COMPARATIVE ANALYSIS OF SOFTWARE DESIGN PATTERNS BASED DESIGN METRICS USING MACHINE LEARNING ALGORITHMS

Software measurement has been elementary for the progress in any engineering discipline. Design metrics is being used for taking qualitative and quantitative measures as well as reduction in software project. The concept of software metrics is coherent, well established and understandable. Therefore, it is very useful in developing software project with superior quality that fulfil the customer requirements. This study emphasis on detecting software design pattern-based design metrics using machine learning algorithm. The study detects the pattern using random forest and J48 algorithms. The results indicate that the algorithms are efficient and accurate for the detection of design pattern. The result shows that random forest gave good result than J48.