Understanding Large Language Model Performance in Software Engineering: A Large-scale Question Answering Benchmark
In this work, we introduce CodeRepoQA, a large-scale benchmark specifically designed for evaluating repository-level question-answering capabilities in the field of software engineering. CodeRepoQA encompasses five programming languages and covers a wide range of scenarios, enabling comprehensive evaluation of language models.To construct this dataset, we crawl data from 30 well-known repositories in GitHub, the largest platform for hosting and collaborating on code, and carefully filter the raw data.In total, CodeRepoQA is a multi-turn question-answering benchmark with 585,687 entries. It covers a diverse array of software engineering scenarios, with an average of 6.62 dialogue turns per entry.
Authors
- Xiangxin Meng (ORCID: https://orcid.org/0000-0001-5630-4810)
- Cuiyun Gao (ORCID: https://orcid.org/0000-0003-4774-2434)
- Ruida Hu (ORCID: https://orcid.org/0009-0000-9221-2788)
- Qinyun Wu
- Ren Jingyi (ORCID: https://orcid.org/0009-0002-3933-5089)
- Bo Jiang (ORCID: https://orcid.org/0009-0000-1080-3278)
- Pengfei Gao (ORCID: https://orcid.org/0000-0003-3800-2565)
- Chao Peng (ORCID: https://orcid.org/0000-0003-2843-0689)
- Xinchen Wang
Institutions
- Shenzhen Institute of Information Technology (CN)
- Harbin Institute of Technology (CN)
Publication Details
- Published
- 2025-07-13
- DOI
- https://doi.org/10.1145/3726302.3730262
- Primary Topic
- Software Engineering Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Guangdong Province