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Failure test case generation method for model domain

A technology for test case generation and test cases, applied in neural learning methods, software testing/debugging, biological neural network models, etc., to improve the effect of defect location

Active Publication Date: 2021-04-20
CHONGQING UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the input that causes the program to fail usually occupies only a small portion of the input field
Therefore, researchers have made great efforts to generate failed test cases, but in view of the difficulty of generating in the input domain, the existing test case generation methods rarely start from generating failed test cases

Method used

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  • Failure test case generation method for model domain
  • Failure test case generation method for model domain
  • Failure test case generation method for model domain

Examples

Experimental program
Comparison scheme
Effect test

test Embodiment T

[0043] S10: data acquisition, given a program P containing defects, there is a set of original test cases T, and the output of each test case in the set of test cases T is known;

[0044] Give each test case in T to P for execution, and obtain the statement coverage information of each test case in program P;

[0045] At the same time, for each test case, compare the known output of the test case with the actual output after running the program P. If the actual output of each test case is the same as the known output, the label of the test case is 1, otherwise The label of this test case is 0;

[0046] The labels of all test cases form a label vector;

[0047] The statement coverage information and labels of all test cases in the program P constitute the original coverage matrix of the original test case set, denoted as TOrig, see figure 2 ; If the program has n statements and m test cases, the dimension of the coverage matrix is ​​m*n, the dimension of the label vector is m*...

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Abstract

The invention relates to a failure test case generation method for a model domain, and the method comprises the steps: firstly defining a minimum suspicious set, and extracting common features from all failure test cases; and then, for each failed test case in the model domain, on the basis of reserving the common characteristics of the failed test cases, mutating the information of the non-common characteristics so as to generate a new failed test case of the model domain; and finally, fusing the failure test cases of the newly added model domain into the original test case set, and carrying out defect positioning. According to the method, the variant nearest neighbor algorithm is used for generating the failure test case vector of the model domain, so that the purpose of improving the defect positioning effect is achieved, and compared with a traditional method for generating the test case from the input domain, the method is simpler and more effective, and a failure label does not need to be obtained through program execution.

Description

technical field [0001] The invention relates to a method for generating a failure test case, in particular to a method for generating a failure test case in a model domain. Background technique [0002] In the process of software development and maintenance, the purpose of software debugging is to find and fix errors in the software. It is a time-consuming and labor-intensive process that often requires a significant investment of effort and time from developers. In order to reduce the cost of debugging, researchers have proposed many methods to help debuggers find defects in programs. A typical process of locating program defects is as follows: Suppose there is a program P with a test case set T constructed from the input domain, after the program P executes all the test cases in T, it will generate an information matrix of the model domain, see attached figure 1 . Then use the suspicious value calculation formula to calculate the coverage information of the model domai...

Claims

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Application Information

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IPC IPC(8): G06F11/36G06N3/04G06N3/08
CPCY02D10/00
Inventor 雷晏张卓谢欢刘春燕鄢萌徐玲徐洲
Owner CHONGQING UNIV
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