Generation Method for Test Oracle Based on Sensitive Variables and Linear Perceptron
Author:
Affiliation:

Clc Number:

Fund Project:

National Natural Science Foundation of China (61103003); Aerospace Fund (2018KC160026); Shanghai Aerospace Science and Technology Support Program (2017MC160014)

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    Test oracle generation technology is one of the hotspots in the testing field of software engineering. There are no historical test case sets available, which are common assumptions about existing test oracle generation techniques. However, this assumption may not always hold, and where it does not, there may be a missed opportunity; perhaps the pre-existing test cases could be used to assist the automated oracle generation of new test cases. In the case of the existing test case set, an automatic test oracle generation method for a new test case based on sensitive variables and linear perceptrons is proposed. Firstly, the statement coverage and memory value set executed by some known test cases are collected, and a set of test cases with high similarity to the execution coverage information of the new test case is computed. Secondly, the memory sensitive variable set solving algorithm of the program at a given breakpoint is given. Thirdly, the known test case set as the training set and the perceptron is used to solve the threshold value at each breakpoint. And on this base an automatic oracle generation method of the new test case is proposed. Finally, 129 fault versions of seven programs are used as experimental objects to generate test oracles of 14 300 new test cases. The empirical evaluation shows that the generated test oracle can achieve 96.2% accuracy on average. The results of the research can form the "snowball effect" of the test case set construction, and iteratively automatically generate test oracles for new test cases.

    Reference
    Related
    Cited by
Get Citation

马春燕,李尚儒,王慧朝,张磊,张涛.敏感变量和感知机结合的测试预言生成方法.软件学报,2019,30(5):1450-1463

Copy
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:August 31,2018
  • Revised:October 31,2018
  • Adopted:
  • Online: May 08,2019
  • Published:
You are the firstVisitors
Copyright: Institute of Software, Chinese Academy of Sciences Beijing ICP No. 05046678-4
Address:4# South Fourth Street, Zhong Guan Cun, Beijing 100190,Postal Code:100190
Phone:010-62562563 Fax:010-62562533 Email:jos@iscas.ac.cn
Technical Support:Beijing Qinyun Technology Development Co., Ltd.

Beijing Public Network Security No. 11040202500063