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28th August 2014. My poster at SEAA 2014 (http://esd.scienze.univr.it/dsd-seaa-2014) about our idea on an approach for investigating the correlation between software developers’ performance and mood via software repository mining. It is well-known that moods and emotions strongly affect our performances. Clearly, this holds also for software developers. Thus, modern managers, trainers, and coaches should be aware of moods and emotions of software developers in their teams. In this context, mining software repositories and social networks in combination can be an invaluable instrument for understanding how the moods and emotions of software developers impact their performance, even in real-time. In this paper, we propose our first steps in mining software repositories for (i) getting information about developers’ moods and emotion throughout the development process, and (ii) investigating on the existence of the correlation between software developers’ performance (in terms of their commits bugginess) and mood. For what concerns data sources, we use publicly-available information on GitHub for getting insights about the performance of software developers, while we semantically analyse developers’ posts on Twitter for extracting their moods during the whole duration of the project.
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How do you feel today? Buggy!
Copyright © Gran Sasso Science Institute & DISIM Department (UDA)
Giampiero Di Paolo1, Ivano Malavolta2, Henry Muccini11DISIM Department, University of L’Aquila, Italy2Gran Sasso Science Institute, L’Aquila, Italy
Discretize project duration time w.r.t. developers’ activities
Estimate developers’ perfor-mance score for every time slot
Estimate developers’ mood for every time slot
Combine performance and mood scores
Visualize results in an accessi-ble and intuitive dashboard
tweets activities
semantic and quantitative analysis
Project overview
Collaborators’ trends
