Impact of the significance of input values and paths on the effectiveness of the automatically generated test suite

Perla Beatriz Fernández Oliva, Martha Dunia Delgado Dapena, Alejandro Miguel Güemes Esperón, Heydi Margarita Henry Chibas, José Miguel Loor Intriago


Software tests are fundamental in the reliability and quality of systems, contributing to their positioning in the market. Generating test data is a critical task, as extensive testing is costly in time and effort. An adequate design of the test cases, which contemplates a selection of adequate values, can detect a high number of defects. There are proposals for the automatic generation of test suites using metaheuristic algorithms with the fundamental objective of reducing the time associated with this process, facilitating its execution by developers and testers, and achieving high levels of coverage. However, there is no emphasis on effectiveness in detecting errors. This work contemplates an analysis of the impact of the significance in the input values and in the paths or scenarios for the detection of suit errors generated using metaheuristic algorithms. Proposals for the automatic generation of test suits by different authors are addressed and experiments based on two case studies are carried out. The results are compared between including or not in this algorithm the significance in the input values and in the paths or scenarios.

Palabras clave

lean test suites; metaheuristic algorithms

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