文章基本信息

标题：Optimization of Component Based Software Engineering Model Using Neural Network
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作者：Gaurav Kumar ; Pradeep Kumar Bhatia
期刊名称：BVICAM's International Journal of Information Technology
印刷版ISSN：0973-5658
出版年度：2014
卷号：6
期号：2
语种：English
出版社：Bharati Vidyapeeth's Institute of Computer Applications and Management
摘要：The goal of Component Based Software Engineering (CBSE) is to deliver high quality, more reliable and more maintainable software systems in a shorter time and within limited budget by reusing and combining existing quality components. A high quality system can be achieved by using quality components, framework and integration process that plays a significant role. So, techniques and methods used for quality assurance and assessment of a component based system is different from those of the traditional software engineering methodology. In this paper, we are presenting a model for optimizing Chidamber and Kemerer (CK) metric values of component-based software. A deep analysis of a series of CK metrics of the software components design patterns is done and metric values are drawn from them. By using unsupervised neural network- Self Organizing Map, we have proposed a model that provides an optimized model for Software Component engineering model based on reusability that depends on CK metric values. Average, standard deviated and optimized values for the CK metric are compared and evaluated to show the optimized reusability of component based model.
关键词：Index Terms – Chidamber and Kemerer (CK) metric; Component Based Software Engineering (CBSE);Neural Network (NN);Self Organizing Map (SOM).