Tools for the Study of the Usual Data Sources found in Libre Software Projects

Robles, Gregório; González-Barahona, Jesús M.; Izquierdo-Cortázar, Daniel; Herraiz, Israel

doi:10.4018/jossp.2009010102

Cited by 46 publications

(11 citation statements)

References 29 publications

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“…Robles et al [44] describe the problems that can be found when retrieving and preparing for OSS data analysis and present the tools that support data retrieval for OSS evolution analysis: source code, source code management systems, mailing lists, and bug tracking systems. In accordance with this study, Bachmann and Bernstein [5] address the quality of data sources and provides insights into the influencing factors to the quality and characteristics of software process data gathered from bug tracking database and version control system log files.…”

Section: Evolution Process Supportmentioning

confidence: 99%

A Systematic Review of Studies of Open Source Software Evolution

Breivold¹,

Chauhan

Babar

2010

2010 Asia Pacific Software Engineering Conference

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Software evolution relates to how software systems evolve over time. With the emergence of the open source paradigm, researchers are provided with a wealth of data for open source software evolution analysis. In this paper, we present a systematic review of open source software (OSS) evolution. The objective of this review is to obtain an overview of the existing studies in open source software evolution, with the intention of achieving an understanding of how software evolvability (i.e., a software system's ability to easily accommodate changes) is addressed during development and evolution of open source software. The primary studies for this review were identified based on a pre-defined search strategy and a multi-step selection process. Based on their research topics, we have identified four main categories of themes: software trends and patterns, evolution process support, evolvability characteristics addressed in OSS evolution, and examining OSS at software architecture level. A comprehensive overview and synthesis of these categories and related studies is presented as well.

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Section: Evolution Process Supportmentioning

confidence: 99%

A Systematic Review of Studies of Open Source Software Evolution

Breivold¹,

Chauhan

Babar

2010

2010 Asia Pacific Software Engineering Conference

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“…Retrieval of mailing list information. We used MLStats [7] to retrieve mail messages from the development mailing list 1 , and store them in a MySQL database.…”

Section: Initial Observationsmentioning

confidence: 99%

“…Retrieval of Git information. We used CVSAnalY [7] to retrieve information from the main Xen git repository 2 , and store it in a MySQL database as well.…”

Section: Initial Observationsmentioning

confidence: 99%

Characterization of the Xen project code review process

Izquierdo-Cortázar¹,

Kurth

González-Barahona

et al. 2016

Proceedings of the 13th International Conference on Mining Software Repositories

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Many software development projects have introduced mandatory code review for every change to the code. This means that the project needs to devote a significant effort to review all proposed changes, and that their merging into the code base may get considerably delayed. Therefore, all those projects need to understand how code review is working, and the delays it is causing in time to merge. This is the case in the Xen project, which performs peer review using mailing lists. During the first half of 2015, some people in the project observed a large and sustained increase in the number of messages related to code review, which had started some years before. This observation led to concerns on whether the code review process was having some trouble, and too large an impact on the overall development process.Those concerns were addressed with a quantitative study, which is presented in this paper. Based on the information in code review messages, some metrics were defined to infer delays imposed by code review. The study produced quantitative data suitable for informed discussion, which the project is using to understand its code review process, and to take decisions to improve it. keywords data mining, software process, code review *

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“…To study the communication across several releases, we retrieved data for 32 months spanning from January 2009 to August 2011. We used MLStats [64] to split into threads the mailing list archive data sets. We chose this period because it comprises 5 release cycles, including the transition between two major releases-from the series 2.x to 3.x.…”

Section: Data Collection and Cleaningmentioning

confidence: 99%

Herding cats in a FOSS ecosystem: a tale of communication and coordination for release management

Poo-Caamaño

Knauss

Singer

et al. 2017

J Internet Serv Appl

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Release management in large-scale software development projects requires significant communication and coordination. It is particularly challenging in Free and Open Source Software (FOSS) ecosystems, in which hundreds of loosely connected developers and their projects are coordinated to release software to a schedule. To better understand this process and its challenges, we analyzed over two and half years of communication in the GNOME ecosystem and studied developers' interactions. Through a case study, we cataloged communication channels, determined the main channel from which we categorized high level communication and coordination activities spanning five releases, and triangulated our results by interviewing ten key developers. We found that a release schedule, influence (instead of direct control), and diversity are the main factors that positively impact the release process in the GNOME ecosystem. We report a set of lessons learned that encapsulates our understanding of how the Release Management process function in a FOSS ecosystem, we learned that: (1) ensure that the release team follows the main communication channels used by developers, (2) provide a common place for coordination for an ecosystem, (3) consider including both good technical and social skills in a release team, (4) aim for a diverse release team, (5) based on lack of power, lobbying and consensus based management must be followed, (6) help the release team in the coordination process with a well defined schedule, and (7) release team work is different from regular software work. Our results can help organizations build better large-scale teams and show that research focused on individual projects might miss important parts of the picture.

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Tools for the Study of the Usual Data Sources found in Libre Software Projects

Cited by 46 publications

References 29 publications

A Systematic Review of Studies of Open Source Software Evolution

A Systematic Review of Studies of Open Source Software Evolution

Characterization of the Xen project code review process

Herding cats in a FOSS ecosystem: a tale of communication and coordination for release management

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