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MLD: An Intelligent Memory Leak Detection Scheme Based on Defect Modes in Software.

Ling Yuan1, Siyuan Zhou1, Peng Pan1

  • 1Department of Computer Science, Huazhong University of Science and Technology, Wuhan 430074, China.

Entropy (Basel, Switzerland)
|July 27, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces an intelligent memory leak detection (MLD) scheme for complex software. The MLD scheme enhances detection speed and accuracy by analyzing memory operation behaviors and utilizing a function summary method.

Keywords:
defect modesmemory leak detection algorithmsoftware defect detectionsoftware detection

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Area of Science:

  • Software Engineering
  • Computer Science
  • Cybersecurity

Background:

  • The increasing scale and complexity of multimedia software necessitate advanced defect detection methods.
  • Existing software defect detection algorithms often suffer from low efficiency and accuracy due to large codebases.

Purpose of the Study:

  • To propose an intelligent memory leak detection (MLD) scheme.
  • To improve the efficiency and accuracy of software defect detection.

Main Methods:

  • Summarized memory operation behaviors (allocation, release, transfer) and developed a state machine model.
  • Employed a fuzzy matching algorithm with regular expressions to identify memory operations.
  • Implemented a function summary method to optimize detection efficiency and prevent repeated analysis.

Main Results:

  • The proposed MLD scheme demonstrated high detection speed and accuracy in experimental evaluations.
  • The algorithm effectively identifies software defects, thereby reducing vulnerability to attacks.

Conclusions:

  • The intelligent memory leak detection scheme offers a significant improvement over existing methods.
  • This approach enhances software security and operational safety by mitigating memory leak vulnerabilities.