Tehnički vjesnik, Vol. 28 No. 6, 2021.
Izvorni znanstveni članak
https://doi.org/10.17559/TV-20210311060442
Test Case Prioritization Based on Artificial Immune Algorithm
Hongwei Xu
; Measurement center of Guizhou Power Grid Company, 32 Jiefang Road, Nanming District, Guiyang City, Guizhou Province, China
Pengcheng Li
; Measurement center of Guizhou Power Grid Company, 7 Guanshui Road, Nanming District, Guiyang City, Guizhou Province, China
Zhongxiao Cong
; Measurement center of Guizhou Power Grid Company, 120 Guanshui Road, Nanming District, Guiyang City, Guizhou Province, China
Fengzhi Zhang
; Holley Technology Co.Ltd, 181 Wuchang Street, Yuhang District, Hangzhou City, Zhejiang Province, China
Yi Pan
; Holley Technology Co.Ltd, 181 Wuchang Street, Yuhang District, Hangzhou City, Zhejiang Province, China
Xu Ren
; Holley Technology Co.Ltd, 181 Wuchang Street, Yuhang District, Hangzhou City, Zhejiang Province, China
Xingde Wang*
orcid.org/0000-0002-0902-0484
; Beijing University of Posts and Telecommunications, 10 Xitucheng Road, Haidian District, Beijing, China
Ying Xing
; Beijing University of Posts and Telecommunications, 10 Xitucheng Road, Haidian District, Beijing, China
Sažetak
Regression testing is an essential and critical part of smart terminal program development. The test case suite is usually preprocessed by test case prioritization technology to improve the efficiency of regression testing. To address the problems of traditional genetic algorithm in solving the test case prioritization problem, this paper proposed a test case prioritization algorithm for intelligent terminal based on artificial immune algorithm. Firstly, different sequences of test case sets were used as the encoding of antibodies to initialize the antibody population; secondly, the Hemming distance was introduced as the concentration index of antibodies to calculate the incentive degree; finally, the antibodies were immunized to find the optimal test case set sequence. The experimental results showed that the algorithm based on the artificial immune algorithm was more capable of global search and less likely to fall into local optimum than the genetic algorithm, which indicated that the artificial immune algorithm was more stable and could better solve the test case prioritization problem.
Ključne riječi
artificial immunity algorithms; intelligent terminal; regression testing; test case prioritization
Hrčak ID:
264044
URI
Datum izdavanja:
7.11.2021.
Posjeta: 710 *