An experimental investigation of personality types impact on pair effectiveness in pair programming

Sfetsos, Panagiotis; Stamelos, Ioannis; Angelis, Lefteris; Deligiannis, Ignatios

doi:10.1007/s10664-008-9093-5

Cited by 98 publications

(46 citation statements)

References 56 publications

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“…In Sfetsos et al [13] more advanced statistics were applied indicating better communication, pair performance and pair collaboration-viability for pairs with heterogeneous personalities and temperaments. One year later, in 2010, Hannay et al [4] using the FF model tried to explore the effect of personality on PP performance, without finding any strong indications.…”

Section: Studies On Personality and Software Developmentmentioning

confidence: 99%

“…This does not come as a surprise if we take into account that personality is one of the most complex concepts in the social sciences and its conceptualization and analysis is one of the most challenging tasks in psychology [10]. Even so, the prediction of performance on specific tasks [11], building effective teams [12] or peers in pair programming [13] and, more generally, the search for the most suitable person for a specific IT job [14] shows that personality-focused SE research is both an active area and has many practical applications.…”

Section: Introductionmentioning

confidence: 99%

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Personality, emotional intelligence and work preferences in software engineering: An empirical study

Kosti

Feldt

Angelis

2014

Information and Software Technology

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Context: There is an increasing awareness among Software Engineering (SE) researchers and practitioners that more focus is needed on understanding the engineers developing software. Previous studies show significant associations between the personalities of software engineers and their work preferences.Objective: Various studies on personality in SE have found large, small or no effects and there is no consensus on the importance of psychometric measurements in SE. There is also a lack of studies employing other psychometric instruments or using larger datasets. We aim to evaluate our results in a larger sample, with software engineers in an earlier state of their career, using advanced statistics.Method: An operational replication study where extensive psychometric data from 279 master level students have been collected in a SE program at a Swedish University. Personality data based on the Five-Factor Model, Trait Emotional Intelligence Questionnaire and Self-compassion have been collected. Statistical analysis investigated associations between psychometrics and work preferences and the results were compared to our previous findings from 47 SE professionals.Results: Analysis confirms existence of two main clusters of software engineers; one with more "intense" personalities than the other. This corroborates our earlier results on SE professionals. The student data also show similar associations between personalities and work preferences. However, for other associations there are differences due to the different population of subjects. We also found connections between the emotional intelligence and work preferences, while no associations were found for self-compassion. Conclusion:The associations can help managers to predict and adapt projects and tasks to available staff. The results also show that the Emotional Intelligence instrument can be predictive. The research methods and analytical tools we employ can detect subtle associations and reflect differences between different groups and populations and thus can be important tools for future research as well as industrial practice.

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Section: Studies On Personality and Software Developmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Personality, emotional intelligence and work preferences in software engineering: An empirical study

Kosti

Feldt

Angelis

2014

Information and Software Technology

Self Cite

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“…Thus the practice's success is largely determined by how effectively they work as a team, despite their skills and abilities. In this regard, considerable number of studies have been conducted to understand the role of personality in determining PP's effectiveness either in academic or industry context [53], [29], [51].…”

Section: Related Workmentioning

confidence: 99%

An empirical study of the effects of conscientiousness in pair programming using the five-factor personality model

Salleh

Mendes

Grundy

et al. 2010

Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 1

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This paper describes a formal experiment carried out to investigate the effect of the Personality factor conscientiousness on the effectiveness of Pair Programming as a pedagogical tool in higher Education. This experiment took place at the University of Auckland, using as subjects undergraduate students attending an introductory programming course. Conscientiousness was chosen because it has been shown to be the most consistent predictor of academic achievement. Our findings showed that differences in conscientiousness level did not significantly affect the academic performance of students who pair programmed, which could have been due to the short duration of the tasks used throughout the experiment. However, results revealed that another Personality factor -Openness to experience -presented a significant correlation with paired students' academic performance.

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“…al. used the coffee machine project to investigate the impact of developer personalities and temperaments on communication, pair performance and pair viability-collaboration [17].…”

Section: B Software Evolution Experimentsmentioning

confidence: 99%

Impact of Unanticipated software evolution on development cost and quality: an empirical evaluation

Vilar¹,

Lima²,

Almeida³

et al. 2015

International Conferences on Software Engineering and Knowledge Engineering

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Abstract-Most techniques to aid maintenance and evolution of software require to define extension points. Generally, developers try to anticipate the parts that are more likely to evolve, but they can make mistakes and spend money in vain. With Unanticipated Software Evolution, developers can easily change any element of the software, even those that are not related with an extension point. However, we have not found empirical validations of Unanticipated Software Evolution impact on development cost and quality. In this work, we design and execute an experiment for Unanticipated Software Evolution (specifically, using the COMPOR platform), in order to compare its results metrics --time, lines of code, test coverage and complexity --using OO systems as baseline. 30 undergraduate students were subjects in this experiment. We concluded that COMPOR have significant impact on the Lines of code and Complexity metrics, reducing the amount of lines changed and the McCabe cyclomatic complexity on evolution of a small system.

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An experimental investigation of personality types impact on pair effectiveness in pair programming

Cited by 98 publications

References 56 publications

Personality, emotional intelligence and work preferences in software engineering: An empirical study

Personality, emotional intelligence and work preferences in software engineering: An empirical study

An empirical study of the effects of conscientiousness in pair programming using the five-factor personality model

Impact of Unanticipated software evolution on development cost and quality: an empirical evaluation

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