Application of Intelligent Adaptive Neuro Fuzzy Method for Reusability of Component Based Software System

Jyoti Agarwal, M. Kumar, Mugdha Sharma, Deepak Verma, Richa Sharma
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Abstract

Component Based Software System (CBSS) provides an easy and efficient way to develop new software application with the help of existing software components of similar functionalities. It increases the reusability of software components and reduce the development time, cost and effort of software developers. To select the appropriate component, it become essential to assess the reusability of software components so that suitable component can be selected to reuse in another application. For assessing the reusability of CBSS, several factors are required to be considered. In this paper, four reusability sub-factors Interface Complexity (IC), Understandability (Un), Customizability (Co) and Reliability (Re) are used as input variables and reusability is assessed using Fuzzy Inference System (FIS) and Adaptive Neuro Fuzzy Inference System (ANFIS) approach because these two approaches are commonly used approach for assessing the quality factors. For experimental work, one case study has been done where rules are generated to assess reusability using four different reusability factors by taking feedback from researchers and academicians using online survey. Reusability was assessed for ten different values of input variables. Experiment shows that results obtained from ANFIS method were closer to the original values. Root Mean Square Error (RMSE) of FIS results was 6.05% which was further reduced by the application of ANFIS approach and finally 2.20% of RMSE was achieved. This research work will be helpful for software developers and researchers to assess the reusability of software components and they will be able to take corrective decision for choosing the appropriate component to be reused in new software applications, which will reduce their effort, time and cost of development
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智能自适应神经模糊方法在构件软件系统可重用性中的应用
基于组件的软件系统(Component Based Software System, CBSS)提供了一种简单有效的方法,可以利用已有的功能相似的软件组件开发新的软件应用程序。它增加了软件组件的可重用性,减少了软件开发人员的开发时间、成本和工作量。为了选择合适的组件,必须评估软件组件的可重用性,以便选择合适的组件以在另一个应用程序中重用。为了评估CBSS的可重用性,需要考虑几个因素。本文以界面复杂性(IC)、可理解性(Un)、可定制性(Co)和可靠性(Re)四个可重用子因素作为输入变量,采用模糊推理系统(FIS)和自适应神经模糊推理系统(ANFIS)方法对可重用性进行评估,因为这两种方法是评估质量因素的常用方法。对于实验工作,已经完成了一个案例研究,其中通过使用在线调查从研究人员和学者那里获得反馈,生成规则来使用四种不同的可重用性因素来评估可重用性。对十个不同的输入变量值进行了可重用性评估。实验表明,ANFIS方法得到的结果更接近于原始值。FIS结果的均方根误差(RMSE)为6.05%,通过应用ANFIS方法进一步减小,最终RMSE为2.20%。这项研究工作将有助于软件开发人员和研究人员评估软件组件的可重用性,他们将能够在新的软件应用程序中选择合适的组件来进行重用,从而减少他们的工作、时间和开发成本
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