Assessing two graph-based algorithms in a model-based testing platform for Java applications

Fecha

2020

Tipo

comunicación de congreso

Autores

Villalobos Arias, Leonardo
Quesada López, Christian Ulises
Martínez Porras, Alexandra
Jenkins Coronas, Marcelo

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Resumen

Model-based testing (MBT) is an approach for auto- matically generating test cases from a model of the system under test. Existing MBT tools support the automation of this process at varying degrees. One such tool is MBT4J, a research platform that extends ModelJUnit, offering a high level of automation. We ex- tended MBT4J with two graph-based algorithms: the Chinese Postman Problem (CPP) and Breadth-First Search (BFS). The purpose of this study is to evaluate the efficacy of these two new algorithms added to MBT4J by comparing them to previous algo- rithms implemented in the platform. A case study was conducted using two open-source Java applications from public repositories, and twenty-one different configurations. The CPP tester per- formed similarly to previous testers in terms of time and coverage, and in addition, it resulted in a greater percentage of failed test cases in one application. The BFS tester was able to generate a greater amount of test cases when using fewer resources. We thus recommend using these algorithms for generating test cases for systems with complex models.

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ALGORITHMS, CASE STUDIES, COMPUTER LANGUAGES, COMPUTER APPLICATIONS