Accurate Design Pattern Detection Based on Idiomatic Implementation Matching in Java Language Context

Abstract

Design patterns (DPs) are widely accepted as solutions to recurring problems in software design. While numerous approaches and tools have been proposed for DP detection over the years, the neglect of language-specific mechanism that underlies the implementation idioms of DPs leads to false or missing DP instances since language-specific features are not captured and similar characteristics are not distinguished. However, there is still a lack of research that emphasizes the idiomatic implementation in the context of a specific language. A vital challenge is the representation of software systems and language mechanism. In this work, we propose a practical approach for DP detection from source code, which exploits idiomatic implementation in the context of Java language. DPs are formally defined under the blueprint of the layered knowledge graph (LKG) that models both language-independent concepts of DPs and Java language mechanism. Based on static analysis and inference techniques, the approach enables flexible search strategies integrating structural, behavioral and semantic aspects of DPs for the detection. Concerning emerging patterns and pattern variants, the core methodology supports pluggable pattern templates. A prototype implementation has been evaluated on five open source software systems and compared with three other approaches. The evaluation results show that the proposed approach improves the accuracy with higher precision (85.7%) and recall (93.8%). The runtime performance also supports its practical applicability.