Jagdeep Kaur ¹, Pradeep Tomar ²

Affiliations
1 CSE and IT Department.,TheNorthCap University, Gurgaon - 122017, Haryana, IN
2 Department of Computer Science and Engineering, School of ICT, Gautam Buddha University, Greater Noida - 201038, Uttar Pardesh, IN

Abstract

Objectives:To search the components that provides desired functionality, from the finite set of component set by the use of software component selection process. The selection process helps in choosing the optimal set of components from the third party repository. Methods/Statistical Analysis:In order to select the optimal set of component having multiple attributes, clustering is found to most suitable technique as revealed in the literature. This paper presents the validation of clustering based algorithms used for software component selection. It mainly covers the fuzzy-c means clustering and subtractive clustering. It also includes the earlier software component selection techniques proposed by the authors, hybrid XOR based clustering technique and fuzzy relation based fuzzy clustering. Findings:The Fuzzy c-means technique requires the need of mentioning the number of clusters centers in advanceand the radii of the cluster in case of Subtractive clustering are required. The disadvantage of Hybrid XOR based clustering is its dependency on subjective judgment of the developer. The FREFCOSCO algorithm has eliminated the usage of similarity index. It is able to deal with multi-attributes component and can generate the optimal set of components. Application/Improvements:The algorithms are validated on a set of components taken from an online repository. The improvement in the FREFCOSCO algorithm can be done by using an appropriate validity mechanism.

Keywords

Fuzzy C Means, Fuzzy Clustering, Hybrid XOR and Fuzzy Relation Based Fuzzy Clustering, Software Component Selection Algorithm, Subtractive Clustering, Validation of Algorithm.

Full Text

   

Chander Diwaker ¹, Pradeep Tomar ²

Affiliations
1 Department of CSE, U.I.E.T., Kurukshetra University, Kurukshetra - 136119, Haryana, IN
2 School of ICT, Gautam Buddha University, Greater Noida - 201312, Uttar Pradesh, IN

Abstract

Objectives: Conventionally, to solve a problem it is necessary to design a new system every time and that it is difficult to reuse existing system for the designing of new system. This paper estimates usability of reusable components and interaction between components for integration of system. Methods: To handle this kind of problem Component Based System (CBS) has been considered. The reusability concept is the main factor of Component Based Software Engineering (CBSE) for components. More usage of reusable components provides better results in terms of estimation of reliability and efficiency of Component Based System (CBS). Ant Colony Optimization (ACO) is one among soft computing technique which may be used to estimate the path followed by components and interaction of components. In this paper ACO is used as methodology to find out more reusable components to increase the reliability or efficiency of the system. MATLAB is used for implementation of ACO. Performance metrics like Component efficiency, component density and component dependency are used for the analysis of proposed work. Findings: The results shows that in proposed mechanism the component efficiency is high, component density is also high as compare to existing CBS. Applications: This paper may helpful for the analysis of soft computing techniques by the use of CBSE performance metrics.

Keywords

ACO, Component Based Software Engineering (CBSE), Component Based System (CBS), Reusability, Soft Computing and MATLAB.

Full Text