University of Oulu

Kuutila, M., Mäntylä, M., Claes, M. et al. Individual differences limit predicting well-being and productivity using software repositories: a longitudinal industrial study. Empir Software Eng 26, 88 (2021).

Individual differences limit predicting well-being and productivity using software repositories : a longitudinal industrial study

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Author: Kuutila, Miikka1; Mäntylä, Mika1; Claes, Mäelick1;
Organizations: 1M3S, ITEE, University of Oulu, Oulu, Finland
2Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
3School of Computing, Queen’s University, Kingston, Ontario, Canada
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 0.6 MB)
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Language: English
Published: Springer Nature, 2021
Publish Date: 2021-09-06


Reports of poor work well-being and fluctuating productivity in software engineering have been reported in both academic and popular sources. Understanding and predicting these issues through repository analysis might help manage software developers’ well-being. Our objective is to link data from software repositories, that is commit activity, communication, expressed sentiments, and job events, with measures of well-being obtained with a daily experience sampling questionnaire. To achieve our objective, we studied a single software project team for eight months in the software industry. Additionally, we performed semi-structured interviews to explain our results. The acquired quantitative data are analyzed with generalized linear mixed-effects models with autocorrelation structure. We find that individual variance accounts for most of the R2 values in models predicting developers’ experienced well-being and productivity. In other words, using software repository variables to predict developers’ well-being or productivity is challenging due to individual differences. Prediction models developed for each developer individually work better, with fixed effects R2 value of up to 0.24. The semi-structured interviews give insights into the well-being of software developers and the benefits of chat interaction. Our study suggests that individualized prediction models are needed for well-being and productivity prediction in software development.

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Series: Empirical software engineering
ISSN: 1382-3256
ISSN-E: 1573-7616
ISSN-L: 1382-3256
Volume: 26
Issue: 5
Article number: 88
DOI: 10.1007/s10664-021-09977-1
Type of Publication: A1 Journal article – refereed
Field of Science: 113 Computer and information sciences
Funding: The first, second and third author have been supported by Academy of Finland grant 298020. The first author has been supported by Kaute-foundation.
Academy of Finland Grant Number: 298020
Detailed Information: 298020 (Academy of Finland Funding decision)
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