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.

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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

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article

Understanding Large Language Model Performance in Software Engineering: A Large-scale Question Answering Benchmark

Xiangxin Meng, Cuiyun Gao, Ruida Hu, Qinyun Wu et al.
Software Engineering Research
article

Understanding Large Language Model Performance in Software Engineering: A Large-scale Question Answering Benchmark

Xiangxin Meng, Cuiyun Gao, Ruida Hu, Qinyun Wu, Ren Jingyi, Bo Jiang, Pengfei Gao, Chao Peng, Xinchen Wang
article en

Abstract

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.

Shenzhen Institute of Information Technology (CN), Harbin Institute of Technology (CN)
National Natural Science Foundation of China, Natural Science Foundation of Guangdong Province
Openalex Percentile: Top 75%
Software Engineering Research
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