一句话：提出自动化多语言缺陷修复数据集构建系统 MBFC，并发布包含 92 万余条细粒度修复对的 M-BF 数据集。
数据驱动的自动缺陷修复方法高度依赖大规模缺陷修复数据集，但现有从代码仓库挖掘的数据集通常只到函数粒度，且缺少故障类型等元信息，难以精确获取缺陷代码片段、修复、位置和类型。针对这一问题，本文提出一个灵活、可扩展且自动化的多语言缺陷修复数据集构建系统 MBFC（Multilingual Bug-Fix Constructor），用于从开源仓库中自动挖掘 bug-fix 对及其元信息。作者进一步使用该系统自动构建并发布大规模细粒度多语言缺陷修复数据集 M-BF，其初始版本包含 921,825 条 bug-fix 对，来自 442,164 个不同开源软件项目，时间范围为 2020 年 1 月至 2020 年 9 月。作者期望该系统与数据集能促进实用程序修复方法的发展，提升程序调试与代码审查效率。
Developing effective data-driven automated bug-fixing approaches is heavily relying on large bug-fix datasets. However, the granularity of current repository-mined bug-fixing datasets is usually at the function level, without meta-information such as the fault type. In order to alleviate the open challenge of precisely mining code snippets with bugs, their fix, location, and types from open source repositories, in this paper, we propose a flexible, extensible, and automated multilingual bug-fix dataset construction system, that is, the Multilingual Bug-Fix Constructor (MBFC). Furthermore, we release a large-scale and fine-grained Multi-lingual Bug-Fix (M-BF) dataset automatically built using the proposed system, which includes a total of 921,825 Bug-Fix pairs that are from 442,164 different open-source software projects starting from January 2020 to September 2020 in the initial version. It is expected that our system and dataset can benefit the development of innovative and practical program repair methods, thereby improving the efficiency of program debugging and code review processes.
@inproceedings{ZhongLZGWGL23,
title = {An Automated and Flexible Multilingual Bug-Fix Dataset Construction System},
author = {Wenkang Zhong and Chuanyi Li and Yunfei Zhang and Ziwen Ge and Jingyu Wang and Jidong Ge and Bin Luo},
booktitle = {ASE},
year = {2023},
doi = {10.1109/ase56229.2023.00176}
}