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Mutation test data generation method based on multi-population coevolution

A technology of mutation testing and co-evolution, which is applied in the fields of electrical digital data processing, software testing/debugging, genetic rules, etc., can solve the problem of low efficiency of hard-to-kill mutant test data generation, and achieve the effect of improving efficiency

Active Publication Date: 2020-06-12
XUZHOU UNIV OF TECH
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Problems solved by technology

[0008] The technical problem to be solved by the present invention: study the mechanism of the difficult-to-kill variant, determine the index for evaluating the difficult-to-kill variant; The information provided by evolution dynamically reduces the search domain and improves the efficiency of mutation test data generation

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  • Mutation test data generation method based on multi-population coevolution
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  • Mutation test data generation method based on multi-population coevolution

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Embodiment Construction

[0060] The technical solutions in the embodiments of the present invention will be fully described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.

[0061] Such as figure 1 As shown, a general flow chart of a mutation test data generation method based on co-evolution of multiple groups. The method includes: Step 1. Determination of hard-to-kill variants

[0062] (1) Indicator I

[0063] The reachable difficulty of the variant sentence is recorded as index I. If the variant sentence s'is reachable, then there is at least one executable path from the variant M to the variant sentence s'. Suppose there are L execut...

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Abstract

The invention discloses a mutation test data generation method based on multi-population coevolution, and aims to gradually reduce a search domain according to information provided by population evolution when a multi-population coevolution genetic algorithm is adopted to generate test data for variants which are difficult to kill, so as to improve the efficiency of generating mutation test data.The method comprises the following steps: firstly, determining a difficult-to-kill variant based on the reachable difficulty of a variant statement, the number of related program input variables and other indexes; then, establishing a mathematical model of a mutation test data generation problem based on path coverage constraints, and finally, for the variants which are difficult to kill, determining the opportunity and strategy of search domain reduction based on information provided by population evolution by adopting a multi-population coevolution genetic algorithm, dynamically reducing thesearch domain, and quickly and accurately generating mutation test data.

Description

Technical field [0001] The invention relates to the field of computer software testing, and designs a method for generating mutation test data based on co-evolution of multiple groups. This method is different from the original method in that, for the difficult-to-kill variants, when the multi-group co-evolution genetic algorithm is used to generate test data, the search field is gradually reduced according to the information provided by the population evolution to increase the generation of mutation test data. s efficiency. Background technique [0002] Software testing is an important means to ensure software quality. Passing the test can not only detect possible defects in the software, but also improve the reliability of the software. Variation testing is a defect-oriented testing technique. Mutation testing is often used to evaluate the quality of test data sets, and is also used to assist in generating test data. [0003] A variant that is difficult to kill refers to a var...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F11/36G06N3/12
CPCG06F11/3684G06N3/126
Inventor 党向盈巩敦卫姚香娟鲍蓉申坤
Owner XUZHOU UNIV OF TECH
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