Artifacts of the ADS Bug-Fix Pattern Study

This is the first bug-fix pattern study in the ADS domain. Our proposed hierarchical classification of ADS bug-fix pattern study includes 15 syntactic and 27 semantic bug-fix patterns, as well as root causes, symptoms, modules, sub-modules, related algorithms, and detailed bug-fix actions. This taxonomy is instrumental for developers, testers, and researchers in developing automated bug detection and repair tools for ADS. data/bfp_label contains the labeled data of pull requests from Apollo and Autoware GitHub repositories in two formats. data/bug-fix file-change dataset contains the bug-fix code changes of pull requests. figs contains the output figures generated by data analysis and data visualization.本研究是自动驾驶系统（ADS）领域内首项针对缺陷修复模式的研究。我们提出的ADS缺陷修复模式层级分类体系涵盖15种句法层面缺陷修复模式与27种语义层面缺陷修复模式，同时包含缺陷根本成因、故障症状、功能模块、子模块、相关算法以及具体缺陷修复操作步骤。该分类体系可助力开发者、测试人员与研究人员开发面向ADS的自动化缺陷检测与修复工具。 data/bfp_label 包含来自Apollo与Autoware的GitHub代码仓库的拉取请求标注数据，共两种格式。 data/bug-fix file-change dataset 包含拉取请求对应的缺陷修复代码变更内容。 figs 文件夹包含通过数据分析与数据可视化生成的输出图表。