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Understanding the impact of GitHub suggested changes on recommendations between developers

Chris Brown, Chris Parnin

202018 citationsDOIOpen Access PDF

Abstract

Recommendations between colleagues are effective for encouraging developers to adopt better practices. Research shows these peer interactions are useful for improving developer behaviors, or the adoption of activities to help software engineers complete programming tasks. However, in-person recommendations between developers in the workplace are declining. One form of online recommendations between developers are pull requests, which allow users to propose code changes and provide feedback on contributions. GitHub, a popular code hosting platform, recently introduced the suggested changes feature, which allows users to recommend improvements for pull requests. To better understand this feature and its impact on recommendations between developers, we report an empirical study of this system, measuring usage, effectiveness, and perception. Our results show that suggested changes support code review activities and significantly impact the timing and communication between developers on pull requests. This work provides insight into the suggested changes feature and implications for improving future systems for automated developer recommendations, such as providing situated, concise, and actionable feedback.

Topics & Concepts

Computer scienceCode reviewSituatedFeature (linguistics)PerceptionCode (set theory)SoftwareWork (physics)Empirical researchSoftware engineeringSoftware developmentWorld Wide WebStatic program analysisEngineeringProgramming languageLinguisticsNeurosciencePhilosophySet (abstract data type)Artificial intelligenceMechanical engineeringBiologyEpistemologySoftware Engineering ResearchSoftware Engineering Techniques and PracticesOpen Source Software Innovations
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