Enhancing state-sensitivity partitioning technique by using prioritization approach

Software Testing is one of the activities in Software Quality Assurance to indicate the successfulness of a project. In dynamic software testing, greybox testing has been suggested to consider both white-box (structure-based testing) and black-box specification-based testing). State-Sensitivity- Partitioning (SSP) is a new technique to generate test cases for grey-box testing. The lengthy sequence with redundant data state makes the testing process expensive and may lead to inefficiency. Thus, this research proposed a prioritization approach in specifying and reordering the generated SSP test cases to enhance the SSP technique. First, coverage-based information which are code coverage, branch coverage, function coverage and path coverage were collected. We apply a weighted method to calculate the priority value for each test sequence based on the collected coverage information. Test cases then are ranked based on the calculated priority values and thus, a new prioritized SSP test suite is obtained. An experimental study using mutation testing analysis is conducted to assess the efficiency of the proposed test case prioritization method. The experimental study has demonstrated that prioritization approach can enhance the efficiency of SSP technique and achieved the purpose on this work.

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