分析七个项目中异常滞留的漏洞，找出长期未解决的共性主题。
When Bugs Linger: A Study of Anomalous Resolution Time Outliers and Their Themes
- 用统计方法识别超长修复时间的异常漏洞
- 发现异常漏洞多集中于测试失败、功能增强和界面问题
- 为维护者提供优先处理长期漏洞的实用参考
高效修复漏洞对保障软件质量与用户满意度至关重要。然而，部分漏洞报告的修复时间异常漫长，可能反映流程效率低下或问题本身复杂。本研究对Cassandra、Firefox、Hadoop、HBase、SeaMonkey、Spark和Thunderbird七个主流开源项目进行了全面分析。采用Z-score和四分位距（IQR）等统计方法识别修复时长异常的漏洞，并通过词频-逆文档频率（TF-IDF）提取文本特征，结合KMeans聚类分析漏洞摘要的主题分布。结果表明，各项目中异常漏洞存在一致模式，主要集中于测试失败、增强请求与用户界面问题。该方法为项目维护者识别并有效处理长期积压漏洞提供了可操作的洞察。
原文摘要 · Abstract (English)
Efficient bug resolution is critical for maintaining software quality and user satisfaction. However, specific bug reports experience unusually long resolution times, which may indicate underlying process inefficiencies or complex issues. This study presents a comprehensive analysis of bug resolution anomalies across seven prominent open-source repositories: Cassandra, Firefox, Hadoop, HBase, SeaMonkey, Spark, and Thunderbird. Utilizing statistical methods such as Z-score and Interquartile Range (IQR), we identify anomalies in bug resolution durations. To understand the thematic nature of these anomalies, we apply Term Frequency-Inverse Document Frequency (TF-IDF) for textual feature extraction and KMeans clustering to group similar bug summaries. Our findings reveal consistent patterns across projects, with anomalies often clustering around test failures, enhancement requests, and user interface issues. This approach provides actionable insights for project maintainers to prioritize and effectively address long-standing bugs.
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