Amalgamation and characterization for test Suite enhancement in software testing using data mining techniques

Abstract

Testing is the fundamental activity intentional at detecting and solving technical issues in the software source code. In software development, test suite plays a major role. A test suite is a collection of test case which describes actual input, action and an expected response to verify whether a system under test satisfies requirements correctly or not. A huge number of test cases are required for testing the software. The test cases may be redundant. So, the execution of all these test cases entails lot of effort, time and cost. So, it is necessary to make enhancement in the test suite that outcome in good coverage with less effort, time and cost. This work proposes a hybrid technique for test suite enhancement using data mining techniques. The hybrid approach is performed in three ways i) Classification based Clustering ii) Classification based Association iii) Classification based RTM approach used to make enhancement in the test suite and to improve accuracy.