This paper introduces the technique to select the test cases from the unified modeling language (UML) behavioral diagram. The UML behavioral diagram describes the boundary, structure, and behavior of the system that is fed as input for generating the graph. The graph is constructed by assigning the weights, nodes, and edges. Then, test case sequences are created from the graph with minimal fitness value. Then, the optimal sequences are selected from the proposed fractional-spider monkey optimization (fractional-SMO). The developed fractional-SMO is designed by integrating fractional calculus and SMO. Thus, the efficient test cases are selected based on the optimization algorithm that uses fitness parameters, like coverage and fault. Simulations are performed via five synthetic UML diagrams taken from the dataset. The performance of the proposed technique is computed using coverage and the number of test cases. The maximal coverage of 49 and the minimal number of test cases as 2,562 indicate the superiority of the proposed technique.
System modeling in software engineering describes the procedure of creating a demonstration of real system in a conceptual way to know the system behavior. The software testing promotes reusing the model for the function of testing and this accelerates test case generation development. The test case generation verifies the reliability of system through enhanced test coverage. Test cases are the set of variables or conditions that defines the quality of product and level of correctness. This research aims to develop a method named Spider Monkey Particle Swarm Optimization (SMPSO) algorithm to generate test case using UML diagram. Accordingly, the proposed algorithm effectively generates the optimal test case by UML diagram through the construction of control graph. The proposed method achieved the coverage as 76, and generates the number of test cases as 82413.
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