Reuse of Test Case based on Attributes Weight Optimization

Abstract

Software testing is complicated and requires a lot of manpower and material resource in the software life cycle. The design of test cases costs a lot of time. In order to improve the efficiency of software testing in the test cases design stage, this paper uses historical test assets to assist the design of test cases in new project, and proposes a test case reuse method based on attribute weight optimization. Firstly, the text vector of test data is obtained by using Natural Language Processing. The test case package is formed based on the keyword extraction and the test case clustering, and the test case vector library is constructed. Then, a test case attribute weight optimization method based on the Genetic Simulated Annealing Algorithm is proposed. Combined with the optimized attribute weights, the test case reuse is realized by using the similarity calculation of the test case data vector. Finally, the test case reuse method is experimentally verified by two projects with different types. Experimental results show that this method can effectively improve the efficiency of test cases’ design. It has better understandability and maintainability, and improve the quality of test cases.