Software test data evolution generation system facing path

Abstract

The invention develops a software test data evolution generation system facing a path, which has the advantages that the test data passing a target path can be automatically generated by using a genetic algorithm according to the test path selected by users, in addition, various optional genetic algorithm individual coding modes, adaptive value calculation methods, selection modes, crossing modes, variation modes and the like can be provided in the process of generating test data by using the genetic algorithm, and users can conveniently select different test data generation methods according to the tested program in different types. In addition, the system also provides the traditional random method test data generation method as the comparison, and the automation generation of the software test data is really realized. When the system disclosed by the invention is utilized, the software test efficiency is greatly improved, a large number of software development resources are also saved, the technical support is provided for the credible software research and development of the national relevant plan and the engineering, and the development of software industry in China is promoted.

Description

technical field [0001] This patent relates to the field of software testing, and designs and develops a path-oriented software testing data automatic generation system. Background technique [0002] Software testing is the key to software quality assurance, an indispensable link in software development, and an important part of software engineering. The effect of testing is directly related to the quality of software products. According to the statistics of the American industry, software testing accounts for more than 50% of the total cost of the entire software development cycle, including many links that are very time-consuming, boring, very difficult and error-prone. In addition, with the continuous improvement of the complexity of computer control objects and the continuous enhancement of software functions, the scale of software is also continuously increasing. The amount of code in a large-scale system even reaches more than tens of millions of lines, which makes the...

AI Technical Summary

Problems solved by technology

There are many existing test data generation methods for path coverage. As an efficient global search method, genetic algorithm has been widely used in test data generation. The existing system software that uses this method to automatically generate path coverage test data adopts It is a traditional genetic algorithm. The individual coding method, fitness value calculation, selection method, crossover method and mutation method of genetic algorithm only use one method, and the efficiency of test data generation needs to be improved.

Images