Finding software errors using data mining methods

The common software problems appear in a wide variety of applications and environments. Some software related problems arises in software project development i.e. software related problems are known as software defect in which Software bug is a major problem arises in the coding implementation .There are no satisfied result found by project development team. The software bug problems mentation in problem report and software engineer does not easily detect this software defect but by the help of data mining classification software engineers easily can classify software bug. In order to overcome the software development challenges like delivering a project on time, developing quality software products and reducing development cost, software industries commonly uses defect detection software tools to manage quality in software products. Defects are detected and classified based on their severity, this can be automated in order to reduce the development time and cost. Nowadays to extract useful knowledge from large software repositories engineers and researchers are using data mining techniques. In this paper, software defect detection and classification method is proposed and data mining techniques are integrated to identify, classify the defects from large software repository. Based on defects severity proposed method discussed in this paper focuses on three layers: core, abstraction and application layer. The designed method is evaluated using the parameters precision and recall.

Keywords:

Software Bugs Tracking , Data Mining Techniques , Software Quality Assurance , Bug Tracking , Bug Classification.