The validation of design pattern implementations to identify pattern violations has gained more relevance as part of re-engineering processes in order to preserve, extend, reuse software projects in rapid development environments. If design pattern implementations do not conform to their definitions, they are considered a violation. Software aging and the lack of experience of developers are the origins of design pattern violations. It is important to check the correctness of the design pattern implementations against some predefined characteristics to detect and to correct violations, thus, to reduce costs. Currently, several tools have been developed to detect design pattern instances, but there has been little work done in creating an automated tool to identify and validate design pattern violations. In this paper we propose a Design Pattern Violations Identification and Assessment (DPVIA) tool, which has the ability to identify software design pattern violations and report the conformance score of pattern instance implementations towards a set of predefined characteristics for any design pattern definition whether Gang of Four (GoF) design patterns by [1]; or custom pattern by software developer. Moreover, we have verified the validity of the proposed tool using two evaluation experiments and the results were manually checked. Finally, in order to assess the functionality of the proposed tool, it is evaluated with a data-set containing 5,679,964 Lines of Code among 28,669 in 15 open-source projects, with a large and small size of open-source projects that extensively and systematically employing design patterns, to determine design pattern violations and suggest refactoring solutions, thus keeping costs of software evolution. The results can be used by software architects to develop best practices while using design patterns.
As the focus of this work lies on detect design pattern violations and their evaluation, we reviewed the early work of Izurieta and Bieman @cite_19 on type of design pattern violations called decay. Decay can involve the design patterns used to structure a system where classes that participate in design pattern realizations accumulate non pattern related code. Izurieta and Bieman investigated the evolution of design pattern implementations to comprehend how patterns decay and examined the extent to which software designs actually decay by studying the aging of design patterns in three successful object-oriented systems that include the entire code base of JRefactory, and added two additional open source systems ArgoUML and eXist. The results indicate that pattern grime (non-pattern-related code) that builds up around design patterns is mostly due to increases in coupling and it is the main factor for the decay of software design patterns.
@cite_19
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A common belief is that software designs decay as systems evolve. This research examines the extent to which software designs actually decay by studying the aging of design patterns in successful object oriented systems. Aging of design patterns is measured using various types of decay indices developed for this research. Decay indices track the internal structural changes of a design pattern realization and the code that surrounds the realization. Hypotheses for each kind of decay are tested. We found that the original design pattern functionality remains, and pattern decay is due to the "grime ", non-pattern code, that grows around the pattern realization.