Application of Data Mining Techniques for Software Reuse Process

• Published in: Procedia technology 2012, Vol.4, p.384-389
• Main Authors: Prakash, B.V. Ajay, Ashoka, D.V., Aradhya, V.N. Manjunath
• Format: Article
• Language: English
• Subjects: Clustering and Classification; Decision Tress; Software Metrics; Software reuse
• ISSN: 2212-0173; 2212-0173
• DOI: 10.1016/j.protcy.2012.05.059

Nowadays’ most of the software products are developed by using existing versions or features in order to reduce the delivery time of software product, to improve the productivity and quality and to reduce the development effort. Software reuse has been a solution factor to acquire the existing knowledge from software repository. To extract existing knowledge from software repository data mining can be used. Data mining is the process of extracting useful patterns and analyzing enormous data sets from large data. This paper gives the description of software reuse process, knowledge discovery process and software metrics for object oriented programming language are identified. Software metrics are used as quantitative measure to determine, assess, evaluating the software components. Mapping is done, for different data mining techniques which can be used for software reusability process using different software metrics. We have prepared 167 instances data sets from open source projects. Data mining techniques is used for evaluating the software components. There is gap between the need of useful data from software repository to software project management practices. To bridge this gap we are applying data mining techniques efficiently and effectively to extract useful knowledge from software repository using different software metrics. Finally, this knowledge can be used by project managers for better management of the software projects.