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SV-COMP 2022 Verification Witnesses This file describes the contents of an archive of the 11th Competition on Software Verification (SV-COMP 2022). https://sv-comp.sosy-lab.org/2022/ The competition was run by Dirk Beyer, LMU Munich, Germany. More information is available in the following article: Dirk Beyer. Progress on Software Verification: SV-COMP 2022. In Proceedings of the 28th International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS 2022, Munich, April 2 - 7), 2022. Springer. Copyright (C) Dirk Beyer https://www.sosy-lab.org/people/beyer/ SPDX-License-Identifier: CC-BY-4.0 https://spdx.org/licenses/CC-BY-4.0.html Contents LICENSE.txt: specifies the license README.txt: this file witnessFileByHash/: This directory contains verification witnesses. Each verification witness in this directory is stored in a file whose name is the SHA2 256-bit hash of its contents followed by the filename extension .graphml. The format of each verification witness is described on the format web page: https://github.com/sosy-lab/sv-witnesses/ A verification witness contains also metadata in order to relate it to the verification task for which it was produced. witnessInfoByHash/: This directory contains for each verification witness in directory witnessFileByHash/ a record in JSON format (also using the SHA2 256-bit hash of the witness as filename, with .json as filename extension) that contains the meta data. witnessListByProgramHashJSON/: For convenient access to all verification witnesses for a certain program, this directory represents a function that maps each program (via its SHA2256-bit hash) to a set of verification witnesses (JSON records for verification witnesses as described above) that the verification tools have produced for that program. For each program for which verification witnesses exist, the directory contains a JSON file (using the SHA2 256-bit hash of the program as filename, with .json as filename extension) that contains all JSON records for verification witnesses for that program. The data structure is described in the following article: Dirk Beyer. A Data Set of Program Invariants and Error Paths. In Proceedings of the 2019 IEEE/ACM 16th International Conference on Mining Software Repositories (MSR 2019, Montreal, Canada, May 26-27), pages 111-115, 2019. IEEE. https://doi.org/10.1109/MSR.2019.00026 Other Archives Overview over archives from SV-COMP 2022 that are available at Zenodo: https://doi.org/10.5281/zenodo.5838498 Verification Witnesses from SV-COMP 2022 Verification Tools. Witness store (containing the generated verification witnesses) https://doi.org/10.5281/zenodo.5831008 Results of the 11th Intl. Competition on Software Verification (SV-COMP 2022). Results (XML result files, log files, file mappings, HTML tables) https://doi.org/10.5281/zenodo.5831003 SV-Benchmarks: Benchmark Set of SV-COMP 2022 and Test-Comp 2022. Verification tasks, version svcomp22 https://doi.org/10.5281/zenodo.5720267 BenchExec, version 3.10. Benchmarking framework All benchmarks were executed for SV-COMP 2022 https://sv-comp.sosy-lab.org/2022/ by Dirk Beyer, LMU Munich, based on the following components: https://gitlab.com/sosy-lab/sv-comp/archives-2022 svcomp22 a6b18082 https://gitlab.com/sosy-lab/benchmarking/sv-benchmarks svcomp22 ad265d07 https://gitlab.com/sosy-lab/sv-comp/bench-defs svcomp22 0332884a https://gitlab.com/sosy-lab/software/benchexec 3.10 4e8716bd https://gitlab.com/sosy-lab/benchmarking/competition-scripts svcomp22 3c959671 https://github.com/sosy-lab/sv-witnesses svcomp22 e4695d2b Contact Feel free to contact me in case of questions: https://www.sosy-lab.org/people/beyer/
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 3 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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