JDart-Based Test Cases Generation and Optimization

基于JDart的测试用例自动生成与优化

¹ School of Automation, Northwestern Polytechnical University, Xi'an 710072, China
² School of Software and Microelectronics, Northwestern Polytechnical University, Xi'an 710072, China

Received: 8 May 2017

Abstract

Test cases play a crucial role in software testing, with the increasing complexity and scale of software, automatic test cases generation becomes increasingly important for software reliability and test efficiency. Symbolic-based test cases generation approach draws great attention due to its high reliability and there are already various kinds of tools introduced. However, most of these tools are C-oriented. JDart is a good open source Java-oriented symbol execution tool with excellent scalability. This paper aims to enhance the automatic test generation ability of JDart by designing and optimizing its array symbolization. The verification result shows that the optimization strategy proposed in this paper is effective in the test of the Jdart, it can effectively improve the coverage of Jdart on program involving complex object testing.

摘要

基于符号执行的测试用例生成方法，以其高可靠性得到了学术界和工业界广泛关注。然而，已有工具大都面向C或者C++程序，面向Java的符号执行工具发展相对较慢。JDart是表现较好的一款开源的面向Java的符号执行工具，但是对复杂数据类型比较数组却支持很弱，因此，在对JDart工具以及动态符号技术进行分析的基础上，通过对JDart测试用例生成能力和存在问题的深入剖析，针对数组处理进行改进，以提高生成测试用例的代码覆盖率，保证测试质量。最后，通过用三角形程序实例进行验证，结果表明，改进后的JDart工具能够完全探索函数中关于数组处理的所有路径。