Early career software developers and work preferences in software engineering

• 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.

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap -- Programvaruteknik (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Software Engineering (hsv//eng)

Keyword

Five-Factor Model

personality

software engineering

Computer Science

Datavetenskap

Publication and Content Type

ref (subject category)

art (subject category)