FEMOSAA: feature-guided and knee-driven multi-objective optimization for self-adaptive software
- Submitting institution
-
Loughborough University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1975
- Type
- D - Journal article
- DOI
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10.1145/3204459
- Title of journal
- ACM Transactions on Software Engineering and Methodology
- Article number
- 5
- First page
- 1
- Volume
- 27
- Issue
- 2
- ISSN
- 1049-331X
- Open access status
- Technical exception
- Month of publication
- June
- Year of publication
- 2018
- URL
-
-
- 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
-
3
- Research group(s)
-
-
- Citation count
- 7
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This output has impacted the state of the art by improving multi-objective software configuration with better quality and less time. It subsequently led to the development of an improved approach based on the concept of knee solution explored in the work by Prof. Lionel Briand (IEEE Fellow) from University of Luxembourg who has endorsed this research (https://tinyurl.com/wd8dgue).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -