An Experimental Search-based Approach to Cohesion Metric Evaluation
- Submitting institution
-
Brunel University London
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 026-118854-7851
- Type
- D - Journal article
- DOI
-
10.1007/s10664-016-9427-7
- Title of journal
- Empirical Software Engineering: An International Journal
- Article number
- -
- First page
- 292
- Volume
- 22
- Issue
- 1
- ISSN
- 1382-3256
- Open access status
- Out of scope for open access requirements
- Month of publication
- April
- Year of publication
- 2016
- URL
-
https://link.springer.com/article/10.1007/s10664-016-9427-7
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
4
- Research group(s)
-
2 - Software, Systems & Security (SSS)
- Citation count
- 8
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Extending work that won Best Paper Award at the IEEE/ACM International Symposium on Empirical Software Engineering and Measurement 2012, (acceptance rate of 27.74%): “Experimental assessment of software metrics using automated refactoring.” Reflecting problems with current software metrics and reflecting on warnings to the empirical software community; we propose too many new metrics, each claiming to measure the same software concept, when actually, the overlap of what they do measure is relatively low. Cited by highly cited articles (e.g. Stol & Fitzgerald (2018), ACM Transactions on Software Engineering and Methodology (https://doi.org/10.1145/3241743), Chari & Agrawal (2018), Empirical Software Engineering (https://doi.org/10.1007/s10664-017-9506-4)
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
