Software defect datasets, which are collections of software bugs, are essential resources to facilitate empirical research and enable standardized benchmarking for a wide range of software engineering techniques, including emerging areas like agentic AI-based software development. Over the years, numerous software defect datasets have been developed, providing rich resources for the community, yet making it increasingly difficult to navigate the landscape. This article provides a comprehensive survey of 151 software defect datasets, covering their scope, construction, availability, usability, and practical uses. We also suggest potential opportunities for future research based on our findings, such as addressing underrepresented kinds of defects. A complete catalog of all surveyed software defect datasets is available at https://defect-datasets.github.io/.

翻译：软件缺陷数据集作为软件错误的集合，是推动实证研究、为各类软件工程技术（包括基于智能体的人工智能软件开发等新兴领域）提供标准化基准测试的重要资源。多年来，已开发出大量软件缺陷数据集，为研究社区提供了丰富的资源，但也使得该领域的全景图日益复杂、难以把握。本文对151个软件缺陷数据集进行了全面综述，涵盖其范围、构建方式、可获取性、可用性及实际用途。基于我们的发现，我们还提出了未来研究的潜在机遇，例如解决代表性不足的缺陷类型。所有被调查的软件缺陷数据集的完整目录可在 https://defect-datasets.github.io/ 获取。