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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
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
Why Developers’ Emotions?
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
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
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.
Happy developers solve
problems better
Happy developers solve
problems better
Emotional Awareness
Developer
Regulate own behavior
Improve individual well-
being and productivity
Mapping code behavior to cause,
programming tools,
fear of failure,
unavailability of resources
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
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!
• 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
• 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
Emotional Awareness
Developer
Regulate own behavior
Improve individual well-
being and productivity
Team
Enhance communication,
coordination
Improve productivity and
organization of work
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
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
Emotions and Self-assessed Productivity
Developers’ emotions, productivity and
satisfaction
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
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
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?
Study protocol 2/3 weeks
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
J. A. Russell, A circumplex model of affect, Journal of Personality and Social Psychology 1980, Vol 39, no. 6
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
Perceived productivity
Self-assessed
Values ranging from very low to
very high
Self-reported Emotions and
Productivity
Developer’s emotions
Developer’s emotions
Correlation Between
Emotions and Perceived
Productivity
Valence is positively correlated with
perceived productivity.
Interaction between valence and time
(morning vs. afternoon)
Emotions and self-assessed productivity
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
Why are Developers (Un)Happy ?
“Did you experience
anything that might have
affected your emotions
during the last session?”
Positive: 18 Negative: 19
Triggers of emotions
350 answers
48
Emotion triggers
Emotion triggers
Positive emotions triggers
High perceived
productivity
Code quality
Positive emotions triggers
Effective
Collaboration
Positive emotions triggers
Positive emotions triggers
Breaks
Negative emotions triggers
Low perceived
productivity
Negative emotions triggers
Fatigue
Negative emotions triggers
Code
comprehension
Negative emotions triggers
Poor code and
tooling
Negative emotions triggers
Time pressure
A recipe for happiness?
A recipe for happiness?
Developers discuss their positive and negative
feelings about events and difficulties encountered
during retrospective meetings
“
“
Westerink et al. Deriving a Cortisol-Related Stress Indicator From Wearable Skin Conductance Measurements: Quantitative Model & Experimental Validation, Frontiers in Computer Science (2020)
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
Can we recognize developers’ emotions at the workplace using lightweight
biometric sensors?
https://www.eecs.qmul.ac.uk/mmv
/datasets/deap/
https://www.eecs.qmul.ac.uk/mmv
/datasets/deap/
Sensor-based recognition of developers’ emotions
Minimal sensor setting for emotion recognition while
programming
Lab study
Machine Learning
Sensor-based Emotion Recognition
Empatica E4
Field study
Our classifiers outperform the baseline
Field study
The performance is
comparable to the one
in the lab
Lab study
Leave-one-subject-out
Sensor-based emotion recognition
Hold-out scores are higher than leave-one-subject out
Variability between participants
Also observed in the lab study (Girardi et al., ICSE 2020)
• 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
Open challenges
• Individual training/fine-tuning of emotion
classifiers
• Self-disclosure of negative emotions
• Analysis of GSR peaks as proxy of stress
Open challenges
• Individual training/fine-tuning of
emotion classifiers
• Self-disclosure of negative
emotions
• Analysis of GSR peaks as proxy of
stress
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
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.
• 23 participants
• Java development tasks
Girardi et al. (ICSE 2020)
Gold standard: facial expression
-100 100
Valence in
{Negative, Neutral, Positive}
F1 = .59
>>
F1 = .68
Self-report
as gold standard
Facial expression
as gold standard
Ethical and Privacy
concerns
Reduced
invasiveness
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
@NicoleNovielli

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A Journey Into the Emotions of Software Developers