Paper Info
Title
Between JIRA and GitHub: ASFBot and its Influence on Human Comments in Issue Trackers
Abstract
Open-Source Software (OSS) projects have adopted various automations for repetitive tasks in recent years. One common type of automation in OSS is bots. In this exploratory case study, we seek to understand how the adoption of one particular bot (ASFBot) by the Apache Software Foundation (ASF) impacts the discussions in the issue-trackers of these projects. We use the SmartShark dataset to investigate whether the ASFBot affects (i) human comments mentioning pull requests and fixes in issue comments and (ii) the general human comment rate on issues. We apply a regression discontinuity design (RDD) on nine ASF projects that have been active both before and after the ASFBot adoption. Our results indicate (i) an immediate decrease in the number of median comments mentioning pull requests and fixes after the bot adoption, but the trend of a monthly decrease in this comment count is reversed, and (ii) no effect in the number of human comments after the bot adoption. We make an effort to gather first insights in understanding the impact of adopting the ASFBot on the commenting behavior of developers who are working on ASF projects.
Year
DOI
Venue
2022
10.1145/3524842.3528528
2022 IEEE/ACM 19th International Conference on Mining Software Repositories (MSR)
Keywords
DocType
ISSN
bots,ASFBot,issue-trackers,Apache
Conference
2574-3848
ISBN
Citations 
PageRank 
978-1-6654-5210-6
0
0.34
References 
Authors
15
6
Name
Order
Citations
PageRank
Ambarish Moharil100.68
Dmitrii Orlov200.34
Samar Jameel300.34
Tristan Trouwen400.34
Nathan Cassee5112.22
Alexander Serebrenik61745150.69