A Genetic Algorithm to Find the Adequate Granularity for Service Interfaces

Romano, Daniele; Pinzger, Martin

doi:10.1109/services.2014.91

Cited by 3 publications

(1 citation statement)

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“…We can distinguish two main categories: manual and fully-automated techniques. The manual approaches propose a set of refactorings that the user can select and execute to split an interface, extract an interface and merge two interfaces [8]. However, manual refactoring of the interface's design is a tedious task for developers that involve exploring the whole operations in the interface to find the best refactoring solution that improves the modularity of an interface.…”

Section: Problem Statementmentioning

confidence: 99%

Interactive Refactoring of Web Service Interfaces Using Computational Search

Wang

Kessentini

Ouni

2017

IEEE Trans. Serv. Comput.

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Successful Web services evolve through a process of continuous change due to several reasons such as improving the quality, fixing bugs and adding new features. However, this evolution process may weaken the design of the Web service's interface by aggregating many noncohesive and semantically unrelated operations. Thus, the service interface becomes unnecessarily complex for users to find relevant operations to be used by their services-based systems. In this paper, we propose an interactive recommendation approach, based on evolutionary algorithms, that dynamically adapts and suggests a possible remodularization of the Web services interface design to users/developers and takes their feedback into consideration. Our approach uses an interactive multi-criteria decision-making algorithm, based on interactive Non-dominated Sorting Genetic Algorithm (NSGA-II), to find a set of good design interface modularization solutions. These solutions provide a trade-off between improving several interface design quality metrics (e.g. coupling, cohesion, number of port types, and number of antipatterns) and fix Web services design antipatterns, maximizing the satisfaction of the interaction constraints learnt from the user feedback during the execution of the algorithm while minimizing the deviation from the initial design. We evaluated our approach on a set of 22 real world Web services, provided by Amazon and Yahoo. Statistical analysis of our experiments shows that our dynamic interactive Web services interface modularization approach performed significantly better than the state-of-the-art modularization techniques in terms of generating well-designed Web services interface for users.

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Section: Problem Statementmentioning

confidence: 99%