InferFix: End-to-End Program Repair with LLMs
Open accessAbstract
Software development life cycle is profoundly influenced by bugs; their introduction, identification, and eventual resolution account for a significant portion of software development cost. This has motivated software engineering researchers and practitioners to propose different approaches for automating the identification and repair of software defects.
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Jin et al. (2023) introduces InferFix, a program repair framework that incorporates static analyzers for fixing critical security and performance vulnerabilities.
“Jin et al. (2023) introduces a program repair framework called InferFix that incorporates the latest static analyzers for fixing critical security and performance vulnerabilities.”
From When LLMs meet cybersecurity: a systematic literature review (2025) · cites this paper as Jin et al. (2023)
Cites
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“The few-shot learning paradigm allows model specialization for a downstream task via prompt augmentation, composition, or ensembling [22].”
BackgroundLiu, P., Yuan, W., Fu, J., Jiang, Z., Hayashi, H., & Neubig, G. (2021) · arXiv · doi:10.48550/arxiv.2107.13586 · Cited by 4,352 · cited 1× · see citing works
“The few-shot learning paradigm allows model specialization for a downstream task via prompt augmentation, composition, or ensembling [22].”
BackgroundUnsupervised Feature Learning via Non-parametric Instance Discrimination
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An Empirical Study on Learning Bug-Fixing Patches in the Wild via Neural Machine Translation
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Self-citationShaping program repair space with existing patches and similar code
Jiang, J., Xiong, Y., Zhang, H., Gao, Q., & Chen, X. (2018) · Proceedings of the 27th ACM SIGSOFT International Symposium on Software Testing and Analysis · doi:10.1145/3213846.3213871 · Cited by 329 · see citing works
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“[12] permute ordering of the spans in the original prompt to train the model to infill.”
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A survey on large language model (LLM) security and privacy: The Good, The Bad, and The Ugly
Yao, Y., Duan, J., Xu, K., Cai, Y., Sun, Z., & Zhang, Y. (2024) · High-Confidence Computing · doi:10.1016/j.hcc.2024.100211 · Cited by 1,083 · see citing works
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AutoCodeRover: Autonomous Program Improvement
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“Frameworks for program repair based on static analyzers like InferFix [19] employ LLMs fine-tuned on bug repair patches to solve core repairing tasks for three types of bugs.”
Counterexample Guided Program Repair Using Zero-Shot Learning and MaxSAT-based Fault Localization
Orvalho, P., Janota, M., & Manquinho, V. (2025) · arXiv · doi:10.48550/arxiv.2502.07786 · Cited by 4 · see citing works
FeedbackEval: A Benchmark for Evaluating Large Language Models in Feedback-Driven Code Repair Tasks
Dai, D., Liu, M., Li, A., Cao, J., Wang, Y., Wang, C., Peng, X., & Zheng, Z. (2025) · arXiv · doi:10.48550/arxiv.2504.06939 · Cited by 1 · see citing works
“For example, InferFix [22] combines static analysis with retrieval-augmented LLMs, using historical bug-fix pairs for patch generation.”
- Authors
- Jin, M., Shahriar, S., Tufano, M., Shi, X., Lu, S., Sundaresan, N., & Svyatkovskiy, A.
- Affiliations
- Microsoft (United States) (US)
- University of California, Los Angeles (US)
- Microsoft Research Asia (China) (CN)
- Venue
- Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering
- Publisher
- ACM
- Published
- 2023-11-30
- Pages
- 1646-1656
- OpenAlex
- W4389158474
- Cited by
- 191
- References
- 10
- Citations by year
- 2026: 56 · 2025: 75 · 2024: 53 · 2023: 7
- FWCI
- 36.94
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Computer Science › Software › Software Testing and Debugging Techniques
- Physical Sciences › Computer Science › Information Systems › Software Engineering Research
- Physical Sciences › Computer Science › Information Systems › Software Engineering Techniques and Practices
- Keywords
- program repair, bug fixes, large language models, end-to-end repair, software defects
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