Using SCL to Specify and Check Design Intent in Source Code
IEEE Transactions on Software Engineering
Experiments on Design Pattern Discovery
PROMISE '07 Proceedings of the Third International Workshop on Predictor Models in Software Engineering
A Rule-based Method to Match Software Patterns Against UML Models
Electronic Notes in Theoretical Computer Science (ENTCS)
Design pattern recovery through visual language parsing and source code analysis
Journal of Systems and Software
Design Patterns Identification Using Similarity Scoring Algorithm with Weighting Score Extension
Proceedings of the 2008 conference on Knowledge-Based Software Engineering: Proceedings of the Eighth Joint Conference on Knowledge-Based Software Engineering
Identification of design motifs with pattern matching algorithms
Information and Software Technology
Design pattern recovery based on annotations
Advances in Engineering Software
A matrix-based approach to recovering design patterns
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A fuzzy matching approach for design pattern mining
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Hybrid approaches for approximate reasoning
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Design patterns are important in software maintenance because they help in designing, in understanding, and in re-engineering programs. The identification of occurrences of a design pattern consists in identifying, in a program, classes which structure and organisation match-strictly or approximately-the structure and organisation of classes as suggested by the design pattern. We express the problem of design pattern identification with operations on finite sets of bit-vectors. We use the inherent parallelism of bit-wise operations to derive an efficient bit-vector algorithm that finds exact and approximate occurrences of design patterns in a program. We apply our algorithm on three smallto- medium size programs, JHotDraw, Juzzle, and QuickUML, with the Abstract Factory and Composite design patterns and compare its performance and results with two existing constraint-based approaches.