race analysis. It relies on thread-modular abstract interpretation where thread interferences are accounted for by means of flow-insensitive global invariants.

Cited by 14 publications

References 10 publications

Goblint: Autotuning Thread-Modular Abstract Interpretation

Goblint: Autotuning Thread-Modular Abstract Interpretation

Mopsa-C: Modular Domains and Relational Abstract Interpretation for C Programs (Competition Contribution)

Software Verification: 10th Comparative Evaluation (SV-COMP 2021)

Contact Info

Product

Resources

About