Overall, this procedure has the potential to convert the representation of system design and design pattern in ingenious shapes. A substring match technique is developed here to discover design patterns in the source code. Considering system code string as main string and design pattern string as a substring, the main string is further decomposed. Impact Analysis matrices of these UML diagrams are converted to string format. UML diagrams corresponding to codes are created using Visual Paradigm Enterprise. This paper introduces a new way to discover a design pattern based on an Impact Analysis matrix followed by substring match.

Additionally, pattern recovering methods often encounter problems dealing with space outburst for extensive systems. Of course, identifying a design pattern is not always a simple task.

The role of design pattern mining is a very significant strategy of re-engineering as with the help of detection one could easily understand complex systems. Finally, we present three different BGM implementations following the above design and analyze their pros and cons in terms of computing/storage overheads and implications to provenance consumers. In particular, we propose a set of requirements for BGM implementations and describe an event-based design of BGM that relies on the Aspect-Oriented Programming (AOP) paradigm to automatically weave the generated code into an application. In this paper, we present in detail UML2PROV’s approach to generating application code for capturing provenance values via the means of Bindings Generation Module (BGM). By so doing, UML2PROV frees application developers from manual instrumentation of provenance capturing while ensuring the quality of recorded provenance. It automates the generation of (1) templates for the provenance to be recorded and (2) the code to capture values required to instantiate those templates from an application at run time, both from the application’s UML diagrams. UML2PROV is a software-engineering methodology that facilitates the instrumentation of provenance recording in applications designed with UML diagrams. However, instrumenting applications, especially legacy ones, to track the provenance of their operations remains a significant technical hurdle, hindering the adoption of provenance technology. It is crucial to ascertaining the origin of data, validating their quality, auditing applications behaviours, and, ultimately, making them accountable. AbstractData provenance is a form of knowledge graph providing an account of what a system performs, describing the data involved, and the processes carried out over them.

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