Technical gazette, Vol. 29 No. 5, 2022.
Original scientific paper
https://doi.org/10.17559/TV-20220328054159
A Study of Wolf Pack Algorithm for Test Suite Reduction
Zemin Li
; Inner Mongolia Power (Group) Co., Ltd., Jinxiu Fuyuan A District, Qianda Men Road, Saihan District, Hohhot, Inner Mongolia, China
Shaobo Lei
; Inner Mongolia Power (Group) Co., Ltd., Jinxiu Fuyuan A District, Qianda Men Road, Saihan District, Hohhot, Inner Mongolia, China
Fugui Tan
; Inner Mongolia Power (Group) Co., Ltd., Jinxiu Fuyuan A District, Qianda Men Road, Saihan District, Hohhot, Inner Mongolia, China
Yupeng Liu
; Inner Mongolia Electric Power (Group) Co., 9 Qianda Men Road, Saihan District, Hohhot, Inner Mongolia, China
Bin Xiao
; Inner Mongolia Power (Group) Co., Ltd., Jinxiu Fuyuan A District, Qianda Men Road, Saihan District, Hohhot, Inner Mongolia, China
Xin Huang
; Inner Mongolia Electric Power (Group) Co., 9 Qianda Men Road, Saihan District, Hohhot, Inner Mongolia, China
Xu Ren
; Holley Technology Co., Ltd., 181 Wuchang Avenue, Wuchang Street, Yuhang District, Hangzhou, Zhejiang Province, China
Abstract
Modern smart meter programs are iterating at an ever-increasing rate, placing higher demands on the software testing of smart meters. How to reduce the cost of software testing has become a focus of current research. The reduction of test overhead is the most intuitive way to reduce the cost of software testing. Test suite reduction is one of the necessary means to reduce test overhead. This paper proposes a smart meter test suite reduction technique based on Wolf Pack Algorithm. First, the algorithm uses the binary optimization set coverage problem to represent the test suite reduction of the smart meter program; then, the Wolf Pack Algorithm is improved by converting the positions of individual wolves into a 0/1 matrix; finally, the optimal test case subset is obtained by iteration. By simulating different smart meter programs and different size test suites, the experimental result shows that the Wolf Pack Algorithm achieves better results compared to similar algorithms in terms of the percentage of obtaining both the optimal solution and the optimal subset of test overhead.
Keywords
smart meters; software testing; test suite reduction; wolf pack algorithm
Hrčak ID:
281664
URI
Publication date:
15.10.2022.
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