Evolution of statistical analysis in empirical software engineering research: Current state and steps forward
Journal article, 2019

© 2019 Elsevier Inc. Software engineering research is evolving and papers are increasingly based on empirical data from a multitude of sources, using statistical tests to determine if and to what degree empirical evidence supports their hypotheses. To investigate the practices and trends of statistical analysis in empirical software engineering (ESE), this paper presents a review of a large pool of papers from top-ranked software engineering journals. First, we manually reviewed 161 papers and in the second phase of our method, we conducted a more extensive semi-automatic classification of papers spanning the years 2001–2015 and 5196 papers. Results from both review steps was used to: i) identify and analyse the predominant practices in ESE (e.g., using t-test or ANOVA), as well as relevant trends in usage of specific statistical methods (e.g., nonparametric tests and effect size measures) and, ii) develop a conceptual model for a statistical analysis workflow with suggestions on how to apply different statistical methods as well as guidelines to avoid pitfalls. Lastly, we confirm existing claims that current ESE practices lack a standard to report practical significance of results. We illustrate how practical significance can be discussed in terms of both the statistical analysis and in the practitioner's context.

Empirical software engineering

Practical significance

Statistical methods

Semi-automated literature review

Author

Francisco Gomes

Chalmers, Computer Science and Engineering (Chalmers), Software Engineering (Chalmers), Software Engineering for Testing, Requirements, Innovation and Psychology

University of Gothenburg

Richard Torkar

Chalmers, Computer Science and Engineering (Chalmers), Software Engineering (Chalmers), Software Engineering for Testing, Requirements, Innovation and Psychology

University of Gothenburg

Robert Feldt

University of Gothenburg

Chalmers, Computer Science and Engineering (Chalmers), Software Engineering (Chalmers), Software Engineering for Cyber Psysical Systems

Blekinge Tekniska Högskola, BTH

Lucas Gren

Chalmers, Computer Science and Engineering (Chalmers)

University of Gothenburg

Carlo A Furia

Universita della Svizzera italiana

Zhongjie Huang

University of Gothenburg

Chalmers, Mechanics and Maritime Sciences, Fluid Dynamics

Journal of Systems and Software

0164-1212 (ISSN)

Vol. 156 246-267

Subject Categories

Other Computer and Information Science

Software Engineering

Information Systemes, Social aspects

DOI

10.1016/j.jss.2019.07.002

More information

Latest update

8/22/2019