Authors: Ekbal Rashid
Addresses: Department of Computer Science and Engineering, Cambridge Institute of Technology, Ranchi, India
Abstract: Making case-based reasoning (CBR), effective and efficient I have introduced some new features i.e., renovation of the knowledgebase (KBS) and reducing the maintenance cost by removing the ambiguous cases from the KBS. Renovation of knowledgebase is the process of removing duplicate record stored in knowledgebase as well as adding new problems along with new solutions. This paper explores improvisation of case-based reasoning and its applications for software fault prediction. The system predicts the error level with respect to LOC and development time and both are dependent variables that affect the quality level. At the outset, it deals with the possibilities of using lines of code and development time from any language may be compared and be used as a uniform metric. Five different similarity measures have been used to find the best method that increases the accuracy. The system is able to get the information by using an information retrieval (IR) technique from the existing knowledgebase. The experimental results reveal that the CBR method with the implementation of similarity measures is a viable technique for the fault prediction with practical advantages. In order to obtain the result I have used indigenous tool.
Keywords: software fault prediction; similarity measures; LOC; lines of code; software development time; efficiency; case-based reasoning; CBR; information retrieval; software errors.
International Journal of Services Technology and Management, 2015 Vol.21 No.4/5/6, pp.214 - 227
Received: 30 Aug 2014
Accepted: 03 Mar 2015
Published online: 29 Dec 2015 *