Explainable AI

Current research on explainability and interpretability of machine learning algorithms

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How Do You Feel, Developer? An Explanatory Theory of the Impact of Affects on Programming Performance

Daniel Graziotin, Xiaofeng Wang, Pekka Abrahamsson. PeerJ Computer Science 1:e18 2015

[ArXiv]    

Affects—emotions and moods—have an impact on cognitive activities and the working performance of individuals. Development tasks are undertaken through cognitive processes, yet software engineering research lacks theory on affects and their impact on software development activities. In this paper, we report on an interpretive study aimed at broadening our understanding of the psychology of programming in terms of the experience of affects while programming, and the impact of affects on programming performance. We conducted a qualitative interpretive study based on: face-to-face open-ended interviews, in-field observations, and e-mail exchanges. This enabled us to construct a novel explanatory theory of the impact of affects on development performance. The theory is explicated using an established taxonomy framework. The proposed theory builds upon the concepts of events, affects, attractors, focus, goals, and performance. Theoretical and practical implications are given.