PredatorHP Revamped (Not Only) for Interval-Sized Memory Regions and Memory Reallocation (Competition Contribution)

Tools and Algorithms for the Construction and Analysis of Systems

2020

This report describes the 2020 Competition on Software Verification (SV-COMP), the 9$$^{\text {th}}$$ edition of a series of comparative evaluations 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 replicability of its results. The competition was based on 11 052 verification tasks for C programs and 416 verification tasks for Java programs. Each verification task consisted of a program and a property (reachability, memory safety, overflows, termination). SV-COMP 2020 had 28 participating verification systems from 11 countries.

Advances in Automatic Software Verification: SV-COMP 2020

Tools and Algorithms for the Construction and Analysis of Systems

2020

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

Tools and Algorithms for the Construction and Analysis of Systems

2021

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.

Construction of Verifier Combinations Based on Off-the-Shelf Verifiers

Lecture Notes in Computer Science

Kanav

Richter

2022

Software verifiers have different strengths and weaknesses, depending on properties of the verification task. It is well-known that combinations of verifiers via portfolio and selection approaches can help to combine the strengths. In this paper, we investigate (a) how to easily compose such combinations from existing, ‘off-the-shelf’ verification tools without changing them and (b) how much performance improvement easy combinations can yield, regarding the effectiveness (number of solved problems) and efficiency (consumed resources). First, we contribute a method to systematically and conveniently construct verifier combinations from existing tools, using the composition framework CoVeriTeam. We consider sequential portfolios, parallel portfolios, and algorithm selections. Second, we perform a large experiment on 8 883 verification tasks to show that combinations can improve the verification results without additional computational resources. All combinations are constructed from off-the-shelf verifiers, that is, we use them as published. The result of our work suggests that users of verification tools can achieve a significant improvement at a negligible cost (only configure our composition scripts).