Variant grouping method based on related input variables

A technology of input variables and grouping methods, applied in the fields of genetic laws, genetic models, instruments, etc., can solve the problems of difficult correlation between variants and input variables, and low test case efficiency.

Active Publication Date: 2021-04-23
XUZHOU UNIV OF TECH
View PDF3 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] In order to solve the problem that it is difficult to find the correlation between variants and input variables in the above-mentioned prior art, which leads to the low efficiency of software testing to generate test cases, the present invention provides a variant grouping method based on related input variables, the method , first establish an optimization model for mutation test case generation, and design the fitness value function; then, transform the correlation between determining whether the mutant is killed and the input variable into determining the correlation between the fitness value and the input variable, that is, within the input domain, Does taking different values ​​of an input variable affect the change of the fitness value

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Variant grouping method based on related input variables
  • Variant grouping method based on related input variables
  • Variant grouping method based on related input variables

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0061] Such as figure 1 As shown, it is a general flowchart of a variant grouping method based on related input variables proposed by the present invention. The method includes:

[0062] Step S1: Construct the optimization model for mutation test case generation and design the fitness value function

[0063] Let the program under test be G, implement mutations on the sentences it contains, and obtain the variant set as M={M 1 , M 2 ,...,M n}, n is the number of variants. Insert the variant branches transformed by these variants into G to obtain a new tested program G'. Let the input vector of the program be X=(x 1 ,x 2 ,...,x m ), m is the number of program input variables. The input domain D(X) is the cross product of each input variable domain, that is, D(X)=D(x 1 )×D(x 2 )×…×D(x m ).

[0064] remember f i (X) is the objective function, which reflects whether the input vector X of the program can cover the mutation branch, that is, whether to kill the mutant ba...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a variant grouping method based on related input variables, and aims to judge the correlation between variants and input components through a dynamic strategy and group the variants based on the same input variables. The method comprises the following steps: firstly, establishing a mutation test case generation optimization model, and designing a fitness function; secondly, randomly generating some evolutionary individuals as benchmark test data, and calculating adaptive values of the evolutionary individuals; performing small disturbance on the value of a certain variable, replacing the value of the original variable with the disturbed value, and calculating the adaptive value of the new test data; comparing the changes of the adaptive values corresponding to the disturbance before and after the disturbance, and judging the correlation between the killed variants and the input variables by judging the correlation between the adaptive values and the input variables; and finally, establishing a variant and input component correlation matrix, and grouping the variants by adopting a certain strategy.

Description

technical field [0001] The invention relates to the field of computer software testing, in particular to a variant grouping method based on related input variables. Background technique [0002] Throughout the software life cycle, software testing is an important guarantee of software quality. Through effective testing, software defects can be detected and the reliability of software can be improved. In recent years, software testing technology has become more and more mature. Among them, mutation testing is a testing technology that intentionally implants defects, and it is also an effective method to improve the sufficiency of test case sets. [0003] Mutation testing first implements a grammatically minor change to a statement of the program by using a mutation operator to generate a new program, which is a variant. A test case executes the variant and the original program separately. If the output results of the two are different, then the test case is said to have kil...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
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姜代红阮少伟袁媛申珅徐玮玮包季楠袁偲朕
Owner XUZHOU UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products