Type inference in flexible model-driven engineering using classification algorithms
- Submitting institution
-
University of York
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 66866729
- Type
- D - Journal article
- DOI
-
10.1007/s10270-018-0658-5
- Title of journal
- International Journal on Software & Systems Modelling
- Article number
- -
- First page
- 345
- Volume
- 18
- Issue
- 1
- ISSN
- 1619-1366
- Open access status
- Compliant
- Month of publication
- January
- 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
-
4
- Research group(s)
-
-
- Citation count
- 1
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- First method combining classification algorithms with modelling for inferring metamodels. Demonstrates accuracy through quantitative experiment. Builds on one conference and three workshop papers published in 2015-16. Funded by an industrial collaboration with Digital Lightspeed Solutions, and part-funded by EPSRC LSCITS. Led to one EngD thesis (Zolotas). The method has been implemented in the widely used open-source Epsilon project of the Eclipse Foundation (http://www.eclipse.org/epsilon).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -