敏感变量和感知机结合的测试预言生成方法

Translated title of the contribution: Generation Method for Test Oracle Based on Sensitive Variables and Linear Perceptron

Chun Yan Ma, Shang Ru Li, Hui Chao Wang, Lei Zhang, Tao Zhang

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

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.

Translated title of the contributionGeneration Method for Test Oracle Based on Sensitive Variables and Linear Perceptron
Original languageChinese (Traditional)
Pages (from-to)1450-1463
Number of pages14
JournalRuan Jian Xue Bao/Journal of Software
Volume30
Issue number5
DOIs
StatePublished - 1 May 2019

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