Discovering Community Patterns in Open-Source: A Systematic Approach and Its Evaluation

Damian A. Tamburri, Fabio Palomba, Alexander Serebrenik, Andy Zaidman

Research output: Contribution to journalArticleScientificpeer-review

7 Citations (Scopus)
43 Downloads (Pure)

Abstract

“There can be no vulnerability without risk; there can be no community without vulnerability; there can be no peace, and ultimately no life, without community.” - [M. Scott Peck]

The open-source phenomenon has reached the point in which it is virtually impossible to find large applications that do not rely on it. Such grand adoption may turn into a risk if the community regulatory aspects behind open-source work (e.g., contribution guidelines or release schemas) are left implicit and their effect untracked. We advocate the explicit study and automated support of such aspects and propose Yoshi (Y ielding O pen-S ource H ealth I nformation), a tool able to map open-source communities onto community patterns, sets of known organisational and social structure types and characteristics with measurable core attributes. This mapping is beneficial since it allows, for example, (a) further investigation of community health measuring established characteristics from organisations research, (b) reuse of pattern-specific best-practices from the same literature, and (c) diagnosis of organisational anti-patterns specific to open-source, if any. We evaluate the tool in a quantitative empirical study involving 25 open-source communities from GitHub, finding that the tool offers a valuable basis to monitor key community traits behind open-source development and may form an effective combination with web-portals such as OpenHub or Bitergia. We made the proposed tool open source and publicly available.
Original languageEnglish
Pages (from-to)1369-1417
Number of pages49
JournalEmpirical Software Engineering
Volume24
Issue number3
Early online date2018
DOIs
Publication statusPublished - 2019

Keywords

  • Community patterns
  • Community types
  • Empirical software engineering
  • Open source systems and community analysis

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