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Early career software developers and work preferences in software engineering
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).ORCID iD: 0000-0002-7885-0369
University of Engineering and Technology, Pakistan.ORCID iD: 0000-0001-7863-3746
University of Malakand, Pakistan.
2024 (English)In: Journal of Software: Evolution and Process, ISSN 2047-7473, E-ISSN 2047-7481, Vol. 36, no 2, article id e2513Article in journal (Refereed) Published
Abstract [en]

Context: The software engineering researchers and practitioners echoed the needfor investigations to better understand the engineers developing software andservices. In light of current studies, there are significant associations between thepersonalities of software engineers and their work preferences. However, limitedstudies are using psychometric measurements in software engineering.Objective: We aim to evaluate attitudes of early-stage software engineers andinvestigate link between their personalities and work preferences.Method: We collected extensive psychometric data from 303 graduate-levelstudents in Computer Science programs at four Pakistani and one Swedish universityusing Five-Factor Model. The statistical analysis investigated associations betweenvarious personality traits and work preferences.Results: The data support the existence of two clusters of software engineers, one ofwhich is more highly rated across the board. Numerous correlations exist betweenpersonality qualities and the preferred types of employment for software developers.For instance, those who exhibit greater levels of emotional stability, agreeableness,extroversion, and conscientiousness like working on technical activities on a settimetable. Similar relationships between personalities and occupational choices arealso evident in the earlier studies. More neuroticism is reported in femalerespondents than in male respondents. Higher intelligence was demonstrated bythose who worked on the“entire development process”and“technical componentsof the project.”Conclusion: When assigning project tasks to software engineers, managers might usethe statistically significant relationships that emerged from the analysis of personalityattributes. It would be beneficial to construct effective teams by taking personalityfactors like extraversion and agreeableness into consideration. The study techniquesand analytical tools we use may identify subtle relationships and reflect distinctionsacross various groups and populations, making them valuable resources for bothfuture academic research and industrial practice.

Place, publisher, year, edition, pages
John Wiley & Sons, 2024. Vol. 36, no 2, article id e2513
Keywords [en]
Five-Factor Model, personality, software engineering
National Category
Software Engineering
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-92125DOI: 10.1002/smr.2513ISI: 000863751100001Scopus ID: 2-s2.0-85139248903OAI: oai:DiVA.org:kau-92125DiVA, id: diva2:1701241
Available from: 2022-10-05 Created: 2022-10-05 Last updated: 2024-02-22Bibliographically approved

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Ahmad, Muhammad Ovais

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