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Are Happy Developers More Productive?

The Correlation of Affective States of Software Developers and Their Self-assessed Productivity

  • Conference paper
Product-Focused Software Process Improvement (PROFES 2013)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 7983))

Abstract

For decades now, it has been claimed that a way to improve software developers’ productivity is to focus on people. Indeed, while human factors have been recognized in Software Engineering research, few empirical investigations have attempted to verify the claim. Development tasks are undertaken through cognitive processing abilities. Affective states – emotions, moods, and feelings - have an impact on work-related behaviors, cognitive processing activities, and the productivity of individuals. In this paper, we report an empirical study on the impact of affective states on software developers’ performance while programming. Two affective states dimensions are positively correlated with self-assessed productivity. We demonstrate the value of applying psychometrics in Software Engineering studies and echo a call to valorize the human, individualized aspects of software developers. We introduce and validate a measurement instrument and a linear mixed-effects model to study the correlation of affective states and the productivity of software developers.

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References

  1. Ashkanasy, N.M., Daus, C.S.: Emotion in the workplace: The new challenge for managers. The Academy of Management Executive 16(1), 76–86 (2002)

    Article  Google Scholar 

  2. Barsade, S.G., Gibson, D.E.: Group emotion: A view from top and bottom. Research On Managing Groups And Teams 1(4), 81–102 (1998)

    Google Scholar 

  3. Beal, D.J., et al.: An episodic process model of affective influences on performance. Journal of Applied Psychology 90(6), 1054–1068 (2005)

    Article  Google Scholar 

  4. Boehm, B.: Understanding and Controlling Software Costs. IEEE Transactions on Software Engineering 14(10), 1462–1477 (1990)

    Article  Google Scholar 

  5. Bradley, L.: Measuring emotion: the self-assessment semantic differential. Journal of Behavior Therapy and Experimental Psychiatry 25(1), 49–59 (1994)

    Article  Google Scholar 

  6. Cockburn, A., Highsmith, J.: Agile software development, the people factor. IEEE Computer 34(11), 131–133 (2001)

    Article  Google Scholar 

  7. Csikszentmihalyi, M.: Finding flow. Psychology Today 30(4), 46 (1997)

    Google Scholar 

  8. Dow, J.: External and Internal Approaches to Emotion. Psycoloquy 3(1), 2 (1992)

    Google Scholar 

  9. Feldt, R., et al.: Towards individualized software engineering: empirical studies should collect psychometrics. In: International Workshop on Cooperative and Human Aspects of Software Engineering, pp. 49–52. ACM (2008)

    Google Scholar 

  10. Fischer, G.: Cognitive View of Reuse and Redesign. IEEE Software 4(4), 60–72 (1987)

    Article  Google Scholar 

  11. Fisher, C.D., Noble, C.: A Within-Person Examination of Correlates of Performance and Emotions While Working. Human Performance 17(2), 145–168 (2004)

    Article  Google Scholar 

  12. Graziotin, D., et al.: Appendix for “Are Happy Developers more Productive? The Correlation of Affective States of Software Developers and their self-assessed Productivity”, http://figshare.com/articles/Appendix_for_Are_Happy_Developers_more_Productive_The_Correlation_of_Affective_States_of_Software_Developers_and_their_self_assessed_Productivity_/683885 , doi:10.6084/m9.figshare.683885

  13. Grimm, M., Kroschel, K.: Evaluation of natural emotions using self assessment manikins. In: 2005 IEEE Workshop on Automatic Speech Recognition and Understanding, pp. 381–385 (2005)

    Google Scholar 

  14. Gueorguieva, R., Krystal, J.H.: Move over ANOVA: progress in analyzing repeated-measures data and its reflection in papers published in the Archives of General Psychiatry. Archives of General Psychiatry 61(3), 310–317 (2004)

    Article  Google Scholar 

  15. Ilies, R., Judge, T.: Understanding the dynamic relationships among personality, mood, and job satisfaction: A field experience sampling study. Organizational Behavior and Human Decision Processes 89(2), 1119–1139 (2002)

    Article  Google Scholar 

  16. Khan, I.A., et al.: Do moods affect programmers’ debug performance? Cognition, Technology & Work 13(4), 245–258 (2010)

    Article  Google Scholar 

  17. Kitchenham, B.A., et al.: Preliminary guidelines for empirical research in software engi-neering. IEEE Transactions on Software Engineering 28(8), 721–734 (2002)

    Article  Google Scholar 

  18. Lang, P.J., et al.: International affective picture system (IAPS): Technical manual and affective ratings. Gainesville FL NIMH Center for the study of emotion and attention University of Florida. Technical Report A–6 (1999)

    Google Scholar 

  19. Larson, R., Csikszentmihalyi, M.: The experience sampling method. New Directions for Methodology of Social and Behavioral Science 15(15), 41–56 (1983)

    Google Scholar 

  20. Lewin, K.: A dynamic theory of personality. McGraw-Hill, New York (1935)

    Google Scholar 

  21. Miner, A.G., Glomb, T.M.: State mood, task performance, and behavior at work: A within-persons approach. Organizational Behavior and Human Decision Processes 112(1), 43–57 (2010)

    Article  Google Scholar 

  22. Ong, J.C., et al.: A two-dimensional approach to assessing affective states in good and poor sleepers. Journal of Sleep Research 20(2), 606–610 (2011)

    Article  Google Scholar 

  23. Oswald, A.J., et al.: Happiness and productivity. The Warwick Economics Research Paper Series TWERPS 882, 1–44 (2008)

    Google Scholar 

  24. Parkinson, B., et al.: Changing moods: The psychology of mood and mood regulation. Addison-Wesley Longman, Amsterdam (1996)

    Google Scholar 

  25. Plutchik, R., Kellerman, H.: Emotion, theory, research, and experience. Academic Press, London (1980)

    Google Scholar 

  26. Pukelsheim, F.: The Three Sigma Rule. The American Statistician 48(2), 88–91 (1994)

    MathSciNet  Google Scholar 

  27. Robinson, G.K.: That BLUP is a Good Thing: The Estimation of Random Effects. Statistical Science 6(1), 15–32 (1991)

    Article  MathSciNet  MATH  Google Scholar 

  28. Russell, J.: A Circumplex Model of Affect. Journal of Personality and Social Psychology 39(6), 1161–1178 (1980)

    Article  Google Scholar 

  29. Sampaio, S.C.D.B., et al.: A Review of Productivity Factors and Strategies on Software Development. In: 2010 Fifth International Conference on Software Engineering Advances, pp. 196–204 (2010)

    Google Scholar 

  30. Scacchi, W.: Understanding Software Productivity. Advances in Software Engineering and Knowledge Engineering 4, 37–70 (1995)

    Google Scholar 

  31. Shaw, T.: The emotions of systems developers. In: Proceedings of the 2004 Conference on Computer Personnel Research Careers, Culture, and Ethics in a Networked Environment, SIGMIS CPR 2004, p. 124. ACM Press, New York (2004)

    Chapter  Google Scholar 

  32. Tichy, W.: Hints for reviewing empirical work in software engineering. Empirical Software Engineering 5(4), 309–312 (2000)

    Article  MathSciNet  Google Scholar 

  33. Tsonos, D., et al.: Towards modeling of Readers’ Emotional State response for the automated annotation of documents. In: 2008 IEEE International Joint Conference on Neural Networks IEEE World Congress on Computational Intelligence, pp. 3253–3260 (2008)

    Google Scholar 

  34. Vickers, A.J.: How many repeated measures in repeated measures designs? Statistical issues for comparative trials. BMC Medical Research Methodology 3(22), 1–9 (2003)

    Google Scholar 

  35. Wohlin, C., et al.: Experimentation in software engineering: an introduction. Kluwer Academic Publishers (2000)

    Google Scholar 

  36. Zelenski, J.M., et al.: The Happy-Productive Worker Thesis Revisited. Journal of Happiness Studies 9(4), 521–537 (2008)

    Article  Google Scholar 

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Graziotin, D., Wang, X., Abrahamsson, P. (2013). Are Happy Developers More Productive?. In: Heidrich, J., Oivo, M., Jedlitschka, A., Baldassarre, M.T. (eds) Product-Focused Software Process Improvement. PROFES 2013. Lecture Notes in Computer Science, vol 7983. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39259-7_7

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  • DOI: https://doi.org/10.1007/978-3-642-39259-7_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39258-0

  • Online ISBN: 978-3-642-39259-7

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