A Case Study of Developer Bots: Motivations, Perceptions, and Challenges
Names and KTH ID
Diogo Gaspar (dgaspar@kth.se)
Tomás Esteves (tmbpe@kth.se)
Deadline
Week 7
Category
Scientific Paper
Description
The paper examines 23 developer bots used in Microsoft's CI/CD workflows, aiding thousands of developers across 13,000 repositories. These bots, categorized into configuration, security, data privacy, productivity, and code quality, help automate tasks and provide early feedback to developer actions; through interviews, surveys, as well as the analysis of hundreds of thousands of bot actions, the authors' study explores the motivations, benefits and challenges of using these bots, such as managing excessive feedback (noise), among others.
Relevance
The study in hand is highly relevant to DevOps, examining how developer bots automate tasks in CI/CD pipelines to improve code quality, productivity, among other key goals of the area. Besides delineating how these bots streamline workflows and support the "shift left" approach, the paper also highlights core challenges: managing multiple bots, and prioritizing feedback, critical for maintaining efficiency in large-scale environments.
Assignment Proposal
Title
A Case Study of Developer Bots: Motivations, Perceptions, and Challenges
Names and KTH ID
Deadline
Category
Description
The paper examines 23 developer bots used in Microsoft's CI/CD workflows, aiding thousands of developers across 13,000 repositories. These bots, categorized into configuration, security, data privacy, productivity, and code quality, help automate tasks and provide early feedback to developer actions; through interviews, surveys, as well as the analysis of hundreds of thousands of bot actions, the authors' study explores the motivations, benefits and challenges of using these bots, such as managing excessive feedback (noise), among others.
Relevance
The study in hand is highly relevant to DevOps, examining how developer bots automate tasks in CI/CD pipelines to improve code quality, productivity, among other key goals of the area. Besides delineating how these bots streamline workflows and support the "shift left" approach, the paper also highlights core challenges: managing multiple bots, and prioritizing feedback, critical for maintaining efficiency in large-scale environments.