SV-Benchmarks: Benchmark Set for Software Verification (SV-COMP 2025)
Bibliographic record
Abstract
SV-COMP 2025 Benchmark Set This file is part of an archive for the 14th Competition on Software Verification (SV-COMP 2025). https://sv-comp.sosy-lab.org/2025/ The competition was organized by Dirk Beyer, LMU Munich, Germany and Jan Strejček, Masaryk University, Czechia. More information is available in the following article: Dirk Beyer and Jan Strejček. Improvements in Software Verification and Witness Validation: SV-COMP 2025. In Proceedings of the 31st International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS 2025, Hamilton, Canada, May 3–8), 2024. Springer. doi:10.1007/978-3-031-90660-2_9 Copyright (C) 2025 Dirk Beyer and Jan Strejček https://www.sosy-lab.org/people/beyer/ https://www.fi.muni.cz/~xstrejc/ SPDX-License-Identifier: CC-BY-4.0 https://spdx.org/licenses/CC-BY-4.0 Contents This archive contains a folder with all verification tasks that were used in the competition. Related Archives Overview of archives from SV-COMP 2025 that are available at Zenodo: https://doi.org/10.5281/zenodo.15012077 Verification Witnesses from SV-COMP 2025 Verification Tools. Witness store (containing the generated verification witnesses) https://doi.org/10.5281/zenodo.15055359 Verifiers and Validators: FM-Tools Data Set for SV-COMP 2025. Metadata snapshot of the evaluated tools (DOIs, options, etc.) https://doi.org/10.5281/zenodo.15012085 Results of the 14th Intl. Competition on Software Verification (SV-COMP 2025). Results (XML result files, log files, file mappings, HTML tables) https://doi.org/10.5281/zenodo.15012096 SV-Benchmarks: Benchmark Set of SV-COMP 2025. Verification tasks, version svcomp24 https://doi.org/10.5281/zenodo.15007216 BenchExec, version 3.29. Benchmarking framework https://doi.org/10.5281/zenodo.12345678 FM-Weck, version … Containerized execution and continuous testing of testers All benchmarks were executed for SV-COMP 2025 https://sv-comp.sosy-lab.org/2025/ by Dirk Beyer, LMU Munich, based on the following components: https://gitlab.com/sosy-lab/benchmarking/fm-tools 2.2 https://gitlab.com/sosy-lab/benchmarking/sv-benchmarks svcomp25 https://gitlab.com/sosy-lab/sv-comp/bench-defs svcomp25 https://gitlab.com/sosy-lab/software/benchexec 3.29 https://gitlab.com/sosy-lab/software/benchcloud 1.3.0 https://gitlab.com/sosy-lab/benchmarking/sv-witnesses 2.0.3 https://gitlab.com/sosy-lab/software/coveriteam 1.2.1 https://gitlab.com/sosy-lab/benchmarking/competition-scripts svcomp25 Contact Feel free to contact me in case of questions: https://www.sosy-lab.org/people/beyer/
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.031 | 0.023 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".