A Journey Into the Emotions of Software Developers
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The document discusses a keynote presentation on the emotional landscape of software developers and its impact on their productivity. It highlights the importance of emotional awareness in improving individual well-being, team communication, and overall organizational productivity, drawing on research findings and field studies. The presentation also examines the role of biometric sensors in recognizing developers' emotions and the challenges associated with emotion assessment.
A Journey Into the Emotions of Software Developers
- 1. A Journey Into the Emotions of Software Developers Keynote for CHASE 2024 - April 14, 2024 @NicoleNovielli nicole.novielli@uniba.it Nicole Novielli University of Bari, Italy Collaborative Development Group
- 2. Acknowledgements Daniela Girardi University of Bari Daniela Grassi University of Bari D. Girardi, F. Lanubile, N. Novielli and A. Serebrenik, "Emotions and Perceived Productivity of Software Developers at the Workplace, in IEEE Transactions on Software Engineering, 2022 doi: 10.1109/TSE.2021.3087906. D. Grassi, F. Lanubile, N. Novielli and A. Serebrenik, "Towards Supporting Emotion Awareness in Retrospective Meetings," 2023 IEEE/ACM 45th International Conference on Software Engineering: New Ideas and Emerging Results (ICSE-NIER), Melbourne, Australia, 2023, pp. 101-105, doi: 10.1109/ICSE-NIER58687.2023.00024. D. Girardi, N.Novielli, D. Fucci, F. Lanubile. “Recognizing Developers’ Emotions while Programming“. In Proceedings of the 42th International Conference on Software Engineering (ICSE 2020) October, 2020 – DOI: https://doi.org/10.1145/3377811.3380374 Filippo Lanubile University of Bari Alexander Serebrenik TU/e
- 4. Ekman, P. (1999). Basic emotions. In T. Dalgleish & M. J. Power (Eds.), Handbook of cognition and emotion (pp. 45–60). John Wiley & Sons Ltd. https://doi.org/10.1002/0470013494.ch3
- 5. Ekman, P. (1999). Basic emotions. In T. Dalgleish & M. J. Power (Eds.), Handbook of cognition and emotion (pp. 45–60). John Wiley & Sons Ltd. https://doi.org/10.1002/0470013494.ch3 Anger Fear Disgust Surprise Joy Sadness Ekman’s Basic Emotions
- 6. Picture: https://theyellowspot.com/blogs/managing-change-part-2/ Emotions influence creativity and problem solving T. M. Amabile, S. G. Barsade, J. S. Mueller, and B. M. Staw, “Affect and creativity at work,” Administ. Sci. Quart., vol. 50, no. 3, pp. 367–403, 2005.
- 7. Happy developers solve problems better
- 8. Happy developers solve problems better
- 9. Emotional Awareness Developer Regulate own behavior Improve individual well- being and productivity
- 11. Mapping code behavior to cause, programming tools, fear of failure, unavailability of resources
- 12. Mapping code behavior to cause, programming tools, fear of failure, unavailability of resources Anger as a proxy for different problems Towards SELF Towards OTHERS Towards OBJECT
- 13. Mapping code behavior to cause, programming tools, fear of failure, unavailability of resources Anger as a proxy for different problems Towards SELF Towards OTHERS Towards OBJECT Actionable insights!
- 14. • Programmers cooperate, directly or indirectly • Massive adoption of social media and rise of the ‘social programmer’ (Storey, ‘12) and the surrounding ecosystem Software development involves interaction
- 15. • Programmers cooperate, directly or indirectly • Massive adoption of social media and rise of the ‘social programmer’ (Storey, ‘12) and the surrounding ecosystem Software development involves interaction
- 16. Emotional Awareness Developer Regulate own behavior Improve individual well- being and productivity Team Enhance communication, coordination Improve productivity and organization of work
- 17. Emotional Awareness Developer Regulate own behavior Improve individual well- being and productivity Team Enhance communication, coordination Improve productivity and organization of work Organization Improve job satisfaction Reduce the risk of undesired turnover
- 18. Emotional Awareness • Investigate the relationship between emotions and productivity • Identify causes for positive and negative emotions • Design and validate tools and practices to support emotional awareness
- 19. Emotions and Self-assessed Productivity
- 20. Developers’ emotions, productivity and satisfaction
- 21. Five companies Dutch software development companies, including - One startup (1 founder and 2 employees) - Two SMEs (between 20 and 200 employees) - Two large companies (> 20.000 employees) 21 professional developers - 18 men, 3 women - Average age: 33 years ± 7.2, ranging from 23 to 50 - Average experience in software development: 8 years ± 6.2, ranging from 1 to 25 Field Study
- 22. Five companies Dutch software development companies, including - One startup (1 founder and 2 employees) - Two SMEs (between 20 and 200 employees) - Two large companies (> 20.000 employees) 21 professional developers - 18 men, 3 women - Average age: 33 years - Average experience in software development: 8 years Field Study
- 23. RQ1. What is the range of developers’ emotions at the workplace? RQ2. To what extent are developers emotions related to self-assessed productivity during the workday?
- 24. Study protocol 2/3 weeks
- 25. J. A. Russell, A circumplex model of affect, Journal of Personality and Social Psychology 1980, Vol 39, no. 6 (Un)Pleasantness of the emotion stimulus
- 26. J. A. Russell, A circumplex model of affect, Journal of Personality and Social Psychology 1980, Vol 39, no. 6
- 27. Emotion self-report Valence (Un)Pleasantness of the emotion stimulus Arousal Level of activation of the emotion stimulus Dominance A person’s perception of being in control of a situation
- 28. Perceived productivity Self-assessed Values ranging from very low to very high
- 32. Correlation Between Emotions and Perceived Productivity
- 33. Valence is positively correlated with perceived productivity. Interaction between valence and time (morning vs. afternoon) Emotions and self-assessed productivity
- 34. Valence is positively correlated with perceived productivity Stronger correlation in the afternoon. Conversely, the correlation between dominance and productivity is stronger in the morning. This could be due to fatigue, which is known to impair emotion regulation. Emotions and self-assessed productivity
- 35. Why are Developers (Un)Happy ?
- 36. “Did you experience anything that might have affected your emotions during the last session?”
- 37. Positive: 18 Negative: 19 Triggers of emotions 350 answers 48
- 38. Emotion triggers
- 39. Emotion triggers
- 40. Positive emotions triggers High perceived productivity
- 41. Code quality Positive emotions triggers
- 44. Negative emotions triggers Low perceived productivity
- 47. Negative emotions triggers Poor code and tooling
- 48. Negative emotions triggers Time pressure
- 49. A recipe for happiness?
- 50. A recipe for happiness?
- 52. Developers discuss their positive and negative feelings about events and difficulties encountered during retrospective meetings
- 53. “ “
- 54. Westerink et al. Deriving a Cortisol-Related Stress Indicator From Wearable Skin Conductance Measurements: Quantitative Model & Experimental Validation, Frontiers in Computer Science (2020)
- 55. Galvanic skin response (GSR) • Electrical activity of the skin • Changes due to the variation in body sweating • Electrical changes in the skin could be due to variation in emotions
- 58. Can we recognize developers’ emotions at the workplace using lightweight biometric sensors?
- 62. Sensor-based recognition of developers’ emotions
- 63. Minimal sensor setting for emotion recognition while programming Lab study
- 64. Machine Learning Sensor-based Emotion Recognition Empatica E4
- 65. Field study Our classifiers outperform the baseline
- 66. Field study The performance is comparable to the one in the lab Lab study
- 69. Sensor-based emotion recognition Hold-out scores are higher than leave-one-subject out
- 70. Variability between participants Also observed in the lab study (Girardi et al., ICSE 2020)
- 71. • Individual training/fine-tuning of emotion classifiers • Further validation with larger/more diverse pool of participants from different companies • Self-disclosure of negative emotions • Analysis of GSR peaks as proxy of stress Open challenges
- 72. Open challenges • Individual training/fine-tuning of emotion classifiers • Self-disclosure of negative emotions • Analysis of GSR peaks as proxy of stress
- 73. Open challenges • Individual training/fine-tuning of emotion classifiers • Self-disclosure of negative emotions • Analysis of GSR peaks as proxy of stress
- 74. Open challenges • Individual training/fine-tuning of emotion classifiers • Self-disclosure of negative emotions • (Mis)alignment of different data sources • Analysis of GSR peaks as proxy of stress
- 75. Emotion as a coherent response among different components (Pekrun) Multiple emotion assessment methods might not align at a particular moment in time At the cognitive level, the emotion is triggered by the assessment of a situation (i.e., worrying about something threatening my goals). At a physical level, emotions reflect in biometrics changes (e.g, EDA changes due to sweating and heart rate rising in presence of anxiety) and might be also visible through facial expressions. J. M. Harley, et al. “A multi-componential analysis of emotions during complex learning with an intelligent multi-agent system,” Computers in Human Behavior, vol. 48, pp. 615–625, 2015. R. Pekrun, Emotions as Drivers of Learning and Cognitive Development. New York, NY: Springer New York, 2011, pp. 23–39.
- 76. • 23 participants • Java development tasks Girardi et al. (ICSE 2020) Gold standard: facial expression -100 100 Valence in {Negative, Neutral, Positive}
- 78. F1 = .59 >> F1 = .68 Self-report as gold standard Facial expression as gold standard
- 80. Ethical and Privacy concerns Reduced invasiveness • Focus on the individual: providing individual providing personalized support • Awareness of the possibility of misclassification • Focus on the team: sharing on a voluntary basis
- 84. @NicoleNovielli