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Meta-analysis for families of experiments in software engineering: a systematic review and reproducibility and validity assessment

Meta-analysis for families of experiments in software engineering: a systematic review and reproducibility and validity assessment Thumbnail


Abstract

Context
Previous studies have raised concerns about the analysis and meta-analysis of crossover experiments and we were aware of several families of experiments that used crossover designs and meta-analysis.

Objective
To identify families of experiments that used meta-analysis, to investigate their methods for effect size construction and aggregation, and to assess the reproducibility and validity of their results.

Method
We performed a systematic review (SR) of papers reporting families of experiments in high quality software engineering journals, that attempted to apply meta-analysis. We attempted to reproduce the reported meta-analysis results using the descriptive statistics and also investigated the validity of the meta-analysis process.

Results
Out of 13 identified primary studies, we reproduced only five. Seven studies could not be reproduced. One study which was correctly analyzed could not be reproduced due to rounding errors. When we were unable to reproduce results, we provide revised meta-analysis results. To support reproducibility of analyses presented in our paper, it is complemented by the reproducer R package.

Conclusions
Meta-analysis is not well understood by software engineering researchers. To support novice researchers, we present recommendations for reporting and meta-analyzing families of experiments and a detailed example of how to analyze a family of 4-group crossover experiments.

Acceptance Date Jul 30, 2019
Publication Date Jul 30, 2019
Publicly Available Date Mar 28, 2024
Journal Empirical Software Engineering
Print ISSN 1382-3256
Publisher Springer Verlag
DOI https://doi.org/10.1007/s10664-019-09747-0
Keywords Evidence-based software engineering, Systematic review, Meta-analysis, Effect size, Families of experiments, Reproducible research
Publisher URL https://doi.org/10.1007/s10664-019-09747-0

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