Computer Software Fault Location Method Based on Machine Vision and Image Processing

Authors

  • Wei Yan Police Information Department, Liaoning Police College, Dalian 116036, Liaoning, China
  • Chen Yang School of Software, Dalian University of Foreign Languages, Dalian 116044, Liaoning, China

Abstract

With the rapid development of science and technology, software applications have penetrated various industries, and the requirements for software systems have become increasingly higher. A variety of software systems have gradually changed people’s lives and their economies. When people demand more and more software, software failures tend to occur. In order to reduce the harm caused by software errors, this paper proposes a computer software fault location method based on machine vision and image processing. First, an analysis was conducted of the graph mining technology, and then an experiment was conducted to compare the two different graph reduction methods in series and parallel to determine their fault location efficiency. According to the experimental results, when the number of nodes was small, the time consumed by serial reduction in fault
location was shorter. However, when the number of nodes increased, the advantages of parallel reduction became increasingly obvious. When the number of nodes was 5646, the efficiency reached 55.22%, which significantly improved the efficiency of fault location. This can help programmers to locate and repair the application faults, improve the performance of software security, and reduce the loss caused by software failure.

Keywords: software fault location; machine vision; image processing; graph mining technology

Cite As

W. Yan, C. Yang, "Computer Software Fault Location Method Based on Machine Vision and Image
Processing", Engineering Intelligent Systems, vol. 33 no. 6, pp. 611-619, 2025.

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Published

2025-11-01

Issue

Vol. 33 No. 6 (2025): International Journal of Engineering Intelligent Systems

Section

Article

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