为进一步提高测试生成效率,提升大规模测试生成的自动化程度,构建了一种基于着色Petri网模型的一致性云测试生成方法,称为PT-Cloud方法,并将该方法实现为可提供一致性测试生成服务的云测试生成平台.该方法利用MapReduce技术,实现了面向测试生成需求的被测系统着色Petri网模型重构和标记,并在此基础上以实际测试数据驱动一致性测试例的自动生成.经实际测试生成和执行实践验证,PT-Cloud方法能保证所生成的测试例是切实可执行的,同时有效提高了测试生成的效率和自动化程度.
To improve efficiency and automation degree of large-scale test generation,a colored Petri nets( CPN) model based conformance test generation approach,named as PT-Cloud approach,is proposed and implemented to provide a cloud based conformance test case generation service. Utilizing MapReduce technology,PT-Cloud approach could perform test generation oriented model reconfiguration and labeling process,and then test cases with actual input data could be automatically generated. Validated through practical test generation and execution,the PT-Cloud approach could guarantee that all generated test cases are sufficiently feasible for practical test executions,and the efficiency and automatic degree of test generation are effectively promoted.