Test Suite Reduction Using Data Mining Techniques: A Review Article

Test Suite Reduction Using Data Mining Techniques: A Review Article

Software testing is one of the most important and timeconsuming tasks in software development life cycle. A large number of test suites are generated using automated test case generating tools. Executing all of these test cases will spend so much time and huge costs, however some of them are redundant and unnecessary to execute. Furthermore, researchers have tried to reduce test cases, and faced several challenges on software testing using test suite reduction techniques. The main purpose of test case reduction is to decrease the number of test cases in order to minimize the time and costs of executing them. There are hundreds of techniques proposed in test suit reduction field. The data mining based test suite reduction techniques are one of important and efficient types of techniques in test suite reduction. Considering the fact that data mining is very important in knowledge discovery and today’s world, the need for existence of an analytical classification for data mining based test suite reduction techniques is felt. Thereupon, in this paper, we have tried to provide a literature review on various research papers in test suite reduction using data mining techniques and classify them. In this regard, data mining based test suite reduction techniques have been categorized into three main classes and several subclasses. All in all, data mining based test suite reduction techniques classified into some classes, namely, statistical-based, decision tree-based, coverage-based, density-based, combination of coverage-based and distribution-based, similarity-based and frequency determination-based.