Towards a network ecology of software ecosystems: an analysis of two OSGi ecosystems

Klaus Marius Hansen, Konstantinos Manikas

6 Citations (Scopus)
621 Downloads (Pure)

Abstract

"Software ecosystems'' are gaining importance in commercial software development; the iPhone iOS and Salesforce.com ecosystems are examples of this. In contrast to traditional forms of software reuse, such as common platforms or product lines, software ecosystems have a heterogeneous set of actors sharing and collaborating over one or more technological platforms and business model(s) that serve the actors. However, little research has investigated the properties of actual software ecosystems.
In this paper, we present an exploratory study of software ecosystems using the formalizations and metrics of the "network ecology'' approach to the analysis of natural ecosystems. In doing so, we mine the Maven central Java repository and analyze two OSGi ecosystems: Apache Felix and Eclipse Equinox. In particular, we define the concept of an ecosystem ``neighborhood'', apply network ecology metrics to these neighborhoods (including a keystone index that identifies the importance of elements in the ecosystem), and compare the ecosystems.
Original languageEnglish
Title of host publicationThe 25th International Conference on Software Engineering & Knowledge Engineering SEKE 2013 : proceedings
Number of pages6
PublisherKnowledge Systems Institute Graduate School
Publication date2013
Pages326-331
ISBN (Print)978-1-891706-33-2
Publication statusPublished - 2013
EventThe 25th International Conference on Software Engineering and Knowledge Engineering (SEKE) - Hyatt Harborside at Logan Int’l Airport, Boston, United States
Duration: 27 Jun 201329 Jun 2013
Conference number: 25

Conference

ConferenceThe 25th International Conference on Software Engineering and Knowledge Engineering (SEKE)
Number25
LocationHyatt Harborside at Logan Int’l Airport,
Country/TerritoryUnited States
CityBoston
Period27/06/201329/06/2013
SeriesProceedings of the International Conference on Software Engineering and Knowledge Engineering
Volume2013
ISSN2325-9000

Keywords

  • Faculty of Science
  • software ecosystems
  • dependency structure
  • dependency graphs
  • network ecology

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