MLD: An Intelligent Memory Leak Detection Scheme Based on Defect Modes in Smart Grids

TL;DR

This paper introduces an intelligent memory leak detection scheme for smart grid software that improves detection speed and accuracy by analyzing defect modes and employing fuzzy matching algorithms.

Contribution

It presents a novel defect mode-based detection scheme with a state machine model and function summary method to enhance efficiency and accuracy in identifying memory leaks.

Findings

High detection speed and accuracy demonstrated in experiments

Effective identification of memory leak defects in smart grid software

Ensures safer operation of smart grid systems

Abstract

With the expansion of the software scale and complexity of smart grid systems, the detection of smart grid software defects has become a research hotspot. Because of the large scale of the existing smart grid software code, the efficiency and accuracy of the existing smart grid defect detection algorithms are not high. We propose an intelligent memory leak detection scheme based on defect modes MLD in smart grid. Based on the analysis of existing memory leak defect modes, we summarize memory operation behaviors (allocation, release and transfer) and present a state machine model. We employ a fuzzy matching algorithm based on regular expression to determine the memory operation behaviors and then analyze the change in the state machine to assess the vulnerability in the source code. To improve the efficiency of detection and solve the problem of repeated detection at the function call point, we propose a function summary method for memory operation behaviors. The experimental results demonstrate that the method we proposed has high detection speed and accuracy. The algorithm we proposed can identify the defects of the smart grid operation software and ensure the safe operation of the grid.