Home > Research > Publications & Outputs > Measuring Human Values in Software Engineering

Electronic data

  • Measuring Values in SE - ESEM2018

    Rights statement: ESEM '18, October 11–12, 2018, Oulu, Finland © 2018 Copyright is held by the owner/author(s). ACM ISBN 978-1-4503-5823-1/18/10. https://doi.org/10.1145/3239235.3267427

    Accepted author manuscript, 879 KB, PDF-document

    Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License

Text available via DOI:

View graph of relations

Measuring Human Values in Software Engineering

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paper

Published
Publication date12/10/2018
Host publicationProceedings of the 12th International Symposium on Empirical Software Engineering and Measurement: ESEM2018
PublisherACM Press
Original languageEnglish

Abstract

Background: Human values, such as prestige, social justice, and financial success, influence software production decision-making processes. While their subjectivity makes some values difficult to measure, their impact on software motivates our research. Aim: To contribute to the scientific understanding and the empirical investigation of human values in Software Engineering (SE). Approach: Drawing from social psychology, we consider values as mental representations to be investigated on three levels: at a system (L1), personal (L2), and instantiation level (L3). Method: We design and develop a selection of tools for the investigation of values at each level, and focus on the design, development, and use of the Values Q-Sort. Results: From our study with 12 software practitioners, it is possible to extract three values ‘prototypes’ indicative of an emergent typology of values considerations in SE. Conclusions: The Values Q-Sort generates quantitative values prototypes indicating values relations (L1) as well as rich personal narratives (L2) that reflect specific software practices (L3). It thus offers a systematic, empirical approach to capturing values in SE.