Between JIRA and GitHub: ASFBot and its influence on human comments in issue trackers

A Moharil, D Orlov, S Jameel, T Trouwen… - Proceedings of the 19th …, 2022 - dl.acm.org
A Moharil, D Orlov, S Jameel, T Trouwen, N Cassee, A Serebrenik
Proceedings of the 19th International Conference on Mining Software Repositories, 2022dl.acm.org
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 …
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.
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