Identifying traits with formal concept analysis

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Identifying traits with formal concept analysis

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Automated Software Engineering archive
Proceedings of the 20th IEEE/ACM international Conference on Automated software engineering table of contents

Long Beach, CA, USA

SESSION: Program understanding table of contents

Pages: 66 - 75

Year of Publication: 2005

ISBN:1-59593-993-4

Authors

Adrian Lienhard	University of Bern (Switzerland)
Stéphane Ducasse	University of Bern (Switzerland) and Université de Savoie (France)
Gabriela Arévalo	University of Bern (Switzerland)

Sponsors

ACM: Association for Computing Machinery
SIGART: ACM Special Interest Group on Artificial Intelligence
SIGSOFT: ACM Special Interest Group on Software Engineering

Publisher

ACM New York, NY, USA

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Downloads (6 Weeks): 5, Downloads (12 Months): 51, Citation Count: 1

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ABSTRACT

Traits are basically mixins or interfaces but with method bodies. In languages that support traits, classes are composed out of traits. There are two main advantages with traits. Firstly, decomposing existing classes into traits from which they can be recomposed improves the factoring of hierarchies. Secondly it increases the library reuse potential by providing more reusable traits. Identifying traits and decomposing class hierarchies into traits is therefore an important and challenging task to facilitate maintainability and evolution. In this paper we present how we use Formal Concept Analysis to identify traits in inheritance hierarchies. Our approach is two-staged: first we identify within a hierarchy maximal groups of methods that have a set of classes in common, second we cluster cohesive groups of methods based on method invocations as potential traits. We applied our approach on two significant hierarchies and compare our results with the manual refactorization of the same code which was done by the authors of traits.

REFERENCES

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