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Despite the number of automatic fault localization tools available for different languages, finding the code responsible for a software failure is still performed manually. This paper presents GZoltarAction, an automated fault localization bot designed for GitHub repositories to assist developers in identifying software faults within a Continuous Integration (CI) environment. Leveraging Spectrum-based Fault Localization (SBFL) via the GZoltar tool, GZoltarAction embeds tailored fault localization reports directly into pull requests or commits, enhancing developers� ability to debug efficiently. Our solution, available on the GitHub Marketplace, offers a practical and accessible tool for the open-source community, hopefully helping streamline automatic fault localization and reducing manual fault-finding efforts.

Sun 27 Apr

Displayed time zone: Eastern Time (US & Canada) change

11:00 - 12:30
Session 1: Bots in Open Source and Development PracticesBotSE at 213
Chair(s): Ahmad Abdellatif University of Calgary

Ahmad Abdellatif

11:00
18m
Talk
A Bot Identification Model and Tool Based on GitHub Activity Sequences
BotSE
Natarajan Chidambaram University of Mons, Alexandre Decan University of Mons; F.R.S.-FNRS, Tom Mens University of Mons
11:18
18m
Talk
The Secret Life of Bots in Pull Requests: An Empirical Study based on Apache Projects
BotSE
Chenhao Wei Stevens Institute of Technology, Lu Xiao Stevens Institute of Technology, Yutong Zhao University of Central Missouri, Ting Liao Stevens Institute of Technology
11:36
18m
Talk
Observing bots in the wild: A quantitative analysis of a large open source ecosystem
BotSE
Natarajan Chidambaram University of Mons, Tom Mens University of Mons
11:54
18m
Talk
GZoltarAction: A Fault Localization Bot for GitHub Repositories
BotSE
Hugo Paiva Faculty of Engineering of the University of Porto, Portugal, José Campos Faculty of Engineering of the University of Porto, Portugal, Rui Abreu Faculty of Engineering of the University of Porto, Portugal
12:12
18m
Talk
Opportunities and Challenges of Software Engineering Bots: A Forward-Looking Analysis
BotSE
Glaucia Melo Toronto Metropolitan University
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