mlsanityData to 7 Oct 2026

BugsInPy: A Database of Existing Bugs in Python Programs to Enable Controlled Testing and Debugging Studies

arXiv 2401.15481 ↗First posted 27 Jan 2024cs.SEcited by 35

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Abstract (arXiv)

The 2019 edition of Stack Overflow developer survey highlights that, for the first time, Python outperformed Java in terms of popularity. The gap between Python and Java further widened in the 2020 edition of the survey. Unfortunately, despite the rapid increase in Python's popularity, there are not many testing and debugging tools that are designed for Python. This is in stark contrast with the abundance of testing and debugging tools for Java. Thus, there is a need to push research on tools that can help Python developers. One factor that contributed to the rapid growth of Java testing and debugging tools is the availability of benchmarks. A popular benchmark is the Defects4J benchmark; its initial version contained 357 real bugs from 5 real-world Java programs. Each bug comes with a test suite that can expose the bug. Defects4J has been used by hundreds of testing and debugging studies and has helped to push the frontier of research in these directions. In this project, inspired by Defects4J, we create another benchmark database and tool that contain 493 real bugs from 17 real-world Python programs. We hope our benchmark can help catalyze future work on testing and debugging tools that work on Python programs.

Key facts. Cited by 35 papers in the map (data through 7 Oct 2026). First posted on arXiv 27 Jan 2024.

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Citing papers per year: 2024: 9; 2025: 12; 2026: 14.

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  1. 2024Large Language Model-Based Agents for Software Engineering: A Surveycited by 173
  2. 2024Code-Aware Prompting: A study of Coverage Guided Test Generation in Regression Setting using LLMcited by 63
  3. 2024HyperAgent: Generalist Software Engineering Agents to Solve Coding Tasks at Scalecited by 61
  4. 2024You Name It, I Run It: An LLM Agent to Execute Tests of Arbitrary Projectscited by 45
  5. 2024CoverUp: Effective High Coverage Test Generation for Pythoncited by 36
  6. 2025LessLeak-Bench: A First Investigation of Data Leakage in LLMs Across 83 Software Engineering Benchmarkscited by 34
  7. 2025SWE-Synth: Synthesizing Verifiable Bug-Fix Data to Enable Large Language Models in Resolving Real-World Bugscited by 22
  8. 2024Are Large Language Models Memorizing Bug Benchmarks?cited by 11
  9. 2025Corrective Diffusion Language Modelscited by 11
  10. 2026SERA: Soft-Verified Efficient Repository Agentscited by 10
  11. 2024Measuring the Influence of Incorrect Code on Test Generationcited by 9
  12. 2025A Comprehensive Empirical Evaluation of Agent Frameworks on Code-centric Software Engineering Taskscited by 7
23 more
  1. 2024Towards Reliable Evaluation of Neural Program Repair with Natural Robustness Testingcited by 5
  2. 2025Assessing the Impact of Code Changes on the Fault Localizability of Large Language Modelscited by 4
  3. 2025Improving LLM Reasoning for Vulnerability Detection via Group Relative Policy Optimizationcited by 4
  4. 2025When Names Disappear: Revealing What LLMs Actually Understand About Codecited by 4
  5. 2024Order Matters! An Empirical Study on Large Language Models' Input Order Bias in Software Fault Localizationcited by 3
  6. 2025Benchmarking AI Models in Software Engineering: A Review, Search Tool, and Unified Approach for Elevating Benchmark Qualitycited by 3
  7. 2026OmniCode: A Benchmark for Evaluating Software Engineering Agentscited by 3
  8. 2025Fault Localization via Fine-tuning Large Language Models with Mutation Generated Stack Tracescited by 1
  9. 2025PyResBugs: A Dataset of Residual Python Bugs for Natural Language-Driven Fault Injectioncited by 1
  10. 2025From Empirical Evaluation to Context-Aware Enhancement: Repairing Regression Errors with LLMscited by 1
  11. 2026Anchored Self-Play for Code Repaircited by 1
  12. 2025SLICEMATE: Accurate and Scalable Static Program Slicing via LLM-Powered Agentscited by 0
  13. 2026Tricky2: Towards a Benchmark for Evaluating Human and LLM Error Interactionscited by 0
  14. 2026SemLoc: Structured Grounding of Free-Form LLM Reasoning for Fault Localizationcited by 0
  15. 2026An Empirical Evaluation of Locally Deployed LLMs for Bug Detection in Python Codecited by 0
  16. 2026PBT-Bench: Benchmarking AI Agents on Property-Based Testingcited by 0
  17. 2026All Green, Still Broken: Real-Flow Verification Lessons from an LLM-Integrated, Multi-Market Web Applicationcited by 0
  18. 2026Diff-Based Code Corruption using LLMs for Large-Scale Bugfix Benchmarkingcited by 0
  19. 2026Do Coverage and Mutation Scores of LLM-Generated Test Suites Correlate with Their Effectiveness? (Replicability Study)cited by 0
  20. 2026Large Language Models at the Intersection of Software Engineering and Software Security:An Evidence-Centered Structured Survey and Research Agendacited by 0
  21. 2026CROCODIL: Cross-Model Code Editing with LLMscited by 0
  22. 2026SWE-Gate: Passing Functional Tests Is Not Enough for Software Engineering Agentscited by 0
  23. 2026COUNTERMEM: World-Model Verified Counter-Factual Memory for Language Agentscited by 0