Open AccessEvaluation of a model‐based testing platform for Java applications
Author(s) -
Villalobos-Arias Leonardo,
Quesada-López Christian,
Martínez Alexandra,
Jenkins Marcelo
Publication year - 2020
Publication title -
iet software
Language(s) - English
Resource type - Journals
ISSN - 1751-8814
DOI - 10.1049/iet-sen.2019.0036
Subject(s) - java , computer science , test case , automation , code coverage , process (computing) , software engineering , programming language , source code , keyword driven testing , open source , model based testing , system under test , operating system , software , software system , machine learning , engineering , software construction , mechanical engineering , regression analysis
Model‐based testing (MBT) automates the design and generation of test cases from a model. This process includes model building, test selection criteria, test case generation, and test case execution stages. Current tools support this process at various levels of automation, most of them supporting three out of four stages. Among them is MBT4J, a platform that extends ModelJUnit with several techniques, offering a high level of automation for testing Java applications. In this study, the authors evaluate the efficacy of the MBT4J platform, in terms of the number of test cases generated, errors detected, and coverage metrics. A case study is conducted using two open‐source Java systems from public repositories, and 15 different configurations. MBT4J was able to automatically generate five models from the source code. It was also able to generate up to 2025 unique test cases for one system and up to 1044 for the other, resulting in 167 and 349 failed tests, respectively. Transition and transition pair coverage reached 100% for all models. Code coverage ranged between 72 and 84% for the one system and between 59 and 76% for the other. The study found that Greedy and Random were the most effective testers for finding errors.