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- Tags
- Kim Mens, Angela Lozano, Structural Source Code Regularities, Source Code Mining, Software Restructuring, Software Evolution, Software Maintenance, Software Development, Tools, Source Code Recommendation, Software Comprehension, Empirical Software Engineering, Metrics, Bad Smells, Source Code Analysis
- Summary
- This collaborative project between RELEASeD and Prof. Gabriela Arevalo at the Centro de Altos Estudios en Tecnología Informática – Universidad Abierta Interamericana, will study the appropriateness of metrics and thresholds to identify structural degradation in source code. Our labs have used previously Formal Concept Analysis to detect source code regularities as well as their violations. The goal of the project is to use this approach to identify key structural metrics to detect certain bad smells. The metrics will be compared against other approaches used to reverse engineer source code based on structural relations. The analysis would be done by cataloging metrics and bad smells found in Open Source projects (and if possible in commercial applications), evaluating the suitability of different metrics and their thresholds to express structural degradation, and automatically detecting the best combination of metrics to detect bad smells.
- Total budget
- The project finances a total of four trips of two week during 2012 and 2013.
- Duration
- September 2011 - August 2013
- Contributor(s)
- Kim Mens, Angela Lozano and Prof. Gabriela Arevalo
- Website
- http://released.info.ucl.ac.be/Projects/FNRS-IdentifyingFingerprintsOfStructuralCodeDeficienciesInObjectOrientedSoftware
Tags:
Kim Mens,
Angela Lozano,
Structural Source Code Regularities,
Source Code Mining,
Software Restructuring,
Software Evolution,
Software Maintenance,
Software Development,
Tools,
Source Code Recommendation,
Software Comprehension,
Empirical Software Engineering,
Metrics,
Bad Smells,
Source Code Analysis