To the top

Page Manager: Webmaster
Last update: 9/11/2012 3:13 PM

Tell a friend about this page
Print version

Evolution of statistical … - University of Gothenburg, Sweden Till startsida
Sitemap
To content Read more about how we use cookies on gu.se

Evolution of statistical analysis in empirical software engineering research: Current state and steps forward

Journal article
Authors Francisco Gomes de Oliveira Neto
Richard Torkar
Robert Feldt
Lucas Gren
Carlo A. Furia
Ziwei Huang
Published in Journal of Systems and Software
Volume 156
Pages 246-267
ISSN 0164-1212
Publication year 2019
Published at Department of Computer Science and Engineering (GU)
Institutionen för data- och informationsteknik, Software Engineering (GU)
Pages 246-267
Language en
Links https://arxiv.org/pdf/1706.00933.pd...
https://doi.org/10.1016/j.jss.2019....
Keywords Empirical software engineering, Practical significance, Semi-automated literature review, Statistical methods
Subject categories Software Engineering

Abstract

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 analyze 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.

Page Manager: Webmaster|Last update: 9/11/2012
Share:

The University of Gothenburg uses cookies to provide you with the best possible user experience. By continuing on this website, you approve of our use of cookies.  What are cookies?