JuiceGen: The JUnit test generation tool from the UML state machine diagram

C. Doungsa-ard, K. Dahal, Zeeshan Pervez
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引用次数: 1

Abstract

This paper proposes a JUnit test code generation tool from the UML state machine diagram which is referred to here as JuiceGen tool. Genetic algorithm (GA) based approach is used to generate the test data because of its simplicity and effectiveness. The generated test data are sequences of triggers which change the status of the state machine diagram. The GAs can generate sequences of triggers which can cover more than 95% transition coverage. The triggers are mapped as methods called in the test code. Junit test code is generated not only from the sequences of triggers. The mapping information between the state machine diagram and the class under tests are also required. This detail includes: the methods which map to the triggers; the class members which map to the attribute; and the initial value of the attributes of the state machine. The generated JUnit test code has been tested by finding the code coverage of the program under test. The experimental results show that JUnit code generated from JuiceGen can represent all behaviours which the sequence of triggers could cover.
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JuiceGen:来自UML状态机图的JUnit测试生成工具
本文提出了一种基于UML状态机图的JUnit测试代码生成工具,这里称为JuiceGen工具。基于遗传算法的测试数据生成方法简单有效。生成的测试数据是改变状态机图状态的触发器序列。GAs可以生成超过95%转换覆盖率的触发器序列。触发器被映射为测试代码中调用的方法。Junit测试代码不仅是从触发器序列生成的。状态机图和测试中的类之间的映射信息也是必需的。这个细节包括:映射到触发器的方法;映射到属性的类成员;以及状态机属性的初始值。生成的JUnit测试代码已经通过查找被测程序的代码覆盖率进行了测试。实验结果表明,由JuiceGen生成的JUnit代码可以表示触发器序列所能涵盖的所有行为。
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