论文标题
开发人员问答网站上的安全漏洞支持的大规模研究
A Large-scale Study of Security Vulnerability Support on Developer Q&A Websites
论文作者
论文摘要
上下文:安全漏洞(SVS)对软件系统构成许多严重威胁。开发人员通常寻求解决这些SV在开发人员的问答(问答)网站上解决这些SV的解决方案。但是,关于有关不同开发人员问答站点进行的持续的SV特定讨论仍然鲜为人知。目的:我们提出了一项大规模的经验研究,以了解开发人员的SV讨论以及Q&A站点如何支持这些讨论。方法:我们首先策划了来自两个大Q&A站点的71,329 SV帖子,即堆叠溢出(SO)和安全性STACKEXCHANGE(SSE)。然后,我们使用主题建模来揭示与SV相关的讨论的主题,并分析每个主题的普及,难度和专业水平。我们还进行定性分析,以确定与SV相关问题的解决方案的类型。结果:我们确定了有关问答站点的13个主要SV讨论主题。许多主题不遵循基于专家的安全资源(例如共同弱点(CWE)和Open Web应用程序安全项目(OWASP))的分布和趋势。我们还发现,SV讨论比许多其他领域都吸引更多的专家回答,但是一些困难的SV主题(例如,脆弱性扫描工具)仍然得到专家的支持。此外,我们确定了在问答网站上给出SV问题的七种关键类型,其中经常提供代码和说明,而SSE通常提供基于经验的建议和解释。结论:我们的发现为研究人员和从业人员提供了支持,以有效地获取,分享和利用问答环节的SV知识。
Context: Security Vulnerabilities (SVs) pose many serious threats to software systems. Developers usually seek solutions to addressing these SVs on developer Question and Answer (Q&A) websites. However, there is still little known about on-going SV-specific discussions on different developer Q&A sites. Objective: We present a large-scale empirical study to understand developers' SV discussions and how these discussions are being supported by Q&A sites. Method: We first curate 71,329 SV posts from two large Q&A sites, namely Stack Overflow (SO) and Security StackExchange (SSE). We then use topic modeling to uncover the topics of SV-related discussions and analyze the popularity, difficulty, and level of expertise for each topic. We also perform a qualitative analysis to identify the types of solutions to SV-related questions. Results: We identify 13 main SV discussion topics on Q&A sites. Many topics do not follow the distributions and trends in expert-based security sources such as Common Weakness Enumeration (CWE) and Open Web Application Security Project (OWASP). We also discover that SV discussions attract more experts to answer than many other domains, but some difficult SV topics (e.g., Vulnerability Scanning Tools) still receive quite limited support from experts. Moreover, we identify seven key types of answers given to SV questions on Q&A sites, in which SO often provides code and instructions, while SSE usually gives experience-based advice and explanations. Conclusion: Our findings provide support for researchers and practitioners to effectively acquire, share and leverage SV knowledge on Q&A sites.