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Cited by 126Software Engineering Techniques and PracticesEmotion and Mood RecognitionSoftware Engineering Research

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Do feelings matter? On the correlation of affects and the self‐assessed productivity in software engineering

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Graziotin, Daniel, Wang, Xiaofeng, Abrahamsson, Pekka·2015·Journal of Software: Evolution and Process
DOI 10.1002/smr.1673
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Abstract

Software engineering (SE) research lacks theory and methodologies for addressing human aspects in software development. Development tasks are undertaken through cognitive processing activities. Affects (emotions, moods, and feelings) have a linkage to cognitive processing activities and the productivity of individuals. SE research needs to incorporate affect measurements to valorize human factors and to enhance management styles. The objective of this study is to analyze the affects dimensions of valence, arousal, and dominance of software developers and their real‐time correlation with their self‐assessed productivity (sPR). A repeated measurements design was conducted with eight participants (four students and four professionals), conveniently sampled and studied individually over 90 min of programming. The analysis was performed by fitting a linear mixed‐effects (LME) model. The results showed that valence and dominance are positively correlated with the sPR. The model was able to express about 38% of deviance from the sPR. Many lessons were learned when employing psychological measurements in SE and for fitting LME. This article demonstrates the value of applying psychological tests in SE and echoes a call to valorize the human individualized aspects of software developers. It reports a body of knowledge about affects, their classification, their measurement, and the best practices to perform psychological measurements in SE with LME models. Copyright © 2014 John Wiley & Sons, Ltd.

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  1. 10.1109/32.6191 · DOI
  2. Stangel L, 2013, Silicon Valley's 7 happiest companies (and what employees secretly say about them), Silicon Valley Business Journal, 1
  3. Drell L, 2011, The perks of working at Google, Facebook, Twitter and More [INFOGRAPHIC], Mashable, 1
  4. 10.1111/j.0741‐6261.2008.00028.x · DOI
  5. 10.1016/j.infsof.2010.01.001 · DOI
  6. Sommerville I, 1996, Human, Social and Organisational Influences on the Software Process
  7. 10.1007/978‐3‐642‐16324‐1_1 · DOI · Paper page
  8. 10.1109/2.963450 · DOI
  9. SampaioSCDB BarrosEA Aquino JuniorGS SilvaMJC MeiraSRDL.A review of productivity factors and strategies on software development.Fifth International Conference on Software Engineering Advances 2010;196–204. DOI:10.1109/ICSEA.2010.37 · DOI
  10. FeldtR TorkarR AngelisL SamuelssonM.Towards individualized software engineering.Proceedings of the 2008 international workshop on Cooperative and human aspects of software engineering ‐ CHASE '08 2008;49–52. DOI:10.1145/1370114.1370127 · DOI
  11. 10.1109/MS.1987.231065 · DOI
  12. 10.1007/s10111‐010‐0164‐1 · DOI
  13. Ciborra C, 2002, The Labyrinths of Information: Challenging the Wisdom of Systems
  14. 10.5465/AME.2002.6640191 · DOI
  15. OswaldAJ ProtoE SgroiD.Happiness and productivity.The Warwick Economics Research Paper Series TWERPS no 882 2008;1(882):44.
  16. 10.1007/s10902‐008‐9087‐4 · DOI
  17. 10.1207/s15327043hup1702 · DOI
  18. 10.1037/a0013115 · DOI
  19. 10.1142/9789812798022_0010 · DOI
  20. ShawT.The emotions of systems developers.Proceedings of the 2004 conference on Computer personnel research Careers culture and ethics in a networked environment ‐ SIGMIS CPR '04 2004;124. DOI:10.1145/982372.982403 · DOI
  21. 10.1037/0021‐9010.90.6.1054 · DOI
  22. 10.1145/2380656.2380668 · DOI
  23. 10.1109/ICSE.2001.919082 · DOI
  24. Basili VR, 1992, Software Modeling and Measurement: The Goal/Question/Metric Paradigm
  25. GraziotinD WangX AbrahamssonP.Are happy developers more productive?14th International Conference on Product‐Focused Software Process Improvement (PROFES 2013)2013;7983:50–64. DOI:10.1007/978‐3‐642‐39259‐7_7 · DOI
  26. JedlitschkaA CiolkowskiM.Reporting experiments in software engineering. InGuide to Advanced Empirical Software Engineering.2008 Section II 201–228. · DOI
  27. 10.1145/359511.359523 · DOI
  28. 10.1037/13945-000 · DOI
  29. Plutchik R, 1980, Emotion, Theory, Research, and Experience
  30. 10.1007/BF00992553 · DOI
  31. 10.1016/S0376‐6357(02)00078‐5 · DOI · Paper page
  32. Parkinson B, 1996, Changing Moods: The Psychology of Mood and Mood Regulation
  33. 10.1037/0033‐2909.95.3.542 · DOI · Paper page
  34. Dogan T, 2013, The role of self‐esteem, psychological well‐being, emotional self‐efficacy, and affect balance on happiness: a path model, European Scientific Journal, 9, 31
  35. 10.1007/s11205‐009‐9493‐y · DOI · Paper page
  36. Schwarz N, 1990, Handbook of Motivation and Cognition: Foundations of Social Behavior, 527
  37. 10.1037/0022‐3514.45.3.513 · DOI · Paper page
  38. 10.1037/a0012815 · DOI
  39. 10.1111/j.1467‐8551.2006.00489.x · DOI
  40. Weiss H, 1996, Affective events theory: A theoretical discussion of the structure, causes and consequences of affective experiences at work, Research in Organizational Behavior, 18, 1
  41. 10.1002/(SICI)1099‐1379(200003)21:2<185::AID‐JOB34>3.0.CO;2‐M · DOI
  42. Ekman P, 1971, Universals and cultural differences in facial expressions of emotion, Nebraska Symposium on Motivation, 207
  43. Matsumoto D, 2011, Reading facial expressions of emotion, Psychological Science Agenda, American Psychological Association
  44. 10.1037/0022‐3514.52.6.1061 · DOI · Paper page
  45. 10.1037/h0077714 · DOI · Paper page
  46. 10.1016/S0028‐3932(99)00017‐2 · DOI
  47. Lewin K, 1935, A Dynamic Theory of Personality
  48. 10.1111/j.1469‐8986.1993.tb03352.x · DOI · Paper page
  49. 10.1016/j.paid.2012.01.007 · DOI
  50. 10.1016/0005‐7916(94)90063‐9 · DOI · Paper page
  51. Csikszentmihalyi M, 1997, Finding Flow: The Psychology of Engagement With Everyday Life
  52. 10.1111/j.1365‐2869.2011.00907.x · DOI
  53. GrimmM KroschelK.Evaluation of natural emotions using self assessment manikins.IEEE Workshop on Automatic Speech Recognition and Understanding 2005;381–385. DOI:10.1109/ASRU.2005.1566530 · DOI
  54. TsonosD IkospentakiK KouroupetrolgouG.Towards modeling of readers' emotional state response for the automated annotation of documents.IEEE International Joint Conference on Neural Networks IEEE World Congress on Computational Intelligence 2008;3253–3260. DOI:10.1109/IJCNN.2008.4634260 · DOI
  55. 10.1177/0894439305281844 · DOI
  56. 10.2307/2529876 · DOI · Paper page
  57. 10.1016/j.obhdp.2009.11.009 · DOI
  58. 10.1177/0305735605050650 · DOI
  59. WrobelMR.Emotions in the software development process.6th International Conference on Human System Interactions (HSI) 2013;518–523. DOI:10.1109/HSI.2013.6577875 · DOI
  60. 10.7717/peerj.289 · DOI
  61. 10.1080/00031305.1994.10476030 · DOI
  62. 10.2307/2245695 · DOI
  63. Winter B, 2013, A Very Basic Tutorial for Performing Linear Mixed Effects Analyses
  64. 10.1186/1471‐2288‐3‐22 · DOI
  65. 10.1109/TSE.2002.1027796 · DOI
  66. 10.1023/A:1009844119158 · DOI
  67. Barsade SG, 1998, Group emotion: A view from top and bottom, Research on Managing Groups and Teams, 1, 81
  68. 10.1016/j.tree.2008.10.008 · DOI · Paper page
  69. 10.1145/2380656.2380670 · DOI
  70. 10.1145/2580712 · DOI
  71. 10.1016/j.infsof.2010.12.001 · DOI · Paper page
  72. KettunenP.Orienting high software team performance: dimensions for aligned excellence.14th International Conference on Product‐Focused Software Process Improvement (PROFES 2013)2013;7983:347–350. DOI:10.1007/978‐3‐642‐39259‐7_31 · DOI

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Metadata

Authors
Graziotin, D., Wang, X., & Abrahamsson, P.
Affiliations
Free University of Bozen-Bolzano (IT)
Corresponding author
Graziotin, Daniel
ORCID
Venue
Journal of Software: Evolution and Process
Publisher
Wiley
Published
2014-08-06
Volume
27
Issue
7
Pages
467-487
ISSN
  • 2047-7473 (ISSN-L)
  • 2047-7481
DOI
10.1002/smr.1673
OpenAlex
W2952567205
Cited by
126
References
6
Citations by year
2026: 8 · 2025: 12 · 2024: 15 · 2023: 10 · 2022: 12 · 2021: 13 · 2020: 12 · 2019: 17 · 2018: 4 · 2017: 10 · 2016: 8 · 2015: 5
FWCI
13.26
Type
journal article
Language
en
Open access
Licence
onlinelibrary.wiley.com/termsAndConditions#vor (vor)
Locations
  • Journal of Software Evolution and Process (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • Open Research (University of Surrey) (submittedVersion)
  • arXiv (Cornell University)
Topics
  • Physical Sciences › Computer Science › Information Systems › Software Engineering Techniques and Practices
  • Physical Sciences › Computer Science › Artificial Intelligence › Emotion and Mood Recognition
  • Physical Sciences › Computer Science › Information Systems › Software Engineering Research
Keywords
affect, emotions, valence, arousal, dominance, software developers, programming, human factors in software development, psychological measurement, linear mixed models

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