Computer Science ›› 2021, Vol. 48 ›› Issue (11A): 88-92.doi: 10.11896/jsjkx.210200096

• Intelligent Computing • Previous Articles     Next Articles

Multiple Fault Localization Method Based on Deep Convolutional Network

ZHANG Hui   

  1. School of Computer Science,Jiangsu University of Science and Technology,Zhenjiang,Jiangsu 212003,China
  • Online:2021-11-10 Published:2021-11-12
  • About author:ZHANG Hui,born in 1982,Ph.D,lec-turer.Her main research interests include fault localization and software testing.

Abstract: Most of the current fault localization methods solve single fault localization,but the faults are related to each other.How to find the relationship between these faults and the test results and the relationship between the faults,and reduce the impact of coincidental correct test cases and similar test cases on the suspiciousness of sentences is very important to improve the efficiency of multiple fault localization.In order to solve the above problems,this paper proposes a multiple fault localization method based on deep convolutional network.A set of suspiciousness with high accuracy is obtained through a deep convolutional network with a special structure,and then applied to forward slicing and backward slicing,the correlation between faults and faults is found to locate multiple faults.Experiments show that the multiple fault localization efficiency of the method in this paper is stronger than that of the existing classic fault localization methods.

Key words: Deep convolutional network, Fault localization, Slicing

CLC Number: 

  • TP311.5
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