SWE-bench-java: A GitHub Issue Resolving Benchmark for Java

Daoguang Zan, Zhirong Huang, Ailun Yu, Shaoxin Lin, Yifan Shi +15 more
8/26/2024
cs.SEcs.AIcs.CL

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Abstract

GitHub issue resolving is a critical task in software engineering, recently gaining significant attention in both industry and academia. Within this task, SWE-bench has been released to evaluate issue resolving capabilities of large language models (LLMs), but has so far only focused on Python version. However, supporting more programming languages is also important, as there is a strong demand in industry. As a first step toward multilingual support, we have developed a Java version of SWE-bench, called SWE-bench-java. We have publicly released the dataset, along with the corresponding Docker-based evaluation environment and leaderboard, which will be continuously maintained and updated in the coming months. To verify the reliability of SWE-bench-java, we implement a classic method SWE-agent and test several powerful LLMs on it. As is well known, developing a high-quality multi-lingual benchmark is time-consuming and labor-intensive, so we welcome contributions through pull requests or collaboration to accelerate its iteration and refinement, paving the way for fully automated programming.

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@article{zan2024swebenchjava,
  title  = {SWE-bench-java: A GitHub Issue Resolving Benchmark for Java},
  author = {Daoguang Zan and Zhirong Huang and Ailun Yu and Shaoxin Lin and Yifan Shi and Wei Liu and Dong Chen and Zongshuai Qi and Hao Yu and Lei Yu and Dezhi Ran and Muhan Zeng and Bo Shen and Pan Bian and Guangtai Liang and Bei Guan and Pengjie Huang and Tao Xie and Yongji Wang and Qianxiang Wang},
  year   = {2024},
  eprint = {2408.14354},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2408.14354v1}
}

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