CLASSIFICATION OF DEFECTS IN SOFTWARE USING DECISION TREE ALGORITHM M. SURENDRA NAIDU Research Scholar, Department of Computer Science & Technology, Sri Krishna Devaraya University E-mail: surendranaidu0580@gmail.com Dr.N. GEETHANJALI Associate Professor, Dept of Computer Science and Technology, Sri Krishna Devaraya University Abstract: Software defects due to coding errors continue to plague the industry with disastrous impact, especially in the enterprise application software category. Identifying how much of these defects are specifically due to coding errors is a challenging problem. Defect prevention is the most vivid but usually neglected aspect of software quality assurance in any project. If functional at all stages of software development, it can condense the time, overheads and wherewithal entailed to engineer a high quality product. In order to reduce the time and cost, we will focus on finding the total number of defects if the test case shows that the software process not executing properly. That has occurred in the software development process. The proposed system classifying various defects using decision tree based defect classification technique, which is used to group the defects after identification. The classification can be done by employing algorithms such as ID3 or C4.5 etc. After the classification the defect patterns will be measured by employing pattern mining technique. Finally the quality will be assured by using various quality metrics such as defect density, etc. The proposed system will be implemented in JAVA. Keywords: ID3, Defect classification, Defect detection, Association Rule mining Algorithm. 1. Introduction Software Defect can be defined as “Imperfections in software development process that would cause software to fail to meet the desired expectations” [11]. Software defects have a major impact of software development life cycle. Software defects are expensive. Moreover, the cost of finding and correcting defects represents one of the most expensive software development activities [15]. Defects found during production may be viewed as a manifestation of process deficiencies. Hence, it makes sense that defect data be analyzed to make in-process improvements [1]. Organizations face many problems that impede rapid development of software systems critical to their operations and growth [2]. Prevention and detection of defect are critical elements of software quality assurance [8]. A small increase in the prevention measure will normally create a major decrease in total quality cost [6]. Defects are identified at various stages of software life cycle through activities like Design review, Code Inspection, GUI review, function and unit testing [12]. Defect prevention plays an important role in the software quality assurance in any projects. Orthogonal Defect Classification (ODC) is a method used to classify the defects according to the defect types [13]. Defect prevention techniques that are being used in each phase of the software development [14]. Defect prevention is the most vital but habitually neglected facet of software quality assurance [5]. Detecting defects in software product development requires serious effort, so it’s important to use the most efficient and effective methods [4]. Orthogonal defect classification is a concept which enables developers, quality managers and project managers to evaluate the effectiveness and correctness of the software [10]. The main objective of the defect management is to achieve complete customer satisfaction. One of the most important steps towards total customer satisfaction is the generation of nearly zero-defect products [9]. The defect management process includes defect prevention, defect discovery and resolution, defect causal analysis, and the process improvement [3]. Quality management is a well-established discipline with historic roots in manufacturing industries. The classical approach to quality management can be summarized in these simple steps: Analyze product defects to determine root causes, Modify processes to address and remove root causes of defects and Fix defects using improved processes [7]. M. Surendra Naidu et al. / International Journal of Engineering Science and Technology (IJEST) ISSN : 0975-5462 Vol. 5 No.06 June 2013 1332