Research Article
Qualitative Analysis Model for Qualifying the Components for Reusability Using Fuzzy Approach
@INPROCEEDINGS{10.1007/978-3-319-11629-7_23, author={V. Subedha and S. Sridhar}, title={Qualitative Analysis Model for Qualifying the Components for Reusability Using Fuzzy Approach}, proceedings={Signal Processing and Information Technology. Second International Joint Conference, SPIT 2012, Dubai, UAE, September 20-21, 2012, Revised Selected Papers}, proceedings_a={SPIT}, year={2014}, month={11}, keywords={Software reuse reusability metrics quality of reusability fuzzy logic component assessment model}, doi={10.1007/978-3-319-11629-7_23} }- V. Subedha
S. Sridhar
Year: 2014
Qualitative Analysis Model for Qualifying the Components for Reusability Using Fuzzy Approach
SPIT
Springer
DOI: 10.1007/978-3-319-11629-7_23
Abstract
A reusable software component is a component in an executable form where it can be plugged into the environment. In order to reuse the high quality components from an existing environment, finding the measurable characteristics of the reusable software components and their corresponding metrics is an important issue. Although, some characteristics are impossible to measure or predict directly there are still many characteristics that can be used for measuring the reusable software component. We propose a qualitative analysis model to assess the quality of the component and this proposed model is feasible and can achieve high quality reusable components compare with other model in the existing literature. We measure the quality of the components for reuse with functional coverage report, software reuse metrics and minimum extraction time. Using these measures the identified set of components is classified into qualified set and not qualified set for reusability. The qualified set for reusability will give high potential and high quality reusable components which will increase the reuse frequency and reuse utility level. The reusability degree of the component can be obtained with the help of Fuzzy Rules.