Bears: An Extensible Java Bug Benchmark for Automatic Program Repair Studies
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Abstract (arXiv)
Benchmarks of bugs are essential to empirically evaluate automatic program repair tools. In this paper, we present Bears, a project for collecting and storing bugs into an extensible bug benchmark for automatic repair studies in Java. The collection of bugs relies on commit building state from Continuous Integration (CI) to find potential pairs of buggy and patched program versions from open-source projects hosted on GitHub. Each pair of program versions passes through a pipeline where an attempt of reproducing a bug and its patch is performed. The core step of the reproduction pipeline is the execution of the test suite of the program on both program versions. If a test failure is found in the buggy program version candidate and no test failure is found in its patched program version candidate, a bug and its patch were successfully reproduced. The uniqueness of Bears is the usage of CI (builds) to identify buggy and patched program version candidates, which has been widely adopted in the last years in open-source projects. This approach allows us to collect bugs from a diversity of projects beyond mature projects that use bug tracking systems. Moreover, Bears was designed to be publicly available and to be easily extensible by the research community through automatic creation of branches with bugs in a given GitHub repository, which can be used for pull requests in the Bears repository. We present in this paper the approach employed by Bears, and we deliver the version 1.0 of Bears, which contains 251 reproducible bugs collected from 72 projects that use the Travis CI and Maven build environment.
Key facts. Cited by 13 papers in the map (data through 14 Oct 2026). First posted on arXiv 17 Jan 2019.
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Citing papers per year: 2021: 1; 2022: 4; 2023: 2; 2024: 3; 2025: 2; 2026: 1.
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- 2021CURE: Code-Aware Neural Machine Translation for Automatic Program Repaircited by 86
- 2023How Effective Are Neural Networks for Fixing Security Vulnerabilitiescited by 52
- 2022Bugs in Machine Learning-based Systems: A Faultload Benchmarkcited by 15
- 2023RunBugRun -- An Executable Dataset for Automated Program Repaircited by 11
- 2024RepairBench: Leaderboard of Frontier Models for Program Repaircited by 9
- 2022Is this Change the Answer to that Problem? Correlating Descriptions of Bug and Code Changes for Evaluating Patch Correctnesscited by 7
- 2024Automated Program Repair: Emerging trends pose and expose problems for benchmarkscited by 7
- 2025BOAD: Discovering Hierarchical Software Engineering Agents via Bandit Optimizationcited by 7
- 2024Towards Reliable Evaluation of Neural Program Repair with Natural Robustness Testingcited by 5
- 2022Leveraging Causal Inference for Explainable Automatic Program Repaircited by 1
- 2025From Empirical Evaluation to Context-Aware Enhancement: Repairing Regression Errors with LLMscited by 1
- 2026Anchored Self-Play for Code Repaircited by 1
1 more
- 2022Infrared: A Meta Bug Detectorcited by 0
- 2026Anchored Self-Play for Code Repair3 Jul 2026
- 2025BOAD: Discovering Hierarchical Software Engineering Agents via Bandit Optimization29 Dec 2025
- 2025From Empirical Evaluation to Context-Aware Enhancement: Repairing Regression Errors with LLMs16 Jun 2025
- 2024RepairBench: Leaderboard of Frontier Models for Program Repair27 Sep 2024
- 2024Automated Program Repair: Emerging trends pose and expose problems for benchmarks8 May 2024
- 2024Towards Reliable Evaluation of Neural Program Repair with Natural Robustness Testing19 Feb 2024
- 2023How Effective Are Neural Networks for Fixing Security Vulnerabilities29 May 2023
- 2023RunBugRun -- An Executable Dataset for Automated Program Repair3 Apr 2023
- 2022Infrared: A Meta Bug Detector18 Sep 2022
- 2022Is this Change the Answer to that Problem? Correlating Descriptions of Bug and Code Changes for Evaluating Patch Correctness8 Aug 2022
- 2022Bugs in Machine Learning-based Systems: A Faultload Benchmark24 Jun 2022
- 2022Leveraging Causal Inference for Explainable Automatic Program Repair26 May 2022
1 more
- 2026Anchored Self-Play for Code Repaircited by 1
- 2026Anchored Self-Play for Code Repair3 Jul 2026
- 2021CURE: Code-Aware Neural Machine Translation for Automatic Program Repaircited by 86
- 2023How Effective Are Neural Networks for Fixing Security Vulnerabilitiescited by 52
- 2022Bugs in Machine Learning-based Systems: A Faultload Benchmarkcited by 15
- 2023RunBugRun -- An Executable Dataset for Automated Program Repaircited by 11
- 2024RepairBench: Leaderboard of Frontier Models for Program Repaircited by 9
- 2022Is this Change the Answer to that Problem? Correlating Descriptions of Bug and Code Changes for Evaluating Patch Correctnesscited by 7
- 2024Automated Program Repair: Emerging trends pose and expose problems for benchmarkscited by 7
- 2024Towards Reliable Evaluation of Neural Program Repair with Natural Robustness Testingcited by 5
- 2022Leveraging Causal Inference for Explainable Automatic Program Repaircited by 1
- 2025From Empirical Evaluation to Context-Aware Enhancement: Repairing Regression Errors with LLMscited by 1
- 2022Infrared: A Meta Bug Detectorcited by 0
- 2025From Empirical Evaluation to Context-Aware Enhancement: Repairing Regression Errors with LLMs16 Jun 2025
- 2024RepairBench: Leaderboard of Frontier Models for Program Repair27 Sep 2024
- 2024Automated Program Repair: Emerging trends pose and expose problems for benchmarks8 May 2024
- 2024Towards Reliable Evaluation of Neural Program Repair with Natural Robustness Testing19 Feb 2024
- 2023How Effective Are Neural Networks for Fixing Security Vulnerabilities29 May 2023
- 2023RunBugRun -- An Executable Dataset for Automated Program Repair3 Apr 2023
- 2022Infrared: A Meta Bug Detector18 Sep 2022
- 2022Is this Change the Answer to that Problem? Correlating Descriptions of Bug and Code Changes for Evaluating Patch Correctness8 Aug 2022
- 2022Bugs in Machine Learning-based Systems: A Faultload Benchmark24 Jun 2022
- 2022Leveraging Causal Inference for Explainable Automatic Program Repair26 May 2022
- 2021CURE: Code-Aware Neural Machine Translation for Automatic Program Repair26 Feb 2021