Software Testing Based On Data Mining Technology

With the rapid development of the information technology, software systems in the economic, financial, medical, communications, transportation, aerospace, aviation, industrial control and other fields has been widely used. Therefore, the reliability of the software more and more attention has been paid.In order to improve software reliability, software engineering methodology has been applied to guide software development procedure. In the whole process of software development, software coding process in the presence of large numbers of clones are often the code, they differ slightly, scattered in different parts of the software, manual methods are difficult to maintain a unified, in the testing phase of the code review stage is not easy detect them, this is a difficult software testing. In the use of test cases to test the program during the test data generated by hand, heavy workload, low efficiency, error-prone, and can not guarantee the adequacy of the test. Therefore, how to generate test data has also become one of the difficulties of software testing.Data mining is related to databases, artificial intelligence, statistics, machine learning and other cross-disciplinary. It can be found hidden among large amounts of data relationships. In this paper, In this paper, investigated the effects of data mining technology and software testing features, and combining the two in software testing to solve the difficulties encountered.For the phenomenon of cloning for the code, this paper presents a new solution, a quantitative approach to the search for code clones; structure for the preparation of test data by hand is extremely difficult and inefficient this problem, a large number of test cases according to their needs characteristics of genetic algorithms used in this way to complete the generation of test cases and automate the testing process.