A Method for Test Case Generation by Improved Genetic Algorithm Based on Static Structure of Procedure

被引:0
|
作者
Wen Jing [1 ]
Zhang Yikun [1 ]
Zhao Ming [1 ,2 ]
Chen Hao [1 ]
Hei Xinhong [1 ]
Shen Jianxiong [3 ]
机构
[1] XiAn Univ Technol, Sch Comp Sci & Informat Technol, Xian, Shaanxi, Peoples R China
[2] Suzhou Insight Cloud Informat Technol Co Ltd, Suzhou, Peoples R China
[3] Shanghai Dev Res Ctr Econ & Informatizat, Dept Internet Econ Consultancy, Shanghai, Peoples R China
关键词
test case; full-automatic; code coverage; static structure;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Software testing is an important method to guarantee software quality. For the large-scale complex software, some mistakes or errors will easily be overlooked if programs are detected only by manual work. Therefore, a full-automatic system is necessary to rapidly cover all program logics through calculation to achieve input and output; besides, the system can assist to generate a large number of test cases before manual intervention, and can find out some software defects to assist manual detection to complete compiling work of all test cases. In this paper, a combination of the static structure of procedure and improved genetic algorithm is proposed in order to implement a fully automatic test case generating technology, enhance the generating efficiency and coverage rate of codes, and also can help to save a lot of time in manual testing.
引用
收藏
页码:1499 / 1504
页数:6
相关论文
共 50 条
  • [31] An improved OTSU method based on Genetic Algorithm
    Shang, Wei
    Cheng, Yan-fen
    Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications, 2016, 71 : 1656 - 1661
  • [32] A novel test case generation method based on program structure diagram
    Wu, Xianghu
    Qu, Mingcheng
    Tao, Yongchao
    Wang, Guannan
    Dong, Ziyu
    INTERNATIONAL JOURNAL OF GRID AND UTILITY COMPUTING, 2019, 10 (04) : 326 - 333
  • [33] Combinatorial Test Case Generation Based on ROBDD and Improved Particle Swarm Optimization Algorithm
    Li, Shunxin
    Song, Yinglei
    Zhang, Yaying
    APPLIED SCIENCES-BASEL, 2024, 14 (02):
  • [34] Research of Automatic Test Case Generation Algorithm Based on Improved Particle Swarm Optimization
    Wu, Weiwei
    PROCEEDINGS OF THE 2016 4TH INTERNATIONAL CONFERENCE ON MACHINERY, MATERIALS AND COMPUTING TECHNOLOGY, 2016, 60 : 1558 - 1562
  • [35] Improved genetic algorithm for multiple path coverage test data generation
    Institute of Database and Multimedia, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China
    Jisuanji Gongcheng, 2006, 13 (196-197+205):
  • [36] A Genetic Algorithm-Based Heuristic Method for Test Set Generation in Reversible Circuits
    Nagamani, A. N.
    Anuktha, S. N.
    Nanditha, N.
    Agrawal, Vinod Kumar
    IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS, 2018, 37 (02) : 324 - 336
  • [37] IMPROVED ANNEALING-GENETIC ALGORITHM FOR TEST CASE PRIORITIZATION
    Wang, Zan
    Zhao, Xiaobin
    Zou, Yuguo
    Yu, Xue
    Wang, Zhenhua
    COMPUTING AND INFORMATICS, 2017, 36 (03) : 705 - 732
  • [38] Test Case Generation for Vulnerability Detection Using Genetic Algorithm
    Shuai, Bo
    Li, Haifeng
    Wang, Jian
    Zhang, Quan
    Tang, Chaojing
    PROCEEDINGS OF THE 2015 4TH NATIONAL CONFERENCE ON ELECTRICAL, ELECTRONICS AND COMPUTER ENGINEERING ( NCEECE 2015), 2016, 47 : 1198 - 1203
  • [39] Initialization method of genetic algorithm based on improved clustering algorithm
    Li, Hao
    Jiang, Xuesong
    Wei, Xiumei
    PROCEEDINGS OF THE 2022 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE COMPANION, GECCO 2022, 2022, : 447 - 450