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With Great Humor Comes Great Developer Engagement

Authors:

Deepika Tiwari,

Martin Monperrus,

Benoit BaudryAuthors Info & Claims

ICSE-SEIS'24: Proceedings of the 46th International Conference on Software Engineering: Software Engineering in Society

Pages 1 - 11

https://doi.org/10.1145/3639475.3640099

Published: 06 June 2024 Publication History

Abstract

The worldwide collaborative effort for the creation of software is technically and socially demanding. The more engaged developers are, the more value they impart to the software they create. Engaged developers, such as Margaret Hamilton programming Apollo 11, can succeed in tackling the most difficult engineering tasks. In this paper, we dive deep into an original vector of engagement - humor - and study how it fuels developer engagement. First, we collect qualitative and quantitative data about the humorous elements present within three significant, real-world software projects: faker, which helps developers introduce humor within their tests; lolcommits, which captures a photograph after each contribution made by a developer; and volkswagen, an exercise in satire, which accidentally led to the invention of an impactful software tool. Second, through a developer survey, we receive unique insights from 125 developers, who share their real-life experiences with humor in software.

Our analysis of the three case studies highlights the prevalence of humor in software, and unveils the worldwide community of developers who are enthusiastic about both software and humor. We also learn about the caveats of humor in software through the valuable insights shared by our survey respondents. We report clear evidence that, when practiced responsibly, humor increases developer engagement and supports them in addressing hard engineering and cognitive tasks. The most actionable highlight of our work is that software tests and documentation are the best locations in code to practice humor.

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Cited By

Tiwari DGamage YMonperrus MBaudry B(2024)PROZE: Generating Parameterized Unit Tests Informed by Runtime Data2024 IEEE International Conference on Source Code Analysis and Manipulation (SCAM)10.1109/SCAM63643.2024.00025(166-176)Online publication date: 7-Oct-2024
https://doi.org/10.1109/SCAM63643.2024.00025
Baudry BEtemadi KFang SGamage YLiu YLiu YMonperrus MRon JSilva ATiwari D(2024)Generative AI to Generate Test Data GeneratorsIEEE Software10.1109/MS.2024.341857041:6(55-64)Online publication date: 1-Nov-2024
https://dl.acm.org/doi/10.1109/MS.2024.3418570

Index Terms

With Great Humor Comes Great Developer Engagement
1. Social and professional topics
  1. User characteristics
    1. Cultural characteristics
2. Software and its engineering
  1. Software creation and management
    1. Collaboration in software development
      1. Programming teams

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Information & Contributors

Information

Published In

cover image ACM Conferences

ICSE-SEIS'24: Proceedings of the 46th International Conference on Software Engineering: Software Engineering in Society

April 2024

210 pages

ISBN:9798400704994

DOI:10.1145/3639475

Co-chairs:
Ana Paiva,
Rui Abreu,
Bonita Sharif
University of Nebraska-Lincoln, USA
,
Xin Xia
Huawei Technologies, China
,
Program Co-chairs:
Prof. Abhik Roychoudhury,
Margaret Storey

This work is licensed under a Creative Commons Attribution International 4.0 License.

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Faculty of Engineering of University of Porto

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Association for Computing Machinery

New York, NY, United States

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Published: 06 June 2024

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ICSE-SEIS'24

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SIGSOFT

ICSE-SEIS'24: 46th International Conference on Software Engineering: Software Engineering in Society

April 14 - 20, 2024

Lisbon, Portugal

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ICSE 2025

2025 IEEE/ACM 46th International Conference on Software Engineering

April 26 - May 3, 2025

Ottawa , ON , Canada

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Cited By

Tiwari DGamage YMonperrus MBaudry B(2024)PROZE: Generating Parameterized Unit Tests Informed by Runtime Data2024 IEEE International Conference on Source Code Analysis and Manipulation (SCAM)10.1109/SCAM63643.2024.00025(166-176)Online publication date: 7-Oct-2024
https://doi.org/10.1109/SCAM63643.2024.00025
Baudry BEtemadi KFang SGamage YLiu YLiu YMonperrus MRon JSilva ATiwari D(2024)Generative AI to Generate Test Data GeneratorsIEEE Software10.1109/MS.2024.341857041:6(55-64)Online publication date: 1-Nov-2024
https://dl.acm.org/doi/10.1109/MS.2024.3418570

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