Abstract
Software models are iteratively refined, restructured and evolved. the detection and analysis of changes applied between two versions of a model are one of the most important tasks during evolution and maintenance activities. in this paper, we propose an approach to detect high-level model changes in terms of refactoring. Our approach takes as input an exhaustive list of possible refactoring, the initial model and revised model, and generates as output a list of detected changes representing a sequence of refactoring. a solution is defined as a combination of refactoring that should maximize as much as possible the similarity between the expected revised model and the generated model after applying the refactoring sequence on the initial model. Due to the huge number of possible refactoring combinations, a heuristic method is used to explore the space of possible solutions. to this end, we used and adapted genetic algorithm as global heuristic search. the validation results on various versions of real-world models taken from an open-source project confirm the effectiveness of our approach. © 2012 IEEE.
Recommended Citation
A. Ben Fadhel et al., "Search-Based Detection of High-level Model Changes," IEEE International Conference on Software Maintenance, ICSM, pp. 212 - 221, article no. 6405274, Institute of Electrical and Electronics Engineers, Dec 2012.
The definitive version is available at https://doi.org/10.1109/ICSM.2012.6405274
Department(s)
Computer Science
Keywords and Phrases
model evolution; refactoring detection; search-based model-driven software engineering
International Standard Book Number (ISBN)
978-146732312-3
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
01 Dec 2012
