Security Defect Detection via Code Review: A Study of the OpenStack and Qt Communities
Jiaxin Yu, Liming Fu, Peng Liang, Amjed Tahir, Mojtaba Shahin

TL;DR
This study empirically investigates how security defects are identified and addressed through code review in open-source projects, highlighting the complementary role of manual review and automated tools in security defect detection.
Contribution
It provides an empirical analysis of security defect discussions in code reviews, revealing insights into reviewer strategies and developer responses in open-source communities.
Findings
Security defects are infrequently discussed in code reviews.
Over half of reviewers suggest specific fixes for security issues.
Developers tend to follow reviewers' security suggestions.
Abstract
Background: Despite the widespread use of automated security defect detection tools, software projects still contain many security defects that could result in serious damage. Such tools are largely context-insensitive and may not cover all possible scenarios in testing potential issues, which makes them susceptible to missing complex security defects. Hence, thorough detection entails a synergistic cooperation between these tools and human-intensive detection techniques, including code review. Code review is widely recognized as a crucial and effective practice for identifying security defects. Aim: This work aims to empirically investigate security defect detection through code review. Method: To this end, we conducted an empirical study by analyzing code review comments derived from four projects in the OpenStack and Qt communities. Through manually checking 20,995 review comments…
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Taxonomy
TopicsSoftware Engineering Research · Advanced Malware Detection Techniques · Web Application Security Vulnerabilities
