Overcoming metric diversity in meta-analysis for software engineering: proposed approach and a case study on its usage on the effects of software reuse
Abstract
This work addresses the problem of metric diversity in meta-analysis for Software Engineering by clustering studies using input-output tables and by vote-counting. Diversity arises when researchers, measuring same phenomena, use different, and typically "incomparable" metrics making impossible a direct analysis of the effects and their sizes. Additionally, this work discusses an application of proposed approach to the case of Software Reuse.
BibTeX
@inproceedings{Daniakin:FSE21,
author = {Kirill Daniakin},
title = {Overcoming metric diversity in meta-analysis for software engineering: proposed approach and a case study on its usage on the effects of software reuse},
booktitle = {{ESEC/SIGSOFT} {FSE}},
pages = {1677--1679},
publisher = {{ACM}},
year = {2021},
}