Recognizing bot activity in collaborative software development

Golzadeh, Mehdi; Mens, Tom; Decan, Alexandre; Constantinou, Eleni; Chidambaram, Natarajan

doi:10.1109/ms.2022.3178601

Request a copy

Article (Scientific journals)

Recognizing bot activity in collaborative software development

Golzadeh, Mehdi; Mens, Tom; Decan, Alexandre et al.

2022 • In IEEE Software, 39 (5), p. 56-61

Peer Reviewed verified by ORBi

Permalink
https://hdl.handle.net/20.500.12907/43038

DOI
10.1109/ms.2022.3178601

Files (1)Send to Details Statistics Bibliography Similar publications

Files

Full Text

IEEESW2022-Recognizing_bot_activity_in_collaborative_software_development.pdf

Publisher postprint (371.88 kB)

Request a copy

All documents in ORBi UMONS are protected by a user license.

Send to

RIS BibTex APA Chicago Permalink X Linkedin

Details

Keywords :

Software; software development; software automation; development bot; open source software

Abstract :

[en] Machine accounts (bots) are an integral part of collaborative software development. They automate many repetitive tasks on behalf of their human owners. Focusing on popular open-source projects on GitHub, we provide evidence that bots are regularly among the most active contributors, even though GitHub does not explicitly acknowledge the presence of several of these bots. This poses a problem for techniques that analyze human contributor activity. For example, tools for recognizing and giving credit to project members for their contributions may wrongly credit bots for their automated contributions. This calls for more accurate bot identification techniques.

Disciplines :

Computer science

Author, co-author :

Golzadeh, Mehdi ; Université de Mons - UMONS > Faculté des Sciences > Service de Génie Logiciel

Mens, Tom ; Université de Mons - UMONS > Faculté des Science > Service de Génie Logiciel ; Université de Mons - UMONS > Faculté des Sciences > Service de Génie Logiciel

Decan, Alexandre ; Université de Mons - UMONS > Faculté des Sciences > Service de Génie Logiciel

Constantinou, Eleni ; Université de Mons - UMONS ; Department of Mathematics and Computer Science, University of Technology Eindhoven, Eindhoven, 5600 North Brabant, Netherlands

Chidambaram, Natarajan ; Université de Mons - UMONS

Language :

English

Title :

Recognizing bot activity in collaborative software development

Publication date :

26 May 2022

Journal title :

IEEE Software

ISSN :

0740-7459

Publisher :

Institute of Electrical and Electronics Engineers (IEEE)

Special issue title :

Bots in Software Engineering

Volume :

Issue :

Pages :

56-61

Peer reviewed :

Peer Reviewed verified by ORBi

Additional URL :

https://ieeexplore.ieee.org/abstract/document/9782582

Research unit :

S852 - Génie Logiciel

Research institute :

R300 - Institut de Recherche en Technologies de l'Information et Sciences de l'Informatique
R150 - Institut de Recherche sur les Systèmes Complexes

Funders :

F.R.S.-FNRS - Fonds de la Recherche Scientifique [BE]
Service Public de Wallonie Recherche

Funding number :

2010235; O.0157.18F- RG43; T.0017.18

Funding text :

This research is supported by DigitalWallonia4.AI research project ARIAC (grant number 2010235), as well as by the Fonds de la Recherche Scientifique – FNRS under grants number O.0157.18F- RG43 (Excellence of Science project SECO-ASSIST) and T.0017.18.

Available on ORBi UMONS :

since 22 June 2022

Statistics

Number of views

10 (7 by UMONS)

Number of downloads

0 (0 by UMONS)

More statistics

Scopus citations^®

Scopus citations^®
without self-citations

OpenCitations

Bibliography

I.-H. Hann, J. Roberts, S. Slaughter, and R. Fielding, "Economic incentives for participating in open source software projects," in Proc. Int. Conf. Inf. Syst., 2002, p. 33
C. Hauff and G. Gousios, "Matching GitHub developer profiles to job advertisements," in Proc. IEEE/ACM 12th Working Conf. Mining Softw. Repositories, 2015, pp. 362-366, doi: 10.1109/MSR.2015.41
M. Wessel et al., "The power of bots: Characterizing and understanding bots in OSS projects," Proc. ACM Hum.-Comput. Interact., vol. 2, no. CSCW, pp. 1-19, 2018, doi: 10.1145/3274451
Z. Liao, X. Qi, Y. Zhang, X. Fan, and Y. Zhou, "How to evaluate the productivity of software ecosystem: A case study in GitHub," Sci. Program., vol. 2020, Aug. 2020, Art. no. 8814247, doi: 10.1155/2020/8814247
"SourceCred: A tool for communities to measure and reward value creation." GitHub. https://sourcecred.io (Accessed: Jun. 5, 2022)
E. Kalliamvakou, G. Gousios, D. Spinellis, and P. Nancy, "Measuring developer contribution from software repository data," in Proc. 4th Mediterranean Conf. Inf. Syst., 2009, pp. 129-132, doi: 10.1145/1370750.1370781
J. Cheng and J. L. C. Guo, "Activity- based analysis of open source software contributors: Roles and dynamics," in Proc. IEEE/ACM 12th Int. Workshop Cooperative Hum. Aspects Softw. Eng., 2019, pp. 11-18, doi: 10.1109/CHASE.2019.00011
J. L. Cánovas Izquierdo and J. Cabot, "On the analysis of non-coding roles in open source development," Empirical Softw. Eng., vol. 27, no. 1, 2021, Art. no. 18, doi: 10.1007/ s10664-021-10061-x
"Octohatrack." GitHub. https:// github.com/LABHR/octohatrack (Accessed: Jun. 5, 2022)
"Auto-add contributors." GitHub. https://github.com/marketplace/ actions/auto-add-contributors (Accessed: Jun. 5, 2022)
J.-G. Young, A. Casari, K. McLaughlin, M. Z. Trujillo, L. Hébert-Dufresne, and J. P. Bagrow, "Which contributions count? Analysis of attribution in open source," in Proc. IEEE/ACM 18th Int. Conf. Mining Softw. Repositories, 2021, pp. 242-253, doi: 10.1109/ MSR52588.2021.00036
M. Goeminne and T. Mens, "A comparison of identity merge algorithms for software repositories," Sci. Comput. Program., vol. 78, no. 8, pp. 971-986, 2013, doi: 10.1016/j.scico.2011.11.004
"Contributors-list." Giters. https:// giters.com/wow-actions/contributors -list (Accessed: Jun. 5, 2022)
M. Golzadeh, A. Decan, D. Legay, and T. Mens, "A ground-truth dataset and classification model for detecting bots in GitHub issue and PR comments," J. Syst. Softw., vol. 175, p. 110,911, May 2021, doi: 10.1016/j. jss.2021.110911
T. Dey et al., "Detecting and characterizing bots that commit code," in Proc. ACM 17th Int. Conf. Mining Softw. Repositories, 2020, pp. 209-219, doi: 10.1145/3379597.3387478
"BoDeGHa." GitHub. https:// github.com/mehdigolzadeh/BoDe- GHa (Accessed: Jun. 5, 2022)
"BoDeGiC." GitHub. https://github. com/mehdigolzadeh/BoDeGiC (Accessed: Jun. 5, 2022)
N. Cassee, C. Kitsanelis, E. Constantinou, and A. Serebrenik, "Human, bot or both? A study on the capabilities of classification models on mixed accounts," in Proc. IEEE Int. Conf. Softw. Maintenance Evol., 2021, pp. 654-658, doi: 10.1109/ICSME52107.2021.00075
M. Golzadeh, A. Decan, and N. Chidambaram, "On the accuracy of bot detection techniques," in Proc. 4th Int. Workshop Bots Softw. Eng. (BotSE), Pittsburgh, PA, USA, May 9, 2022. [Online]. Available: https:// doi.org/10.1145/3528228.3528406
"This repo is for Vue 2." GitHub. https://github.com/vuejs/vue (Accessed: Jun. 5, 2022)
"The servo parallel browser engine project." GitHub. https://github.com/ servo/servo (Accessed: Jun. 5, 2022)