Title :
Mining features from the object-oriented source code of software variants by combining lexical and structural similarity
Author :
Al-msie´deen, R. ; Seriai, A.-D. ; Huchard, M. ; Urtado, Christelle ; Vauttier, S.
Author_Institution :
LIRMM, Montpellier 2 Univ., Montpellier, France
Abstract :
Migrating software product variants which are deemed similar into a product line is a challenging task with main impact in software reengineering. To exploit existing software variants to build a software product line (SPL), the first step is to mine the feature model of this SPL which involves extracting common and optional features. Thus, we propose, in this paper, a new approach to mine features from the object-oriented source code of software variants by using lexical and structural similarity. To validate our approach, we applied it on ArgoUML, Health Watcher and Mobile Media software. The results of this evaluation showed that most of the features were identified1.
Keywords :
data mining; feature extraction; object-oriented programming; product development; software reusability; source coding; systems re-engineering; ArgoUML; Health Watcher; Mobile Media software; SPL; feature extraction; feature mining; lexical similarity; object-oriented source code; software product line; software product variant; software reengineering; structural similarity; Buildings; Couplings; Data mining; Large scale integration; Object oriented modeling; Shape; Software; Formal Concept Analysis; Latent Semantic Indexing; Software Product Line; code dependencies; feature mining; software product variants; structural similarity;
Conference_Titel :
Information Reuse and Integration (IRI), 2013 IEEE 14th International Conference on
Conference_Location :
San Francisco, CA
DOI :
10.1109/IRI.2013.6642522
