IEICE TRANSACTIONS on Information
Investigating and Projecting Population Structures in Open Source Software Projects: A Case Study of Projects in GitHub
Summary :
GitHub is a developers' social networking service that hosts a great number of open source software (OSS) projects. Although some of the hosted projects are growing and have many developers, most projects are organized by a few developers and face difficulties in terms of sustainability. OSS projects depend mainly on volunteer developers, and attracting and retaining these volunteers are major concerns of the project stakeholders. To investigate the population structures of OSS development communities in detail and conduct software analytics to obtain actionable information, we apply a demographic approach. Demography is the scientific study of population and seeks to identify the levels and trends in the size and components of a population. This paper presents a case study, investigating the characteristics of the population structures of OSS projects on GitHub, and shows population projections generated with the well-known cohort component method. We found that there are four types of population structures in OSS development communities in terms of experiences and contributions. In addition, we projected the future population accurately using a cohort component population projection method. This method predicts a population of the next period using a survival rate calculated from past population. To the best of our knowledge, this is the first study that applied demography to the field of OSS research. Our approach addressing OSS-related problems based on demography will bring new insights, since studying population is novel in OSS research. Understanding current and future structures of OSS projects can help practitioners to monitor a project, gain awareness of what is happening, manage risks, and evaluate past decisions.
- Publication
- IEICE TRANSACTIONS on Information Vol.E99-D No.5 pp.1304-1315
- Publication Date
- 2016/05/01
- Publicized
- 2016/02/05
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2015EDP7363
- Type of Manuscript
- PAPER
- Category
- Software Engineering
Authors
Saya ONOUE
Nara Institute of Science and Technology
Hideaki HATA
Nara Institute of Science and Technology
Akito MONDEN
Okayama University
Kenichi MATSUMOTO
Nara Institute of Science and Technology
Keyword
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Saya ONOUE, Hideaki HATA, Akito MONDEN, Kenichi MATSUMOTO, "Investigating and Projecting Population Structures in Open Source Software Projects: A Case Study of Projects in GitHub" in IEICE TRANSACTIONS on Information,
vol. E99-D, no. 5, pp. 1304-1315, May 2016, doi: 10.1587/transinf.2015EDP7363.
Abstract: GitHub is a developers' social networking service that hosts a great number of open source software (OSS) projects. Although some of the hosted projects are growing and have many developers, most projects are organized by a few developers and face difficulties in terms of sustainability. OSS projects depend mainly on volunteer developers, and attracting and retaining these volunteers are major concerns of the project stakeholders. To investigate the population structures of OSS development communities in detail and conduct software analytics to obtain actionable information, we apply a demographic approach. Demography is the scientific study of population and seeks to identify the levels and trends in the size and components of a population. This paper presents a case study, investigating the characteristics of the population structures of OSS projects on GitHub, and shows population projections generated with the well-known cohort component method. We found that there are four types of population structures in OSS development communities in terms of experiences and contributions. In addition, we projected the future population accurately using a cohort component population projection method. This method predicts a population of the next period using a survival rate calculated from past population. To the best of our knowledge, this is the first study that applied demography to the field of OSS research. Our approach addressing OSS-related problems based on demography will bring new insights, since studying population is novel in OSS research. Understanding current and future structures of OSS projects can help practitioners to monitor a project, gain awareness of what is happening, manage risks, and evaluate past decisions.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2015EDP7363/_p
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@ARTICLE{e99-d_5_1304,
author={Saya ONOUE, Hideaki HATA, Akito MONDEN, Kenichi MATSUMOTO, },
journal={IEICE TRANSACTIONS on Information},
title={Investigating and Projecting Population Structures in Open Source Software Projects: A Case Study of Projects in GitHub},
year={2016},
volume={E99-D},
number={5},
pages={1304-1315},
abstract={GitHub is a developers' social networking service that hosts a great number of open source software (OSS) projects. Although some of the hosted projects are growing and have many developers, most projects are organized by a few developers and face difficulties in terms of sustainability. OSS projects depend mainly on volunteer developers, and attracting and retaining these volunteers are major concerns of the project stakeholders. To investigate the population structures of OSS development communities in detail and conduct software analytics to obtain actionable information, we apply a demographic approach. Demography is the scientific study of population and seeks to identify the levels and trends in the size and components of a population. This paper presents a case study, investigating the characteristics of the population structures of OSS projects on GitHub, and shows population projections generated with the well-known cohort component method. We found that there are four types of population structures in OSS development communities in terms of experiences and contributions. In addition, we projected the future population accurately using a cohort component population projection method. This method predicts a population of the next period using a survival rate calculated from past population. To the best of our knowledge, this is the first study that applied demography to the field of OSS research. Our approach addressing OSS-related problems based on demography will bring new insights, since studying population is novel in OSS research. Understanding current and future structures of OSS projects can help practitioners to monitor a project, gain awareness of what is happening, manage risks, and evaluate past decisions.},
keywords={},
doi={10.1587/transinf.2015EDP7363},
ISSN={1745-1361},
month={May},}
Copy
TY - JOUR
TI - Investigating and Projecting Population Structures in Open Source Software Projects: A Case Study of Projects in GitHub
T2 - IEICE TRANSACTIONS on Information
SP - 1304
EP - 1315
AU - Saya ONOUE
AU - Hideaki HATA
AU - Akito MONDEN
AU - Kenichi MATSUMOTO
PY - 2016
DO - 10.1587/transinf.2015EDP7363
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E99-D
IS - 5
JA - IEICE TRANSACTIONS on Information
Y1 - May 2016
AB - GitHub is a developers' social networking service that hosts a great number of open source software (OSS) projects. Although some of the hosted projects are growing and have many developers, most projects are organized by a few developers and face difficulties in terms of sustainability. OSS projects depend mainly on volunteer developers, and attracting and retaining these volunteers are major concerns of the project stakeholders. To investigate the population structures of OSS development communities in detail and conduct software analytics to obtain actionable information, we apply a demographic approach. Demography is the scientific study of population and seeks to identify the levels and trends in the size and components of a population. This paper presents a case study, investigating the characteristics of the population structures of OSS projects on GitHub, and shows population projections generated with the well-known cohort component method. We found that there are four types of population structures in OSS development communities in terms of experiences and contributions. In addition, we projected the future population accurately using a cohort component population projection method. This method predicts a population of the next period using a survival rate calculated from past population. To the best of our knowledge, this is the first study that applied demography to the field of OSS research. Our approach addressing OSS-related problems based on demography will bring new insights, since studying population is novel in OSS research. Understanding current and future structures of OSS projects can help practitioners to monitor a project, gain awareness of what is happening, manage risks, and evaluate past decisions.
ER -
English
