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System Development & Application
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App. Res. of Comp. Printed Article
Vol. 36, 2019 No. 7
2075-2080

Search-based hierarchical regression test suite augmentation method

Wang Shuyan
Gao Lu
Sun Jiaze
School of Computer Science & Technology, Xi'an University of Posts & Telecommunications, Xi'an 710121, China
DOI: 10.19734/j.issn.1001-3695.2018.05.0272

Abstract

It is difficult for the original test data to meet the requirements of the new version of software testing in regression testing, thus this paper proposed a search-based hierarchical regression test suite augmentation method to solve the problem. The method mainly included obtaining the target function set module and the test data generation module. Firstly, it abstracted function call graph from the new program, and built function coverage information by using function traces and original test case set. Afterwards, it used Bayesian conditional probability to choose the target function set through calculating. Then it used Hadamard matrix to design the orthogonal population, and initialized population with the combination of the orthogonal population and existing test data set. Finally, it used the memetic algorithm to generate test data for target functions. This paper compared the proposed algorithm with the random algorithm based, the genetic algorithm based and particle swarm algorithm based test data augmentation methods on four benchmark programs. The results show that generation efficiency of the proposed method is improved on average by approximately 95.2%, 78.2% and 50.5% respectively, the error detection ability of the test case is improved on average by approximately 47.9%, 33.6% and 18.2% respectively. The experimental results show that the proposed method is more suitable for regression test suite augmentation.

Foundation Support

陕西省工业攻关项目(2017GY-092)
西安邮电大学创新基金重点项目(CXJJ2017020)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.05.0272
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 7
Section: System Development & Application
Pages: 2075-2080
Serial Number: 1001-3695(2019)07-035-2075-06

Publish History

[2019-07-05] Printed Article

Cite This Article

王曙燕, 高露, 孙家泽. 基于搜索的分层回归测试数据集扩增方法 [J]. 计算机应用研究, 2019, 36 (7): 2075-2080. (Wang Shuyan, Gao Lu, Sun Jiaze. Search-based hierarchical regression test suite augmentation method [J]. Application Research of Computers, 2019, 36 (7): 2075-2080. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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