构建了用于自然语言驱动故障注入的残余Python缺陷数据集
PyResBugs: A Dataset of Residual Python Bugs for Natural Language-Driven Fault Injection
- 收集主流Python框架中的未检测缺陷，配以修复版本和多级自然语言描述
- 支持用自然语言生成真实世界故障，提升测试场景的现实代表性
- 适合研究AI自动化测试、软件故障注入与自然语言编程的学者
本文提出PyResBugs，一个精心整理的残余缺陷数据集，即在传统测试中未被发现但在生产环境中暴露的缺陷，数据来自主要Python框架。每个缺陷均配有对应的无错（修复）版本，并附有多层次自然语言（NL）描述。这些描述支持自然语言驱动的故障注入，为模拟软件系统中的真实故障提供了新方法。通过弥合软件故障注入技术与实际表现之间的差距，PyResBugs为研究人员提供了一个高质量资源，有助于推动Python系统中基于AI的自动化测试发展。
原文摘要 · Abstract (English)
This paper presents PyResBugs, a curated dataset of residual bugs, i.e., defects that persist undetected during traditional testing but later surface in production, collected from major Python frameworks. Each bug in the dataset is paired with its corresponding fault-free (fixed) version and annotated with multi-level natural language (NL) descriptions. These NL descriptions enable natural language-driven fault injection, offering a novel approach to simulating real-world faults in software systems. By bridging the gap between software fault injection techniques and real-world representativeness, PyResBugs provides researchers with a high-quality resource for advancing AI-driven automated testing in Python systems.
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