Design pattern detection using a DSL-driven graph matching approach

Abstract

Knowledge about design pattern (DP) instances improves program comprehension and reengineering of object‐oriented systems. Effectively, it helps to discover developer design decisions and trade‐offs that often are not documented. This work describes an approach to automatically detect DPs in existing object‐oriented systems by tracing systems' source code components with the roles they play in the patterns. In the proposed approach, DPs are modeled based on their high‐level structural properties (e.g., inheritance, dependency, invocation, delegation, type nesting, and membership relationships) that are checked, by source code parsing, against the system structure and components. Moreover, the approach can also detect pattern variants, defined by overriding the pattern properties. This paper presents a description of the approach, provides a brief description of the supporting tool, and discusses the results from the experiments carried out to validate it. The approach was validated on seven systems of an open benchmark that contains systems of increasing sizes. For five additional systems, the results have been compared with the ones from a similar approach existing in the literature. The obtained results, the identified DP variants, and the effectiveness of the approach are thoroughly presented and discussed. Copyright © 2014 John Wiley & Sons, Ltd.

Towards Lightweight Detection of Design Patterns in Source Code

“…While SparT [17] was also evaluated, we excluded it from the analysis as the off-the-shelf implementation did not include specifications for creational and structural patterns. We excluded Tools that are unavailable for download (e.g., [19,20]) or those for which a core dependency is deprecated (e.g., [21,15]) from the comparison.…”

A Feature-Based Method for Detecting Design Patterns in Source Code

“…On the other hand, these methods cannot distinguish design patterns with similar structures [9,22]. For this reason, using behavioral analysis along with structural analysis increases the accuracy of the detection results [7,[30][31][32][33][34].…”

GEML: A grammar-based evolutionary machine learning approach for design-pattern detection

“…While the former reduces the search space by conveniently partitioning the project graph, the latter defines ordered sequences to guide the search in such an order that the most representative classes of the pattern are discovered first, filtering irrelevant classes at an early stage. DPF is a model-based graph matching tool for which a meta-model and a domain-specific language are proposed to specify the structural and behavioural relationships describing DPs (Bernardi et al, 2014). Another popular tool, PINOT (Shi and Olsson, 2006), uses graphs as an abstract representation of methods taking part in candidate DP implementations, from which control flow is statically analysed.…”