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Chaos genetic algorithm based test case intensive simple algorithm

A chaotic inheritance and test case technology, applied in the field of software test case minimization generation, can solve the problems of complex method and low efficiency, and achieve the effect of simple reduction algorithm, reducing test cost and improving test efficiency.

Inactive Publication Date: 2015-01-07
HUZHOU TEACHERS COLLEGE
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Problems solved by technology

[0003] The purpose of the present invention is to provide a test case set reduction algorithm based on a chaotic genetic algorithm, which solves the problems that the existing test case set reduction method is complex and inefficient

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  • Chaos genetic algorithm based test case intensive simple algorithm
  • Chaos genetic algorithm based test case intensive simple algorithm
  • Chaos genetic algorithm based test case intensive simple algorithm

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test Embodiment t1

[0027] Put the test case t 1 ,t 2 ,...,t n Respectively called sub-body 1,2,3,L,n, with g [i] express. Use binary code 0, 1 to encode all children as the parent body: W i =[g [1] , g [2] ,...,g [n] ], g [i] ∈{0,1},g [i] = 1 means that the child body i is selected into the parent body, g [i] = 0 means that the child body i is not selected into the parent body. A parent's gene code contains the coverage information of all offspring, that is, the length is n. The population represents the collection of all parents, and the test case minimization problem can be transformed into finding the parent with the least number of tests in the population and covering all test requirements as much as possible.

[0028] Step 1: Coding and initializing the population;

[0029] Satisfied when the parent body encoding is initialized when the parent body W i with daughter g [i] When the subscripts are equal, g [i] = 1, the rest g [i] =0.

[0030] Step 2: parent body fitness functio...

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Abstract

The invention discloses a chaos genetic algorithm based test case intensive simple algorithm. The chaos genetic algorithm based test case intensive simple algorithm comprises initializing male parent body codes; performing fitness calculation on a male parent body; defining genetic operators are defined, wherein the genetic operators comprise three steps of selection, intersection and variation, the genetic variation and the optimization are performed on the male parent body mainly to obtain a new male parent body finally, the change of the variation to an optimal solution can be increased due to the production of the new male parent body, and accordingly the fitness evaluation needs to be performed on the new male parent body after the genetic operators are finished to determine whether the output conditions are met or not, an optimal filial generation is output if yes, and the chaos disturbance is added if not; performing continuous iteration until the difference between fitness average values calculated through twice calculation is less than a preset minimum positive number epsilon 1. According to the chaos genetic algorithm based test case intensive simple algorithm, the algorithm is simple, the test efficiency can be improved, and the test cost can be reduced.

Description

technical field [0001] The invention belongs to the technical field of software test case minimization generation, and relates to a test case set reduction algorithm based on a chaotic genetic algorithm. Background technique [0002] Software testing is an essential part of software quality assurance. In order to meet a certain test coverage rate, the number of test cases generated is often extremely large. The iteration of the software system development process requires frequent regression testing, and the test redundancy is serious. In order to improve test efficiency, reduce test cost, and reduce the overhead of test case execution, management and maintenance, it is extremely necessary to reduce the test case set. Existing test case reduction methods mainly include greedy algorithm, heuristic algorithm, integer programming algorithm, expanded set algorithm, genetic algorithm and so on. Aiming at the problem that when the genetic algorithm is used for the reduction of th...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F11/36G06N3/12
Inventor 蒋云良楼俊钢
Owner HUZHOU TEACHERS COLLEGE
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