Automatic software test system and method for artificial intelligence

Abstract

The invention discloses an automatic software test system and method constructed based on an artificial intelligence algorithm, and the system can autonomously learn test specification requirements and previous test data and results, and summarize and refine a test specification requirement model. The system can autonomously learn programming language design content and generate a programming language model. The system can be combined with different software platforms and hardware platforms to carry out self-adaption on a programming language model to generate a target system model, and the target system model is used for guiding automatic software testing to be carried out on different software and hardware platforms. By adopting the test system, a system and a method for autonomously learning test requirements and programming specifications, autonomously adapting to different software and hardware platforms to automatically generate test cases, automatically carrying out software tests and automatically providing software test reports can be provided.

Description

technical field [0001] The invention belongs to the technical field of software testing, and in particular relates to an artificial intelligence automated software testing system and method. Background technique [0002] Software testing is a technology that has emerged with the large-scale application of software control programs. This technology is mainly used to test the quality of software programs. Check before application, and guide software designers to fix possible loopholes, errors, defects, etc., so as to provide evaluation support for efficient application of software, reduce possible risks in software application, and improve software effectiveness. [0003] Based on the importance of software testing, a large-scale reliability verification of the developed software program is required before the software program is put into the market, so as to eliminate the possible risks after the market application, especially in some key fields such as aerospace, industry, e...

AI Technical Summary

Problems solved by technology

[0004] In order to deal with some of the above problems, some semi-automated and automated testing tools or auxiliary scripts have been introduced on the market to speed up software testing. These tools or scripts can help speed up testing to a certain extent, but their applicability is low. It is set for some single test scenarios, and the number of test cases is relatively limited, limited by the number of previous settings, and it is not possible to provide feedback and automatic updates for some problems in actual applications. Applicability to similar test scenarios These problems lead to an improvement in the efficiency of the test, but the improvement is not large, and the scope of the test is limited by the thinking and settings of the test script writers. The test cases cannot be automatically updated, and the test cases may not be fully covered. The efficiency and accuracy of the test are still low

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