Review article Q1
Software development analytics in practice: A systematic literature review
João Caldeira (Caldeira, J.); Fernando Brito e Abreu (Brito e Abreu, F.); Jorge S. Cardoso (Cardoso, J.); Rachel Vital Simões (Simões, R.); Toacy Cavalcante de Oliveira (Oliveira, T. C.); José Pereira dos Reis (Reis, J.);
Journal Title
Archives of Computational Methods in Engineering
Year (definitive publication)
2023
Language
English
Country
Germany
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Abstract
Software development analytics is a research area concerned with providing insights to improve product deliveries and processes. Many types of studies, data sources and mining methods have been used for that purpose. This systematic literature review aims at providing an aggregate view of the relevant studies on Software Development Analytics in the past decade, with an emphasis on its application in practical settings. Definition and execution of a search string upon several digital libraries, followed by a quality assessment criteria to identify the most relevant papers. On those, we extracted a set of characteristics (study type, data source, study perspective, development life-cycle activities covered, stakeholders, mining methods, and analytics scope) and classified their impact against a taxonomy. Source code repositories, exploratory case studies, and developers are the most common data sources, study types, and stakeholders, respectively. Testers also get moderate attention from researchers. Product managers’ concerns are being addressed frequently and project managers are also present but with less prevalence. Mining methods are rapidly evolving, as reflected in their identified long list. Descriptive statistics are the most usual method followed by correlation analysis. Being software development an important process in every organization, it was unexpected to find that process mining was present in only one study. Most contributions to the software development life cycle were given in the quality dimension. Time management and costs control were less prevalent. The analysis of security aspects is even more reduced, however, evidences suggest it is an increasing topic of concern. Risk management contributions are also scarce. There is a wide improvement margin for software development analytics in practice. For instance, mining and analyzing the activities performed by software developers in their actual workbench, i.e., in their IDEs. Together with mining developers’ behaviors, based on the evidences and trend, in a short term period we expect an increase in the volume of studies related with security and risks management.
Acknowledgements
This work was partially funded by the Portuguese Foundation for Science and Technology, under ISTAR’s projects UIDB/04466/2020 and UIDP/04466/2020.
Keywords
Software analytics,Software development analytics,Software development process mining,Software development life cycle,Systematic literature review
  • Computer and Information Sciences - Natural Sciences
  • Electrical Engineering, Electronic Engineering, Information Engineering - Engineering and Technology
Funding Records
Funding Reference Funding Entity
UIDB/04466/2020 Fundação para a Ciência e a Tecnologia
UIDP/04466/2020 Fundação para a Ciência e a Tecnologia
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