Genetic algorithm parallelization test case generation method based on front and back end fusion of Web application
A test case generation and genetic algorithm technology, applied in the field of efficient test case generation, can solve problems such as poor system resource utilization and low efficiency, and achieve the effects of improving generation efficiency, ensuring continuity, and reducing code complexity
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Publication Date
- 2020-12-01
- Estimated Expiration
- Not applicable · inactive patent
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Abstract
Description
technical field
[0001] The invention is an efficient test case generation method based on genetic algorithm (GA) parallelization, which belongs to the field of software test, Web application test, concurrent test and test case generation. Background technique
[0002] With the popularization and rapid development of Web technology, Web application programs are becoming more and more complex, and software testing for Web applications has become a challenging task. Web application security test case generation is an important means to ensure its reliability and security.
[0003] At present, the research on web application security testing mainly focuses on the test generation based on the front-end model and the penetration test based on the back-end. Most of the testing research based on the front-end model aims at the state / transition / transition sequence coverage of the model itself, and cannot effectively test the security vulnerabilities existing in the back-end. Backen...
Examples
Embodiment Construction
[0013] The present invention is a GA parallelization-based Web application EFSM model test case generation optimization, through the parallel execution of population individuals and parallel calculation of fitness values, better utilization of system resources, and improved efficiency of Web application test case generation. The specific implementation process of the present invention can be divided into the following stages.
[0014] The first phase, thread initialization. The present invention designs a new thread pool model to support parallel execution of Web application populations. Initialize a thread pool object AsyncTask, including the following attributes: method list, parameter list (and dictionary parameter list), started thread list, result list, number of available threads, and available browser process pool. At the same time, initialize a set of browser process lists for use by the thread pool.
[0015] The second stage is the parallel execution of genetic algo...