Automatic generation of trusted test cases based on adaptive genetic algorithm. Issue 4 (April 2021)
- Record Type:
- Journal Article
- Title:
- Automatic generation of trusted test cases based on adaptive genetic algorithm. Issue 4 (April 2021)
- Main Title:
- Automatic generation of trusted test cases based on adaptive genetic algorithm
- Authors:
- Wu, Danyang
Yu, Xuejun - Abstract:
- Abstract: In recent years, the development and operating environment of software system has developed from the traditional closed and static environment to an open and dynamic Internet environment. The software system has become increasingly large and difficult to control, and the emergence of defects and loopholes is inevitable, resulting in the problem of software credibility [1]. How to improve the credibility of software has become the core hot issue in the field of software engineering [2]. In this paper, we will test the credibility of web applications based on the idea of "consistency of words and deeds". By analyzing the characteristics of web applications, define the trusted behavior statement rules of web applications, and combine the genetic algorithm to realize the automatic generation of trusted test cases. Because the basic genetic algorithm has the shortcoming of "premature convergence", in this paper, we will use adaptive parameters to implement genetic algorithm, and through the experimental verification, the adaptive parameter genetic algorithm can effectively improve the efficiency of searching the optimal solution.
- Is Part Of:
- Journal of physics. Volume 1865:Issue 4(2021)
- Journal:
- Journal of physics
- Issue:
- Volume 1865:Issue 4(2021)
- Issue Display:
- Volume 1865, Issue 4 (2021)
- Year:
- 2021
- Volume:
- 1865
- Issue:
- 4
- Issue Sort Value:
- 2021-1865-0004-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-04
- Subjects:
- Software credibility -- behavior declaration -- genetic algorithm -- Adaptive parameters -- automatic generation of trusted test cases
Physics -- Congresses
530.5 - Journal URLs:
- http://www.iop.org/EJ/journal/1742-6596 ↗
http://ioppublishing.org/ ↗ - DOI:
- 10.1088/1742-6596/1865/4/042074 ↗
- Languages:
- English
- ISSNs:
- 1742-6588
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5036.223000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 25646.xml