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Quality Assessment of a Job Portal System Designed Using Bout Design Pattern

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Advanced Informatics for Computing Research (ICAICR 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 712))

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Abstract

Design Patterns provide solutions to problems that are notably prevailing in software engineering. The paper targets the importance of design patterns, but also aims on how design patterns uncover and fortify good object oriented principles. A design pattern called Bout was discovered to maintain sessions for a specific period of time. The design is a generic solution to implementing web portals by storing session data of clients on the server. The Bout pattern comprises the design principle of Singleton and Prototype patterns, thus guaranteeing a more reusable design. The Bout pattern is documented in the Gang of Four pattern description template. The Bout pattern was tested with a Job Portal system with additional patterns, Factory Method, Decorator and Observer, with significant improvement in object oriented design metrics. Metrics which showed a significant enhancement were Depth of Inheritance Tree and McCabe Cyclomatic Complexity. The reusability of black box components was analyzed for the Job Portal system which shows a momentous rise in the metrics. The source code was analyzed for modularity traits such as size, complexity, cohesion and coupling, which in turn determines the class quality, package quality and hence the modularity index. These quality metrics showed a symbolic upswing with Bout pattern and supporting patterns. Thus software designers can enhance the quality of distributed systems with the exercising of Bout pattern.

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Correspondence to G. Priyalakshmi .

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Priyalakshmi, G., Nadarajan, R., Washizaki, H., Sharma, S. (2017). Quality Assessment of a Job Portal System Designed Using Bout Design Pattern. In: Singh, D., Raman, B., Luhach, A., Lingras, P. (eds) Advanced Informatics for Computing Research. ICAICR 2017. Communications in Computer and Information Science, vol 712. Springer, Singapore. https://doi.org/10.1007/978-981-10-5780-9_18

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  • DOI: https://doi.org/10.1007/978-981-10-5780-9_18

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-5779-3

  • Online ISBN: 978-981-10-5780-9

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