一句话：提出 ASTOR 自动化识别触发安全关切的代码审查，以便安全专家进一步审查。
在代码审查过程中，开发者若发现安全问题通常会提出安全关切；若这些关切被忽略，可能对软件产品质量造成严重影响。为降低该风险，需要自动识别那些触发安全关切的代码审查，从而安排安全专家进行额外审查。本文的研究目标是开发名为 ASTOR 的自动化工具来完成这一识别任务。摘要未具体说明所采用的技术路线、实验设计与评估结果，因此其核心贡献在于提出面向安全代码审查自动识别的问题设定与工具目标。
During code reviews, software developers often raise security concerns if they find any. Ignoring such concerns can bring a severe impact on the performance of a software product. This risk can be reduced if we can automatically identify such code reviews that trigger security concerns so that we can perform additional scrutiny from the security experts. Therefore, the objective of this study is to develop an automated tool to identify code reviews that trigger security concerns.
DOI 原文 ·
@inproceedings{paperbot7361,
title = {ASTOR: An Approach to Identify Security Code Reviews},
author = {Rajshakhar Paul},
booktitle = {ASE},
year = {2022},
doi = {10.1145/3551349.3559509}
}