Intelligent test case generation method based on historical demand data mining and medium

Abstract

The invention discloses an intelligent test case generation method based on historical demand data mining and a medium, belongs to the field of computer software development and software testing, andsolves the problems of low effectiveness and availability of test cases generated in the prior art. The method comprises the following steps: processing an obtained historical demand document to obtain a demand sub-item sequence, and meanwhile, processing a test case corresponding to the obtained historical demand document to obtain a test case sequence; establishing a hidden Markov model for predicting the test case based on the test case sequence of the demand subitem sequence; based on the training set and the test set, adopting a supervised learning mode hidden Markov model to obtain a prediction model with optimal parameters; and inputting the demand subitem sequence of the to-be-predicted demand document and the prediction model of the optimal parameter into a Viterbi algorithm, solving and outputting an optimal test case sequence, and searching a final test case based on the output and mapping relationship. The method is used for generating the test case.

Description

technical field [0001] The invention discloses a method and medium for intelligently generating test cases based on historical demand data mining, which are used for generating test cases and belong to the field of computer software development and software testing. Background technique [0002] At present, the main idea of ​​testers designing test cases is formed in the process of product requirements analysis. Based on the analysis and research of requirements analysis documents, testers focus on the business implementation logic and system implementation logic, combined with their own experience and skills, to dig out the focus and key points of the test work, form test ideas, and finally convert the test ideas into test case output. [0003] The above process is all done manually by the testers, and the experience and skills of the testers are very important. Different testers design different test cases for the same requirement, resulting in uneven design quality of te...

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Problems solved by technology

[0006] In view of the problems of the above research, the purpose of the present invention is to provide a method and medium for intelligently generating test cases based on historical demand data mining, so as to solve the problem of machine learning related to natural language processing based on machine learning and not using linear sequences in the prior art. Algorithms are used to generate test cases, resulting in low effectiveness and usability of test case generation results, that is, low prediction accuracy and slow processing speed.

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