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A method for prioritizing test cases of upper-level multi-objectives

A technology of prioritization and test cases, applied in software testing/debugging, error detection/correction, instruments, etc., can solve the problem of unsatisfactory algorithm performance, poor MOPSO convergence, genetic algorithm selection, crossover, mutation and other complex operations and other problems, to achieve the effect of reducing the test cost, widening the distribution of the solution set, and improving the quality of the solution.

Active Publication Date: 2021-09-24
XIAN UNIV OF POSTS & TELECOMM
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AI Technical Summary

Problems solved by technology

Deb Kalyanmoy et al. proposed a fast non-dominated sorting genetic algorithm (Non-dominated Sorting Genetic Algorithm II, NSGA-II) with an elite strategy to solve multi-objective optimization problems. Although NSGA-II runs fast and has a good convergence of the solution set, but Operations such as selection, crossover, and mutation in genetic algorithms are relatively complex, and the performance of the algorithm is not ideal
The particle swarm optimization (Multi-ObjectiveParticle Swarm Optimization, MOPSO) algorithm used to solve multi-objective optimization problems such as Tyagi Manika solves the prioritization of test cases, but the convergence of MOPSO is not good

Method used

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  • A method for prioritizing test cases of upper-level multi-objectives
  • A method for prioritizing test cases of upper-level multi-objectives
  • A method for prioritizing test cases of upper-level multi-objectives

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Embodiment Construction

[0027] Take the test case priority sorting of the JavaScript unit testing framework Jasmine as an example, combined with the attachedfigure 1 The specific implementation manner of a method for prioritizing high-level multi-objective test cases for regression testing proposed by the present invention will be described.

[0028] Step 1: For Jasmine, a program to be tested, use the 24 test cases already designed in the regression test as a test case set for testing. The source program of Jasmine has 95 branches, and record the branch coverage of the program to be tested by the test cases. , to obtain the branch coverage information matrix A of the test case program to be tested; if the test case set is represented by Φ, Φ={T 1 , T 2 ,...,T i ,...,T n}, where T i (1≤i≤n) is the i-th test case in the test case set, the size of the constructed branch coverage information matrix A is 24×95, the range of branch numbers in the program to be tested is 1 to 95, and the range of test c...

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Abstract

Aiming at the problem of prioritization of multi-objective test cases in regression testing, the invention discloses a method for prioritization of upper-level multi-objective test cases. In this method, the orderly sequence of test case numbers is used as the particle code, and the set of test case number sequences is used as the particle swarm to randomly generate the initial population; the average branch coverage and effective execution time of the program to be tested in the test case sequence are used as the fitness evaluation function ; Then use the epistasis crossover method to generate new individuals, and use the particles in the non-dominated solution set as the global optimal particles; finally, when the number of iterations reaches the maximum number of iterations, the individuals in the non-dominated solution set are the optimal multi-objective sorting results. Compared with the existing methods, the present invention provides a multi-objective test case prioritization method with a wide range of non-dominated solution sets and higher fitness values. This method helps to find software defects as early as possible in the regression test process, Reduce the cost of testing.

Description

technical field [0001] The invention belongs to the technical field of software testing, in particular to the technical field of software regression testing, and specifically relates to a prioritization method for upper-level multi-objective test cases. Background technique [0002] In the process of software evolution, Test Case Prioritization (TCP) technology, as an efficient and practical regression testing technology, achieves higher testing efficiency by sorting test cases according to certain test objectives, which is helpful for improving defect It is of great significance to improve the early detection rate and reduce the cost of testing. With the continuous improvement of industrial testing requirements, it is no longer enough to optimize the sequence of test cases for a single test target, because the actual testing process needs to consider the impact of various factors on software quality, such as testing cost, time and Code modification and other factors, Multi...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F11/36G06N3/00
CPCG06F11/3676G06F11/3684G06N3/006
Inventor 孙家泽王刚王曙燕
Owner XIAN UNIV OF POSTS & TELECOMM
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