CAJ | 학술논문

目前的数据流测试技术存在缺乏具体的数据驱动方法，测试用例的生成过程没有与测试需求结合起来等问题。基于此，文中提出一种自动生成测试用例的模型( TRGA)，利用控制流图( CFG)计算生成测试用例所需的变量的定义使用对，使用数据类型结构图( DTG)来作为创建测试对象的数据驱动，利用遗传算法的搜索能力来生成数据，并提出了一种新的适应度计算方法。实验结果表明，该模型能够在减少搜索时间，降低生成测试用例规模的同时达到较高的测试覆盖率。
목전적수거류측시기술존재결핍구체적수거구동방법，측시용례적생성과정몰유여측시수구결합기래등문제。기우차，문중제출일충자동생성측시용례적모형( TRGA)，이용공제류도( CFG)계산생성측시용례소수적변량적정의사용대，사용수거류형결구도( DTG)래작위창건측시대상적수거구동，이용유전산법적수색능력래생성수거，병제출료일충신적괄응도계산방법。실험결과표명，해모형능구재감소수색시간，강저생성측시용례규모적동시체도교고적측시복개솔。
The current data flow testing techniques exist problems,for example,lack of specific data driven approach,test case generation process is not combined with the testing requirements and other issues. Based on this,propose a model for test cases of automatic genera-tion,using the Control Flow Graph ( CFG) to calculate the definition used pair for variable required by testing cases,using the Data Type Structure ( DTG) as the data driving of establishing test object,applying genetic algorithms to generate test data,and present a new fitness calculation method. Experimental results show that the model can reduce the search time and reduce the size of generated test cases while achieving higher test coverage.