An upper multi-objective test case priority sorting method
A technology of prioritization and test cases, applied in software testing/debugging, error detection/correction, instruments, etc., can solve complex operations such as poor convergence of MOPSO, unsatisfactory algorithm performance, genetic algorithm selection, crossover, and mutation and other problems, to achieve the effects of reducing test costs, widening the distribution of solution sets, and improving solution quality
Active Publication Date: 2019-01-25
XIAN UNIV OF POSTS & TELECOMM
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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
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[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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The invention discloses an upper multi-objective test case priority sorting method aiming at the multi-objective test case priority sorting problem in regression testing. Firstly, the ordered sequenceof test case numbers is used as particle code, and the set of test case number sequences is used as particle swarm to generate initial population randomly. The average branch coverage and effective execution time of the test case sequence are used as fitness evaluation functions. Then a new individual is generated by using the method of epistatic crossover, and the particles in the non-dominatedsolution set are used as the global optimal particles. Finally, when the number of iterations reaches the maximum number of iterations, the individual in the non-dominated solution set is the optimalmulti-objective ranking result. Compared with the existing method, the invention provides a multi-objective test case priority sorting method with wide distribution range of non-dominated solution sets and higher fitness value. The method is conducive to discovering software defects as early as possible in the regression test process and reducing test cost.
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...
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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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