Evolution of statistical analysis in empirical software engineering research: Current state and steps forward
Artikel i vetenskaplig tidskrift, 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

Författare

Francisco Gomes

Chalmers, Data- och informationsteknik, Software Engineering, Software Engineering for Testing, Requirements, Innovation and Psychology

Göteborgs universitet

Richard Torkar

Chalmers, Data- och informationsteknik, Software Engineering, Software Engineering for Testing, Requirements, Innovation and Psychology

Göteborgs universitet

Robert Feldt

Göteborgs universitet

Chalmers, Data- och informationsteknik, Software Engineering, Software Engineering for Cyber Psysical Systems

Blekinge Tekniska Högskola, BTH

Lucas Gren

Chalmers, Data- och informationsteknik

Göteborgs universitet

Carlo A Furia

Universita della Svizzera italiana

Zhongjie Huang

Göteborgs universitet

Chalmers, Mekanik och maritima vetenskaper, Strömningslära

Journal of Systems and Software

0164-1212 (ISSN)

Vol. 156 246-267

Ämneskategorier

Annan data- och informationsvetenskap

Programvaruteknik

Systemvetenskap, informationssystem och informatik med samhällsvetenskaplig inriktning

DOI

10.1016/j.jss.2019.07.002

Mer information

Senast uppdaterat

2019-08-22