research-article

Mining Communication Patterns in Software Development: A GitHub Analysis

Authors:

Michele Marchesi,

Roberto Tonelli,

Giuseppe DestefanisAuthors Info & Claims

PROMISE'18: Proceedings of the 14th International Conference on Predictive Models and Data Analytics in Software Engineering

Pages 70 - 79

https://doi.org/10.1145/3273934.3273943

Published: 10 October 2018 Publication History

Abstract

Background: Studies related to human factors in software engineering are providing insightful information on the emotional state of contributors and the impact this has on the code. The open source software development paradigm involves different roles, and previous studies about emotions in software development have not taken into account what different roles might play when people express their feelings. Aim: We present an analysis of issues and commits on five GitHub projects distinguishing contributors between users and developers, and between one-commit and multi-commit developers. Method: We analyzed more than 650K comments from 130K issues of 64K contributors. We calculated emotions (love, joy, anger, sadness) and politeness of the comments related to the issues of the considered projects and introduced the definition of contributor fan-in and fan-out. Results: Results show that users and developers communicate differently as well as multi-commit developers and one-commit developers do. Conclusions: We provide empirical evidence that one-commit developers are more active and more polite in posting comments. Multi-commit developers are less active in posting comments, and while commenting, they are less polite than when commented.

References

[1]

Silvia T Acuña, Marta Gómez, and Natalia Juristo. 2008. Towards understanding the relationship between team climate and software qualityâĂTa quasi-experimental study. Empirical software engineering 13, 4 (2008), 401--434.

Digital Library

[2]

Teresa Amabile, Sigal G. Barsade, Jennifer S. Mueller, and Barry M. Staw. 2005. Affect and Creativity at Work. Administrative Science Quarterly 50, 3 (Sept. 2005), 367--403.

[3]

Blerina Bazelli, Abram Hindle, and Eleni Stroulia. 2013. On the personality traits of Stack Overflow users. In Software Maintenance (ICSM), 2013 29th IEEE International Conference on. IEEE, 460--463.

Digital Library

[4]

Fabio Calefato, Filippo Lanubile, Federico Maiorano, and Nicole Novielli. 2017. Sentiment Polarity Detection for Software Development. Empirical Software Engineering (2017), 1--31.

Digital Library

[5]

Alistair Cockburn and Jim Highsmith. 2001. Agile software development: The people factor. Computer 11 (2001), 131--133.

Digital Library

[6]

Melvin E Conway. 1968. How do committees invent. Datamation 14, 4 (1968), 28--31.

[7]

Cristian Danescu-Niculescu-Mizil, Moritz Sudhof, Dan Jurafsky, Jure Leskovec, and Christopher Potts. 2013. A computational approach to politeness with application to social factors. In Proceedings of ACL.

[8]

Jorge Carrillo de Albornoz, Laura Plaza, and Pablo Gervás. 2012. SentiSense: An easily scalable concept-based affective lexicon for sentiment analysis. In LKEC. 3562--3567.

[9]

Giuseppe Destefanis, Marco Ortu, David Bowes, Michele Marchesi, and Roberto Tonelli. 2018. On Measuring Affects of GitHub Issues' Commenters. In Emotion Awareness in Software Engineering (SEmotion), 2018 IEEE/ACM 3rd International Workshop on.

Digital Library

[10]

Giuseppe Destefanis, Marco Ortu, Steve Counsell, Stephen Swift, Michele Marchesi, and Roberto Tonelli. 2016. Software development: do good manners matter? PeerJ Computer Science 2 (2016), e73.

[11]

Giuseppe Destefanis, Marco Ortu, Steve Counsell, Stephen Swift, Roberto Tonelli, and Michele Marchesi. 2017. On the randomness and seasonality of affective metrics for software development. In Proceedings of the Symposium on Applied Computing. ACM, 1266--1271.

Digital Library

[12]

Amir Erez and Alice M Isen. 2002. The influence of positive affect on the components of expectancy motivation. Journal of Applied Psychology 87, 6 (2002), 1055.

[13]

Robert Feldt, Richard Torkar, Lefteris Angelis, and Maria Samuelsson. 2008. Towards individualized software engineering: empirical studies should collect psychometrics. In Proceedings of the 2008 international workshop on Cooperative and human aspects of software engineering. ACM, 49--52.

Digital Library

[14]

Georgios Gousios. 2013. The GHTorrent dataset and tool suite. In Proceedings of the 10th Working Conference on Mining Software Repositories (MSR '13). IEEE Press, Piscataway, NJ, USA, 233--236. http://dl.acm.org/citation.cfm?id=2487085.2487132

Digital Library

[15]

Daniel Graziotin, Xiaofeng Wang, and Pekka Abrahamsson. 2014. Happy software developers solve problems better: psychological measurements in empirical software engineering. PeerJ 2 (2014), e289.

[16]

Daniel Graziotin, Xiaofeng Wang, and Pekka Abrahamsson. 2014. Software Developers, Moods, Emotions, and Performance. IEEE Software 31, 4 (2014).

[17]

Daniel Graziotin, Xiaofeng Wang, and Pekka Abrahamsson. 2015. Understanding the affect of developers: theoretical background and guidelines for psychoempirical software engineering. In Proceedings of the 7th International Workshop on Social Software Engineering - SSE 2015. ACM Press, New York, New York, USA, 25--32.

Digital Library

[18]

M. R. Islam and M. F. Zibran. 2016. Towards understanding and exploiting developers' emotional variations in software engineering. In 2016 IEEE 14th International Conference on Software Engineering Research, Management and Applications (SERA). 185--192.

[19]

Eugene Kaluzniacky. 2004. Managing psychological factors in information systems work: An orientation to emotional intelligence. IGI Global.

Digital Library

[20]

Iftikhar Ahmed Khan, Willem-Paul Brinkman, and Robert M Hierons. 2011. Do moods affect pro grammersâĂ&Zacute; debug performance? Cognition, Technology & Work 13, 4 (2011), 245--258.

Digital Library

[21]

Amanda Lee and Jeffery C Carver. 2017. Are One-Time Contributors Different? A Comparison to Core and Periphery Developers in FLOSS Repositories. In Empirical Software Engineering and Measurement (ESEM), 2017 ACM/IEEE International Symposium on. IEEE.

Digital Library

[22]

Amanda Lee, Jeffrey C Carver, and Amiangshu Bosu. 2017. Understanding the impressions, motivations, and barriers of one time code contributors to FLOSS projects: a survey. In Proceedings of the 39th International Conference on Software Engineering. IEEE Press, 187--197.

Digital Library

[23]

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

[24]

Alessandro Murgia, Giulio Concas, Roberto Tonelli, Marco Ortu, Serge Demeyer, and Michele Marchesi. 2014. On the influence of maintenance activity types on the issue resolution time. In Proceedings of the 10th international conference on predictive models in software engineering. ACM, 12--21.

Digital Library

[25]

Alessandro Murgia, Marco Ortu, Parastou Tourani, Bram Adams, and Serge Demeyer. 2017. An exploratory qualitative and quantitative analysis of emotions in issue report comments of open source systems. Empirical Software Engineering (2017), 1--44.

Digital Library

[26]

Nicole Novielli, Fabio Calefato, and Filippo Lanubile. 2014. Towards discovering the role of emotions in Stack Overflow. In Proceedings of the 6th International Workshop on Social Software Engineering. ACM, 33--36.

Digital Library

[27]

Marco Ortu, Bram Adams, Giuseppe Destefanis, Parastou Tourani, Michele Marchesi, and Roberto Tonelli. 2015. Are Bullies More Productive? Empirical Study of Affectiveness vs. Issue Fixing Time. In 2015 IEEE/ACM 12th Working Conference on Mining Software Repositories. IEEE, 303--313.

Digital Library

[28]

Marco Ortu, Giuseppe Destefanis, Bram Adams, Alessandro Murgia, Michele Marchesi, and Roberto Tonelli. 2015. The JIRA Repository Dataset. In Proceedings of the 11th International Conference on Predictive Models and Data Analytics in Software Engineering - PROMISE '15. ACM Press, New York, New York, USA, 1--4.

Digital Library

[29]

Marco Ortu, Giuseppe Destefanis, Steve Counsell, Stephen Swift, Roberto Tonelli, and Michele Marchesi. 2016. Arsonists or firefighters? Affectiveness in agile software development. In International Conference on Agile Software Development. Springer, 144--155.

[30]

Marco Ortu, Giuseppe Destefanis, Steve Counsell, Stephen Swift, Roberto Tonelli, and Michele Marchesi. 2017. How diverse is your team? Investigating gender and nationality diversity in GitHub teams. Journal of Software Engineering Research and Development 5, 1 (2017), 9.

[31]

Marco Ortu, Giuseppe Destefanis, Mohamad Kassab, Steve Counsell, Michele Marchesi, and Roberto Tonelli. 2015. Would you mind fixing this issue? An Empirical Analysis of Politeness and Attractiveness in Software Developed Using Agile Boards. In Agile Processes, in Software Engineering, and Extreme Programming. Springer, 129--140.

[32]

Julie Pallant. 2013. SPSS survival manual. McGraw-Hill Education (UK).

[33]

James W Pennebaker, Martha E Francis, and Roger J Booth. 2001. Linguistic inquiry and word count: LIWC 2001. Mahway: Lawrence Erlbaum Associates 71 (2001), 2001.

[34]

R. Plutchik and H. Kellerman. 1980. Emotion, theory, research, and experience. Vol. 1. Academic Press, London.

[35]

Robert Rosenthal. 1994. Parametric measures of effect size. The handbook of research synthesis (1994), 231--244.

[36]

James A. Russell. 1980. A circumplex model of affect. Journal of Personality and Social Psychology 39, 6 (1980), 1161--1178.

[37]

Sidney Siegel. 1956. Nonparametric statistics for the behavioral sciences, New York, 1956. Sisdpalvelusohjesaant& (The manual of Interior Duty), Helsinki (1956).

[38]

Igor Steinmacher, Igor Wiese, Ana Paula Chaves, and Marco Aurélio Gerosa. 2013. Why do newcomers abandon open source software projects?. In Cooperative and Human Aspects of Software Engineering (CHASE), 2013 6th International Workshop on. IEEE, 25--32.

[39]

Igor Steinmacher, Igor Scaliante Wiese, Tayana Conte, Marco Aurélio Gerosa, and David Redmiles. 2014. The hard life of open source software project newcomers. In Proceedings of the 7th international workshop on cooperative and human aspects of software engineering. ACM, 72--78.

Digital Library

[40]

Gary R VandenBos. 2013. APA dictionary of clinical psychology. American Psychological Association.

[41]

Mike Voight and John Callaghan. 2001. A team building intervention program: Application and evaluation with two university soccer teams. Journal of Sport Behavior 24, 4 (2001), 420.

[42]

Amy Beth Warriner, Victor Kuperman, and Marc Brysbaert. 2013. Norms of valence, arousal, and dominance for 13,915 English lemmas. Behavior Research Methods 45, 4 (dec 2013), 1191--1207.

[43]

Jialiang Xie, Minghui Zhou, and Audris Mockus. 2013. Impact of triage: a study of mozilla and gnome. In Empirical Software Engineering and Measurement, 2013 ACM/IEEE International Symposium on. IEEE, 247--250.

[44]

Kazuhiro Yamashita, Shane McIntosh, Yasutaka Kamei, and Naoyasu Ubayashi. 2014. Magnet or sticky? an oss project-by-project typology. In Proceedings of the 11th working conference on mining software repositories. ACM, 344--347.

Digital Library

[45]

David Yukelson. 1997. Principles of effective team building interventions in sport: A direct services approach at Penn State University. Journal of Applied Sport Psychology 9, 1 (1997), 73--96.

[46]

Minghui Zhou and Audris Mockus. 2012. What make long term contributors: Willingness and opportunity in OSS community. In Proceedings of the 34th International Conference on Software Engineering. IEEE Press, 518--528.

Digital Library

Cited By

Graf-Vlachy LWagner S(2024)Cleaning Up Confounding: Accounting for Endogeneity Using Instrumental Variables and Two-Stage ModelsACM Transactions on Software Engineering and Methodology10.1145/3674730Online publication date: 28-Jun-2024
https://dl.acm.org/doi/10.1145/3674730
Vaccargiu MAufiero SBartolucci SNeykova RTonelli RDestefanis G(2024)Sustainability in Blockchain Development: A BERT-Based Analysis of Ethereum Developer DiscussionsProceedings of the 28th International Conference on Evaluation and Assessment in Software Engineering10.1145/3661167.3661194(381-386)Online publication date: 18-Jun-2024
https://dl.acm.org/doi/10.1145/3661167.3661194
Coutinho DCito LLima MArantes BAlves Pereira JArriel JGodinho JMartins VLibório PLeite LGarcia AAssunção WSteinmacher IBaffa AFonseca B(2024)"Looks Good To Me ;-)": Assessing Sentiment Analysis Tools for Pull Request DiscussionsProceedings of the 28th International Conference on Evaluation and Assessment in Software Engineering10.1145/3661167.3661189(211-221)Online publication date: 18-Jun-2024
https://dl.acm.org/doi/10.1145/3661167.3661189
Show More Cited By

Recommendations

On measuring affects of github issues' commenters
SEmotion '18: Proceedings of the 3rd International Workshop on Emotion Awareness in Software Engineering

In this study, we analyzed issues and comments on GitHub projects and built collaboration networks dividing contributors into two categories: users and commenters. We identified as commenters those users who only post comments without posting any issues ...
"Leagile" software development

In recent years there has been a noticeable shift in attention from those who use agile software development toward lean software development, often labelled as a shift "from agile to lean". However, the reality may not be as simple or linear as this ...
Empathy models and software engineering — A preliminary analysis and taxonomy
Abstract
Empathy is widely used in many disciplines such as philosophy, sociology, psychology, health care. Ability to empathise with software end-users seems to be a vital skill software developers should possess. This is because engineering ...
Highlights
- We developed a preliminary taxonomy of empathy considering widely used empathy models.

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences

PROMISE'18: Proceedings of the 14th International Conference on Predictive Models and Data Analytics in Software Engineering

October 2018

97 pages

ISBN:9781450365932

DOI:10.1145/3273934

General Chair:
Burak Turhan
Monash University
,
Program Chairs:
Ayse Tosun
Istanbul Technical University
,
Shane McIntosh
McGill University

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

In-Cooperation

Univ. of Oulu: University of Oulu

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 10 October 2018

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed limited

Conference

PROMISE'18

PROMISE'18: The 14th International Conference on Predictive Models and Data Analytics in Software Engineering

October 10, 2018

Oulu, Finland

Acceptance Rates

Overall Acceptance Rate 98 of 213 submissions, 46%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

26
Total Citations
View Citations
468
Total Downloads

Downloads (Last 12 months)90
Downloads (Last 6 weeks)12

Reflects downloads up to 16 Oct 2024

Other Metrics

View Author Metrics

Citations

Cited By

Graf-Vlachy LWagner S(2024)Cleaning Up Confounding: Accounting for Endogeneity Using Instrumental Variables and Two-Stage ModelsACM Transactions on Software Engineering and Methodology10.1145/3674730Online publication date: 28-Jun-2024
https://dl.acm.org/doi/10.1145/3674730
Vaccargiu MAufiero SBartolucci SNeykova RTonelli RDestefanis G(2024)Sustainability in Blockchain Development: A BERT-Based Analysis of Ethereum Developer DiscussionsProceedings of the 28th International Conference on Evaluation and Assessment in Software Engineering10.1145/3661167.3661194(381-386)Online publication date: 18-Jun-2024
https://dl.acm.org/doi/10.1145/3661167.3661194
Coutinho DCito LLima MArantes BAlves Pereira JArriel JGodinho JMartins VLibório PLeite LGarcia AAssunção WSteinmacher IBaffa AFonseca B(2024)"Looks Good To Me ;-)": Assessing Sentiment Analysis Tools for Pull Request DiscussionsProceedings of the 28th International Conference on Evaluation and Assessment in Software Engineering10.1145/3661167.3661189(211-221)Online publication date: 18-Jun-2024
https://dl.acm.org/doi/10.1145/3661167.3661189
Kumar JChimalakonda SBaysal OLinares-Vasquez MMoran KSteinmacher I(2024)What Do Developers Feel About Fast-Growing Programming Languages? An Exploratory StudyProceedings of the 32nd IEEE/ACM International Conference on Program Comprehension10.1145/3643916.3644422(178-189)Online publication date: 15-Apr-2024
https://dl.acm.org/doi/10.1145/3643916.3644422
Jamieson JYamashita NFoong ERoychoudhury APaiva AAbreu RStorey M(2024)Predicting open source contributor turnover from value-related discussions: An analysis of GitHub issuesProceedings of the IEEE/ACM 46th International Conference on Software Engineering10.1145/3597503.3623340(1-13)Online publication date: 20-May-2024
https://dl.acm.org/doi/10.1145/3597503.3623340
Shafiq SMayr‐Dorn CMashkoor AEgyed A(2024)Balanced knowledge distribution among software development teams—Observations from open‐ and closed‐source software developmentJournal of Software: Evolution and Process10.1002/smr.2655Online publication date: 13-Feb-2024
https://doi.org/10.1002/smr.2655
Cabras MLunesu MPinna AFenu G(2023)A Notarization System for Water Quality Parameters2023 IEEE/ACM 6th International Workshop on Emerging Trends in Software Engineering for Blockchain (WETSEB)10.1109/WETSEB59161.2023.00010(33-36)Online publication date: May-2023
https://doi.org/10.1109/WETSEB59161.2023.00010
Agroskin ALyulina ETitov SKovalenko V(2023)Constructing Temporal Networks of OSS Programming Language Ecosystems2023 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)10.1109/SANER56733.2023.00067(663-667)Online publication date: Mar-2023
https://doi.org/10.1109/SANER56733.2023.00067
Kondo MSaito SIimura YChoi EMizuno OKamei YUbayashi N(2023)Towards Better Online Communication for Future Software Development in Industry2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC)10.1109/COMPSAC57700.2023.00250(1619-1624)Online publication date: Jun-2023
https://doi.org/10.1109/COMPSAC57700.2023.00250
Kuskova VZaytsev DKhvatsky GSokol AVorobeva MKamalov R(2023) Expanding the boundaries of interdisciplinary field: Contribution of Network Science journal to the development of network science Network Science10.1017/nws.2022.4111:1(65-97)Online publication date: 20-Jan-2023
https://doi.org/10.1017/nws.2022.41
Show More Cited By

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents