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Evolution Prediction and Process Support of OSS Studies: A Systematic Mapping

  • Research Article - Computer Engineering and Computer Science
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Abstract

Open source software (OSS) evolution is an important research domain, and it is continuously getting more and more attention of researchers. A large number of studies are published on different aspects of OSS evolution. Different metrics, models, processes and tools are presented for predicting the evolution of OSS studies. These studies foster researchers for contemporary and comprehensive review of literature on OSS evolution prediction. We present a systematic mapping that covers two contexts of OSS evolution studies conducted so far, i.e., OSS evolution prediction and OSS evolution process support. We selected 98 primary studies from a large dataset that includes 56 conference, 35 journal and 7 workshop papers. The major focus of this systematic mapping is to study and analyze metrics, models, methods and tools used for OSS evolution prediction and evolution process support. We identified 20 different categories of metrics used by OSS evolution studies and results show that SLOC metric is largely used. We found 13 different models applied to different areas of evolution prediction and auto-regressive integrated moving average models are largely used by researchers. Furthermore, we report 13 different approaches/methods/tools in existing literature for the evolution process support that address different aspects of evolution.

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Correspondence to Ghulam Rasool.

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Rasool, G., Fazal, N. Evolution Prediction and Process Support of OSS Studies: A Systematic Mapping. Arab J Sci Eng 42, 3465–3502 (2017). https://doi.org/10.1007/s13369-017-2556-5

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