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Assessing personality traits in a large scale software development company: exploratory industrial case study

Akarsu, Zulal, Orgun, Pinar, Dinc, Hakan, Gunyel, Bora and Yilmaz, Murat orcid logoORCID: 0000-0002-2446-3224 (2019) Assessing personality traits in a large scale software development company: exploratory industrial case study. In: 26th European Conference on Software Process Improvement (2019), 18 - 20 Sept 2019, Edinburgh, Scotland. ISBN 978-3-030-28004-8

Abstract
Software development methodologies become increasingly more people and team-oriented. However, many software projects fail due to conflicts of team members. Formation of an effective software development team may be particularly challenging given the differences inherent across an individual’s personality. This paper explores personality traits of agile software development teams by using a context-specific interactive assessment. Concerning the assessment, we have conducted a questionnaire with 110 participants from a large-scale software development company. We have visualized personality traits with team radar charts showing the personality traits of 18 project teams and analyzed the results by validation interviews. Our preliminary results indicate that higher introversion is observed most commonly in isolated teams that has less contact with customers. Moreover, high levels of agreeableness and conscientiousness personality traits are observed in most of the agile software development teams.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:Software Team Visualization; Agile Software Development; Personality Assessment; Industrial Case Study
Subjects:UNSPECIFIED
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Published in: European Conference on Software Process Improvement. Communications in Computer and Information Science (CCIS) 1060. Springer. ISBN 978-3-030-28004-8
Publisher:Springer
Official URL:http://dx.doi.org/10.1007/978-3-030-28005-5_15
Copyright Information:© 2019 Springer
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:24033
Deposited On:18 Dec 2019 15:09 by Thomas Murtagh . Last Modified 18 Dec 2019 15:09
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