article

A comparison of identity merge algorithms for software repositories

Authors:

Mathieu Goeminne,

Tom MensAuthors Info & Claims

Science of Computer Programming, Volume 78, Issue 8

Pages 971 - 986

https://doi.org/10.1016/j.scico.2011.11.004

Published: 01 August 2013 Publication History

Abstract

Software repository mining research extracts and analyses data originating from multiple software repositories to understand the historical development of software systems, and to propose better ways to evolve such systems in the future. Of particular interest is the study of the activities and interactions between the persons involved in the software development process. The main challenge with such studies lies in the ability to determine the identities (e.g., logins or e-mail accounts) in software repositories that represent the same physical person. To achieve this, different identity merge algorithms have been proposed in the past. This article provides an objective comparison of identity merge algorithms, including some improvements over existing algorithms. The results are validated on a selection of large ongoing open source software projects.

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Vidoni M(2022)A systematic process for Mining Software RepositoriesInformation and Software Technology10.1016/j.infsof.2021.106791144:COnline publication date: 9-May-2022
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cover image Science of Computer Programming

Science of Computer Programming Volume 78, Issue 8

August, 2013

236 pages

ISSN:0167-6423

Issue’s Table of Contents

Copyright © Elsevier B.V. © 2011.

Publisher

Elsevier North-Holland, Inc.

United States

Publication History

Published: 01 August 2013

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Cited By

Foundjem AEghan EAdams B(2023)A Grounded Theory of Cross-Community SECOs: Feedback Diversity Versus SynchronizationIEEE Transactions on Software Engineering10.1109/TSE.2023.331387549:10(4731-4750)Online publication date: 1-Oct-2023
https://dl.acm.org/doi/10.1109/TSE.2023.3313875
Golzadeh MMens TDecan AConstantinou EChidambaram N(2022)Recognizing Bot Activity in Collaborative Software DevelopmentIEEE Software10.1109/MS.2022.317860139:5(56-61)Online publication date: 1-Sep-2022
https://dl.acm.org/doi/10.1109/MS.2022.3178601
Vidoni M(2022)A systematic process for Mining Software RepositoriesInformation and Software Technology10.1016/j.infsof.2021.106791144:COnline publication date: 9-May-2022
https://dl.acm.org/doi/10.1016/j.infsof.2021.106791
Foundjem AConstantinou EMens TAdams B(2022)A mixed-methods analysis of micro-collaborative coding practices in OpenStackEmpirical Software Engineering10.1007/s10664-022-10167-w27:5Online publication date: 18-Jun-2022
https://dl.acm.org/doi/10.1007/s10664-022-10167-w
Golzadeh MLegay DDecan AMens T(2020)Bot or not?Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops10.1145/3387940.3391503(31-35)Online publication date: 27-Jun-2020
https://dl.acm.org/doi/10.1145/3387940.3391503
Zhang YZhou MStol KWu JJin ZRothermel GBae D(2020)How do companies collaborate in open source ecosystems?Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering10.1145/3377811.3380376(1196-1208)Online publication date: 27-Jun-2020
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Zhu JWei JStorey MAdams BHaiduc S(2019)An empirical study of multiple names and email addresses in OSS version control repositoriesProceedings of the 16th International Conference on Mining Software Repositories10.1109/MSR.2019.00068(409-420)Online publication date: 26-May-2019
https://dl.acm.org/doi/10.1109/MSR.2019.00068
Moreno DDueñas SCosentino VFernandez MZerouali ARobles GGonzalez-Barahona JMussbacher GAtlee JBultan T(2019)SortingHatProceedings of the 41st International Conference on Software Engineering: Companion Proceedings10.1109/ICSE-Companion.2019.00036(51-54)Online publication date: 25-May-2019
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Zhang YTan XZhou MJin ZChaudron MCrnkovic IChechik MHarman M(2018)Companies' domination in FLOSS developmentProceedings of the 40th International Conference on Software Engineering: Companion Proceeedings10.1145/3183440.3195047(440-441)Online publication date: 27-May-2018
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Han XWang LCui CMa JZhang S(2017)Linking Multiple Online Identities in Criminal Investigations: A Spectral Co-Clustering FrameworkIEEE Transactions on Information Forensics and Security10.1109/TIFS.2017.270490612:9(2242-2255)Online publication date: 1-Sep-2017
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