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Higher order variation testing method based on statement dominance relation and two-stage genetic algorithm

A genetic algorithm and sentence technology, applied in the field of computer software testing, can solve problems such as the inability of mutation sentences to play a role and the ineffectiveness of high-order mutations

Inactive Publication Date: 2014-02-26
CHINA UNIV OF MINING & TECH
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Problems solved by technology

[0009] If the mutation statements in the high-order variant cannot be executed at the same time, the non-executed mutation statements cannot play a role, so the effectiveness of the high-order mutation cannot be truly reflected

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  • Higher order variation testing method based on statement dominance relation and two-stage genetic algorithm
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  • Higher order variation testing method based on statement dominance relation and two-stage genetic algorithm

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Embodiment Construction

[0033] Embodiments of the present invention will be described in detail below in conjunction with specific drawings and examples.

[0034] Step 1. High-order mutation sentence selection method based on sentence dominance relationship

[0035] 1.1 Basic concepts

[0036] Control flow graph (Control flow graph, CFG) is a graphical representation of program control structure, which is a directed graph G=(N,E,s,e) with the following structure, where the elements of N are called nodes of G , a certain statement of the corresponding program is not general; the element e of E ij =(n i ,n j ) is called the edge of G, which means from the statement n i to statement n j There is control flow. The control flow graph of each program also contains a unique entry node s and exit node e.

[0037] A path P refers to a sequence of nodes n 1 ,n 2 ,...,n l , satisfying the slave node n i to n i+1 There are edges, i=1,2,...,l-1. When program G takes X as input, the path traversed is ...

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Abstract

The invention discloses a higher order variation testing method based on a statement dominance relation and a two-stage genetic algorithm, and aims to improve effectiveness and quality of higher order variation tests. The method includes firstly, on the basis of a dominance relation tree of a program, determining the statement selecting problem of higher order variation, and accordingly guaranteeing all mutated statements in a same higher order variant being executed; secondly, establishing required target function, and measuring merits and demerits of the higher order variants; finally, designing the genetic algorithm including two alternating evolution processes to generate high-quality higher order variants, and accordingly disclosing complex defects contained by the program. The method has the advantages that the number of the higher order variants can be decreased, good performances of the higher order variants can be guaranteed, and significances is provided for improving effectiveness and feasibility of the higher order variation tests.

Description

technical field [0001] The invention relates to the field of computer software testing, and designs a high-order variation testing method based on sentence dominance relationship and two-stage genetic algorithm. This method differs from existing methods in that it selects sentences for mutation based on the dominant relationship between sentences, thus ensuring that all mutated sentences can be executed at the same time; in addition, a new high-order variant evaluation method is given for Finally, a genetic algorithm including two alternate evolution processes is designed to generate high-quality high-order variants, thereby revealing the complex defects contained in the program. This method can not only reduce the number of high-order variants, but also ensure that the high-order variants have good performance, which is of great significance for improving the effectiveness and feasibility of high-order variant testing. Background technique [0002] The purpose of testing s...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F11/36
Inventor 姚香娟巩敦卫郭仪昊李鑫张功杰顾雅丽王文亮吴飞跃
Owner CHINA UNIV OF MINING & TECH
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