Research On Software Automatio Test Case Generation Based On GA

With the rise of the software testing industry, the number of people who research software testing technology is also increasing. The study on testing technology is two parts,One is research on test method,which includes white-box testing and black box testing.The other is research on test tools, The present situation is one of the test tools to study the degree of attention far more than on the testing methods.At present, a wide range of testing tools at home and abroad really is endless. The more famous are Mercury company QTP, WinRunner,Segue company SilkTest,IBM company ClearQuest,RTRT(Rational Test RealTime),METROWERKS CodeTest,Measurement Science and Technology Co., Ltd. of Shenzhen City Link's VcTester,elelogic Logiscope.Why do people so popular test tools? The reason is simple, It just want to improve testing efficiency, and achieve the automation of software testing.Test cases in software testing is the core, However, as much flexibility in the design of test cases,so far there are no automated testing tools can achieve a good test case automatic generation. This is an automatic test technology research bottleneck, Some people even suspect that the unlikely case generation of automation. Currently, some test tools simply generate random test cases of, Then make the test a large number of personnel changes. As a test case for this one is no effective automated.To enable automatic generation of test cases and further improve the automation of software testing. In this paper, the genetic algorithm unit in white-box testing phase to achieve the automation of test case generation. In the test phase of the test unit is relatively little flexibility. Because a single test scenario, Constitute a test case is just a test data. Simplification of the problem so that we'll automatically generate test cases automatically generated into a group to meet the requirements of test coverage data.. This is the most prominent feature, implemented automatic test data generation algorithms from theoretical research to practical application of the changes to improve the automated testing tools automatically generate functional test cases. Further improve the automation of software testing.