一句话：提出利用 GUI 交互数据弥合缺陷报告与源代码之间的语义鸿沟，以提升基于文本检索的缺陷定位效果。
论文关注缺陷报告管理中的缺陷定位任务。已有工作常将其建模为信息检索问题，按缺陷报告与源代码文件（标识符或自然语言）的文本相似度检索并排序可能包含缺陷的文件。然而，缺陷报告中的信息与源代码文本之间常存在明显语义鸿沟，影响定位效果。作者指出，对于面向用户的软件，图形用户界面（GUI）交互信息可能为缺陷定位提供重要线索，但此前尚未得到充分研究。该摘要主要阐述研究动机与切入点，未展开具体技术方案、实验设置及结果；其核心主张是引入 GUI 交互数据以补充文本检索信号，从而改进基于文本检索的缺陷定位。
One of the most important tasks related to managing bug reports is localizing the fault so that a fix can be applied. As such, prior work has aimed to automate this task of bug localization by formulating it as an information retrieval problem, where potentially buggy files are retrieved and ranked according to their textual similarity with a given bug report. However, there is often a notable semantic gap between the information contained in bug reports and identifiers or natural language contained within source code files. For user-facing software, there is currently a key source of information that could aid in bug localization, but has not been thoroughly investigated - information from the graphical user interface (GUI).
@inproceedings{paperbot11455,
title = {On Using GUI Interaction Data to Improve Text Retrieval-based Bug Localization},
author = {Junayed Mahmud and Nadeeshan De Silva and Safwat Ali Khan and Seyed Hooman Mostafavi and S M Hasan Mansur and Oscar Chaparro and Andrian (Andi) Marcus and Kevin Moran},
booktitle = {ICSE},
year = {2024},
doi = {10.1145/3597503.3608139}
}