一句话：通过分析静态分析器评论引发的开发者对话情感与意图，衡量其在代码审查中的有用性。
静态代码分析器已普遍集成到代码审查流程中，其评论方式类似人类审查者：对代码变更发表意见并建议改进。分析器评论往往会引发开发者之间的讨论，以确认问题是否存在以及如何修复。然而，开发者很少直接向工具提供反馈，因此难以直接判断分析器是否有用。本文提出从分析器评论所触发的对话入手，理解其中的情感和意图，以此理解开发者与分析器的交互，并将这些信号作为衡量静态分析器有用性的手段。摘要未报告具体的评估结果，其贡献在于为分析器实用性评估提供了一种基于对话的观察视角。
Static code analyzers are now a common part of the codereview process. These automated tools integrate into the code review process by commenting on code changes and suggesting improvements, in the same way as human reviewers. The comments made by static analyzers often trigger a conversation between developers to align on if and how the issue should be fixed. Because developers rarely give feedback directly to the tool, understanding the sentiment and intent in the conversation triggered by the tool comments can be used to measure the usefulness of the static analyzer.
@inproceedings{paperbot8272,
title = {Understanding Developer-Analyzer Interactions in Code Reviews},
author = {Martin Schaef and Berk Cirisci and Linghui Luo and Muhammad Numair Mansur and Omer Tripp and Daniel Sanchez and Qiang Zhou and Muhammad Bilal Zafar},
booktitle = {ASE},
year = {2024},
doi = {10.1145/3691620.3695257}
}