Software Analytics to Software Domains: A Systematic Literature Review

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ID: 282323
2015
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Abstract
Software Analytics (SA) is a new branch of big data analytics that has recently emerged (2011). What distinguishes SA from direct software analysis is that it links data mined from many different software artifacts to obtain valuable insights. These insights are useful for the decision-making process throughout the different phases of the software lifecycle. Since SA is currently a hot and promising topic, we have conducted a systematic literature review, presented in this paper, to identify gaps in knowledge and open research areas in SA. Because many researchers are still confused about the true potential of SA, we had to filter out available research papers to obtain the most SA-relevant work for our review. This filtration yielded 19 studies out of 135. We have based our systematic review on four main factors: which software practitioners SA targets, which domains are covered by SA, which artifacts are extracted by SA, and whether these artifacts are linked or not. The results of our review have shown that much of the available SA research only serves the needs of developers. Also, much of the available research uses only one artifact which, in turn, means fewer links between artifacts and fewer insights. This shows that the available SA research work is still embryonic leaving plenty of room for future research in the SA field.
Reference Key
ho2015software Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Tamer Mohamed Abdelltif; Luiz Fernando Capretz; Danny Ho
Journal arXiv
Year 2015
DOI
DOI not found
URL
http://arxiv.org/abs/1511.04109v1
Keywords
cs.se

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