Open Source Software Evolution: A Systematic Literature Review (Part 1)

Open Source Software Evolution: A Systematic Literature Review (Part 1)

Kuljit Kaur Chahal (Department of Computer Science, Guru Nanak Dev University, Punjab, India) and Munish Saini (Department of Computer Science, Guru Nanak Dev University, Punjab, India)
Copyright: © 2016 |Pages: 27
DOI: 10.4018/IJOSSP.2016010101
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Abstract

Due to the dominance of Open Source Software (OSS) in IT and the IT enabled services industry, various stakeholders are keen to understand the OSS evolution process. Several studies have been conducted in the past in this regard. There are various techniques used in the past for understanding OSS evolution process from different perspectives. This paper reports a systematic literature review on the topic in order to understand its current state and to identify opportunities for future. This research identified 190 studies, selected against a set of questions, for discussion. It categorizes the research studies into nine categories. We report the review results in a set of two papers. This paper discusses the research results of the techniques used for OSS evolution analysis only i.e. one out of the nine categories. A subsequent paper carries discussion on the remaining categories. Based on the results obtained from the systematic review, there is evidence of shift in the metrics and methods for OSS evolution analysis over the period of time. OSS systems were found to grow at a super linear rate in the initial studies. But later studies revealed that branches of an OSS system grow at different rates. However, more number of studies should be carried out using a repeatable methodology in order to obtain well-formed and generalizable results.
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Review Methodology

The study follows a review protocol to carry out the review in a systematic manner so as to reduce the research bias. The review process included the following steps: 1) Defining the research questions, 2) Choosing a search strategy and study selection criteria, and 3) Data Extraction and Synthesis.

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