Research On Software Test Suite Automated Generation And Optimization Methods

With the development of informationization, the software products being used more and more widely, the scale and complexity of the software system getting much larger, the potential danger in the software system growing more and more, so improving the reliability and quality of software has become the most important task in the software testing field.Software testing is the important measure to assure the quality and reliability of software. At the same time, it is also a complex process spending enormous human, material resources and time. The cost of software testing is about 40 to 50 percent in the whole process of software development. Therefore, improving the automation ability is very important to ensure the quality of software and reduce the developing cost. And improving the automation ability of test cases generation is the key point in improving the testing efficiency. So according to the test suite automatically generation, the paper makes deep research and specific design.In the first, the paper introduces some basic theory of software testing and what is software testing automation. Then it introduces some important concepts and approaches about test case, focusing on discussing the generation methods of functional test case and structure test case. Subsequently, the paper introduces the principle of genetic algorithm, analyzing the process and the major factors which impact the operator of genetic algorithm.The paper takes the genetic algorithm as the key algorithm, and makes some analyses about genetic algorithm's advantages and disadvantages in the software testing environment. According to the analyses, it makes some improvement to genetic algorithm's disadvantages of the designing content in the subject. First, it designs a more applicable fitness function in this paper's system; secondly, adopts the method of more points cross and dividing cross points which avoid the large damage of parameter string; finally, it designs the fit mutation which assures the optimum individual can be kept in the process of evolution. Through these improvements, the search capability and path coverage have been enhanced a lot.At last, the paper designs and implements the test case automated generation system based on the improved genetic algorithm. And taking the triangle judgment program as an example, use the system to generate test case which can implement path coverage. The experiment shows that this system can complete test data automatic generation for objectives path, and it can also automatically generate test case which can exactly satisfied with the specified path testing. At the same time, the program path to be covered or not recorded, the best solution currently can also be given while path are not fully covered.