Motivation is an important factor in software development. However, it is a subjective concept that is hard to quantify and study empirically. In order to use the wealth of data available about real software development projects in GitHub, we represent the motivation of developers using labeling functions. These are validated heuristics that need only be better than a guess, computable on a dataset. We define four labeling functions for motivation based on behavioral cues like working in diverse hours of the day. We validated the functions by agreement with respect to a developers survey, per person behavior, and temporal changes. We then apply them to 150 thousand developers working on GitHub projects. Using the identification of motivated developers, we measure developer performance gaps. We show that motivated developers have up to 70% longer activity period, produce up to 300% more commits, and invest up to 44% more time per commit.
Wed 19 JunDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
11:00 - 12:20 | Human AspectsShort Papers, Vision and Emerging Results / Research Papers / Industry at Room Capri Chair(s): Guilherme Horta Travassos Federal University of Rio de Janeiro | ||
11:00 15mTalk | Trustworthy AI in practice: an analysis of practitioners' needs and challenges Research Papers Maria Teresa Baldassarre Department of Computer Science, University of Bari , Domenico Gigante SER&Practices and University of Bari, Azzurra Ragone University of Bari, Sara Tibidò Scuola IMT Alti Studi Lucca, Marcos Kalinowski Pontifical Catholic University of Rio de Janeiro (PUC-Rio) | ||
11:15 15mTalk | "Looks Good To Me ;-)": Assessing Sentiment Analysis Tools for Pull Request Discussions Research Papers Daniel Coutinho Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Luísa Cito Pontifical Catholic University of Rio de Janeiro, Maria Vitória Lima Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Beatriz Arantes Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Juliana Alves Pereira PUC-Rio, Johny Arriel PUC-Rio, João Godinho Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Vinícius Martins PUC-Rio, Paulo Vítor C. F. Libório Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Leonardo Leite Federal University of Alagoas (UFAL), Alessandro Garcia Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Wesley Assunção North Carolina State University, Igor Steinmacher Northern Arizona University, Augusto Baffa PUC-Rio, Baldoino Fonseca Federal University of Alagoas | ||
11:30 15mTalk | Motivation Research Using Labeling Functions Research Papers DOI Pre-print | ||
11:45 15mTalk | Insight AI Risk Detection Model - Vulnerable People Emotional Situation Support Industry Diego Gosmar Open Voice Trustmark Ethical use task force Linux Foundation AI & DATA, Elena Peretto Fundaci— Ajuda i Esperanچa, Oita Coleman Open Voice Trustmark Ethical use task force Linux Foundation AI & DATA | ||
12:00 10mTalk | On the Use of ChatGPT for Code Review Short Papers, Vision and Emerging Results Miku Watanabe Nara College, National Institute of Technology/Nara Institute of Science and Technology, Yutaro Kashiwa Nara Institute of Science and Technology, Bin Lin Radboud University, Toshiki Hirao , Ken'Ichi Yamaguchi , Hajimu Iida Nara Institute of Science and Technology Pre-print | ||
12:10 10mTalk | What You Use is What You Get: Unforced Errors in Studying Cultural Aspects in Agile Software Development Short Papers, Vision and Emerging Results Michael Neumann University of Applied Sciences & Arts Hannover, Klaus Schmid University of Hildesheim, Lars Baumann DOI Pre-print | ||