Affect Recognition in Code Review: An In-situ Biometric Study of Reviewer's Affect
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CitationVrzakova, Hana. Begel, Andrew. Mehtätalo, Lauri. Bednarik, Roman. (2020). Affect Recognition in Code Review: An In-situ Biometric Study of Reviewer's Affect. Journal of systems and software, 159, 110434. 10.1016/j.jss.2019.110434.
Code review in software development is an important practice that increases team productivity and improves product quality. Code review is also an example of remote, computer-mediated asynchronous communication prone to the loss of affective information. Since positive affect has been linked to productivity in software development, prior research has focused on sentiment analysis in source codes. Although the methods of sentiment analysis have advanced, there are remaining challenges due to numerous domain oriented expressions, subtle nuances, and indications of sentiment. Here we explore the potentials of (1) nonverbal behavioral signals such as conventional typing, and (2) indirect physiology (eye gaze, GSR, touch pressure) that reflect genuine affective states in the in-situ code review in a large software company. Nonverbal behavioral signals of 33 professional software developers were unobtrusively recorded while they worked on their daily code review. Using Linear Mixed Effect Models, we observed that affect presented in the written comments was associated with prolonged typing duration. Using physiological features, a trained Random Forest classifier could predict post-task valence with 90.0% accuracy (F1-score = 0.937) and arousal with 83.9% accuracy (F1-score = 0.856). The results presents potentials for intelligent affect-aware interfaces for code review in-situ.