Automated Memory Corruption Detection through Analysis of Static Variables and Dynamic Memory Usage

Various methods for memory fault detection have been developed through continuous study. However, many memory defects remain that are difficult to resolve. Memory corruption is one such defect, and can cause system crashes, making debugging important. However, the locations of the system crash and the actual source of the memory corruption often differ, which makes it difficult to solve these defects using the existing methods. In this paper, we propose a method that detects memory defects in which the location causing the defect is different from the actual location, providing useful information for debugging. This study presents a method for the real-time detection of memory defects in software based on data obtained through static and dynamic analysis. The data we used for memory defect analysis were (1) information of static global variables (data, address, size) derived through the analysis of executable binary files, and (2) dynamic memory usage information obtained by tracking memory-related functions that are called during the real-time execution of the process. We implemented the proposed method as a tool and applied it to applications running on the Linux. The results indicate the defect-detection efficacy of our tool for this application. Our method accurately detects defects with different cause and detected-fault locations, and also requires a very low overhead for fault detection.

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Single Fault Diagnosis Method of Sensors in Cascade System Based on Data-Driven

Sensors ◽

10.3390/s21217340 ◽

2021 ◽

Vol 21 (21) ◽

pp. 7340

Author(s):

Wenbo Na ◽

Siyu Guo ◽

Yanfeng Gao ◽

Jianxing Yang ◽

Junjie Huang

Keyword(s):

Fault Diagnosis ◽

Fault Detection ◽

Real Time ◽

Fault Detection And Diagnosis ◽

Data Driven ◽

Cascade System ◽

The Real ◽

Single Fault ◽

Time Calibration ◽

Diagnosis Method

The reliability and safety of the cascade system, which is widely applied, have attached attention increasingly. Fault detection and diagnosis can play a significant role in enhancing its reliability and safety. On account of the complexity of the double closed-loop system in operation, the problem of fault diagnosis is relatively complex. For the single fault of the second-order valued system sensors, a real-time fault diagnosis method based on data-driven is proposed in this study. Off-line data is employed to establish static fault detection, location, estimation, and separation models. The static models are calibrated with on-line data to obtain the real-time fault diagnosis models. The real-time calibration, working flow and anti-interference measures of the real-time diagnosis system are given. Experiments results demonstrate the validity and accuracy of the fault diagnosis method, which is suitable for the general cascade system.

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The Real-Time Vision System for Fabric Defect Detection with Combined Approach

Lecture Notes in Computer Science - Image and Graphics ◽

10.1007/978-3-319-21969-1_41 ◽

2015 ◽

pp. 460-473

Author(s):

Pengfei Li ◽

Zhuo Zhao ◽

Lei Zhang ◽

Hongwei Zhang ◽

Junfeng Jing

Keyword(s):

Real Time ◽

Defect Detection ◽

Vision System ◽

Combined Approach ◽

The Real ◽

Fabric Defect Detection ◽

Fabric Defect

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Model Analysis for the Key Component of Carriage Hoists

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.174-177.1792 ◽

2012 ◽

Vol 174-177 ◽

pp. 1792-1795

Author(s):

Bin Zhao ◽

Hai Long Zhou ◽

Can Wang ◽

Ling Li Meng ◽

Hong Guang Ma ◽

...

Keyword(s):

Finite Element Method ◽

Finite Element ◽

Dynamic Analysis ◽

Working Conditions ◽

Weight Reduction ◽

Model Analysis ◽

The Finite Element Method ◽

The Real ◽

Static And Dynamic Analysis ◽

Reduction Costs

Based on the real working conditions of the carriage hoists, the Finite Element Method (FEM) software is used to make static and dynamic analysis for the key component and then to optimize its components according to the analysis results to achieve some goals, e.g., simplified structure, weight reduction, costs reduction, etc.. The process provides useful references for the design of carriage hoists.

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Approach for Detecting Soft Faults in GPS/INS Integrated Navigation based on LS-SVM and AIME

Journal of Navigation ◽

10.1017/s037346331600076x ◽

2017 ◽

Vol 70 (3) ◽

pp. 561-579 ◽

Cited By ~ 12

Author(s):

Lina Zhong ◽

Jianye Liu ◽

Rongbing Li ◽

Rong Wang

Keyword(s):

Kalman Filter ◽

Fault Detection ◽

Real Time ◽

Support Vector ◽

Observation Data ◽

Navigation Systems ◽

Integrated Navigation ◽

The Real ◽

Time Performance ◽

Soft Fault

In life-critical applications, the real-time detection of faults is very important in Global Positioning System/Inertial Navigation System (GPS/INS) integrated navigation systems. A new fault detection method for soft fault detection is developed in this paper with the purpose of improving real-time performance. In general, the innovation information obtained from a Kalman filter is used for test statistic calculations in Autonomous Integrity Monitored Extrapolation (AIME). However, the innovation of the Kalman filter is degraded by error tracking and closed-loop correction effects, leading to time delays in soft fault detection. Therefore, the key issue of improving real-time performance is providing accurate innovation to AIME. In this paper, the proposed algorithm incorporates Least Squares-Support Vector Machine (LS-SVM) regression theory into AIME. Because the LS-SVM has a good regression and prediction performance, the proposed method provides replaced innovation obtained from the LS-SVM driven by real-time observation data. Based on the replaced innovation, the test statistics can follow fault amplitudes more accurately; finally, the real-time performance of soft fault detection can be improved. Theoretical analysis and physical simulations demonstrate that the proposed method can effectively improve the detection instantaneity.

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Static and dynamic analysis of real-time systems

Proceedings of the 30th annual Southeast regional conference on - ACM-SE 30 ◽

10.1145/503720.503801 ◽

1992 ◽

Cited By ~ 1

Author(s):

Wael Elseaidy

Keyword(s):

Dynamic Analysis ◽

Real Time ◽

Real Time Systems ◽

Static And Dynamic Analysis ◽

Time Systems

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The real-time behavior of dynamic memory management in C++

Proceedings Real-Time Technology and Applications Symposium ◽

10.1109/rttas.1995.516211 ◽

2002 ◽

Cited By ~ 8

Author(s):

K.D. Nilsen ◽

Hong Gao

Keyword(s):

Real Time ◽

Memory Management ◽

Time Behavior ◽

Dynamic Memory ◽

The Real ◽

Dynamic Memory Management

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The Real-Time Fault Analysis of Personal Escape Suit Based on the Object Oriented Model

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.1030-1032.1837 ◽

2014 ◽

Vol 1030-1032 ◽

pp. 1837-1840

Author(s):

Yao Tang ◽

Pei Hu ◽

Qian Hao ◽

Shan Yi Fang ◽

Shi Long Xing

Keyword(s):

Fault Detection ◽

Real Time ◽

Fault Tree ◽

Object Oriented ◽

Fault Analysis ◽

Tree Model ◽

The Real ◽

Actual Equipment ◽

Analysis System

According the actual equipment support demand of rapidly floating escape suit, this paper built the object oriented fault tree model for the rapidly floating escape suit, detailed descried the planning and realization method of the fault detection and analysis system with actual examples.

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