Identification of design motifs with pattern matching algorithms

Kaczor, Olivier; Guéhéneuc, Yann‐Gaël; Hamel, Sylvie

doi:10.1016/j.infsof.2009.08.006

Cited by 13 publications

(6 citation statements)

References 32 publications

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“…Incomplete criteria may prevent finding the correct instances or result in finding false instances. The criteria can be divided into two categories, namely, positive and negative criteria (Guéhéneuc & Antoniol, 2008;De Lucia et al, 2009;Rasool, 2011;Philippow et al, 2004;Olivier et al, 2010;Philippow et al, 2003).…”

Section: Signatures Used To Detect Patternsmentioning

confidence: 99%

A new method for detecting various variants of GoF design patterns using conceptual signatures

et al. 2021

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Software design patterns are well-known solutions for solving commonly occurring problems in software design. Detecting design patterns used in the code can help to understand the structure and behavior of the software, evaluate the quality of the software, and trace important design decisions. To develop and maintain a software system, we need sufficient knowledge of design decisions and software implementation processes. However, the acquisition of knowledge related to design patterns used in complex software systems is a challenging, time-consuming, and costly task. Therefore, using a suitable method to detect the design patterns used in the code reduces software development and maintenance costs. In this paper, we proposed a new method based on conceptual signatures to improve the accuracy of design pattern detection. So we used the conceptual signatures based on the purpose of patterns to detect the patterns' instances that conform to the standard structure of patterns, and cover more instances of patterns' variants and implementation versions of the patterns and improve the accuracy of pattern detection. The proposed method is a specific process in two main phases. In the first phase, the conceptual signature and detection formula for each pattern is determined manually. Then in the second phase, each pattern in the code is detected in a semi-automatic process using the conceptual signature and pattern detection formula. To implement the proposed method, we focused on GoF design patterns and their variants. We evaluated the accuracy of our proposed method on five open-source projects, namely, Junit v3.7, JHotDraw v5.1, QuickUML 2001, JRefactory v2.6.24, and MapperXML v1.9.7. Also, we performed our experiments on a set of source codes containing the instances of GoF design patterns' variants for a comprehensive and fair evaluation. The evaluation results indicate that the proposed method has improved the accuracy of design pattern detection in the code.

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Section: Signatures Used To Detect Patternsmentioning

confidence: 99%

A new method for detecting various variants of GoF design patterns using conceptual signatures

et al. 2021

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“…Most of these approaches adopt what might be called a top-down strategy [47] to using design patterns whereby the designer first selects a design pattern to instantiate, then specifies the instantiation parameters (e.g., application-specific class names) that are used by a Computer-aided software engineering (CASE) tool to generate the instance of the pattern, as in [11][12][13][14][15][16][17][18][19]. By contrast, the bottom-up strategy consists of identifying perfect instances (hits) or imperfect ones (near hits) of specific design patterns, as in [10,20,48]. A mixed strategy consists of completing a set of elements that partially match the structure of a pattern by adding new entities and associations so that the resulting set reproduces the full structure of the pattern, as in [17].…”

Section: Representing Design Patternsmentioning

confidence: 99%

“…However, existing work has, for the most part, focused on a subset of these tasks. Indeed, depending on their goals, the approaches that we have studied have focused on either representing structures of the solutions proposed by design patterns (e.g., [10][11][12][13][14][15][16][17][18][19][20]), either representing the transformation embodied in pattern's application (e.g., [21][22][23]). The task of finding opportunities for applying patterns in existing models has not been tackled by these approaches, which are further discussed in the related work section.…”

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confidence: 99%

Understanding design patterns — what is the problem?

Boussaidi

Mili

2011

Softw Pract Exp

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SUMMARY Design patterns codify proven solutions to recurring design problems. Their proper use within a development context requires that: (i) we understand them; (ii) we ascertain their applicability or relevance to the design problem at hand; and (iii) we apply them faithfully to the problem at hand. We argue that an explicit representation of the design problem solved by a design pattern is key to supporting the three tasks in an integrated fashion. We propose a model‐driven representation of design patterns consisting of triples < MP, MS, T > where MP is a model of the problem solved by the pattern, MS is a model of the solution proposed by the pattern, and T is a model transformation of an instance of the problem into an instance of the solution. Given an object‐oriented design model, we look for model fragments that match MP (call them instances of MP), and when one is found, we apply the transformation T yielding an instance of MS. Easier said than done. Experimentation with an Eclipse Modeling Framework‐based implementation of our approach applied to a number of open‐source software application's raised fundamental questions about: (i) the nature of design patterns in general, and the ones that lend themselves to our approach, and (ii) our understanding and codification of seemingly simple design patterns. In this paper, we present the principles behind our approach, report on the results of applying the approach to the Gang of Four (GoF) design patterns, and discuss the representability of design problems solved by these patterns. Copyright © 2011 John Wiley & Sons, Ltd.

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“…DeMIMA [31,41] is an approach to semi-automatically identify micro-architectures that are similar to design patterns in source code and to ensure the traceability of these micro-architectures between implementation and design. DeMIMA consists of three layers: two layers to recover an abstract model of the source code, including binary class relationships, and a third layer to identify design patterns in the abstract model.…”

Section: Design Pattern Detectionmentioning

confidence: 99%