Memory corruption detecting method using static variables and dynamic memory usage

Jihyun Park; Changsun Park; Byoungju Choi; Gihun Chang

doi:10.1145/3194733.3194741

Memory corruption detecting method using static variables and dynamic memory usage

Jihyun Park, Changsun Park, Byoungju Choi, Gihun Chang

Computer Science & Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Memory fault detection has been continuously studied and various detection methods exist. However, there are still remains many memory defects that are difficult to debug. Memory corruption is one of those defects that often cause a system crash. However, there are many cases where the location of the crash is different from the actual location causing the actual memory corruption. These defects are difficult to solve by existing methods. In this paper, we propose a method to detect real time memory defects by using static global variables derived from execution binary file and dynamic memory usage obtained by tracing memory related functions. We implemented the proposed method as a tool and applied it to the application running on the IoTivity platform. Our tool detects defects very accurately with low overhead even for those whose detected location and the location of its cause are different.

Original language	English
Title of host publication	Proceedings 2018 ACM/IEEE 13th International Workshop on Automation of Software Test, AST 2018
Publisher	IEEE Computer Society
Pages	46-52
Number of pages	7
ISBN (Electronic)	9781450357432
DOIs	https://doi.org/10.1145/3194733.3194741
State	Published - 28 May 2018
Event	13th ACM/IEEE International Workshop on Automation of Software Test, AST 2018 - Gothenburg, Sweden Duration: 28 May 2018 → 29 May 2018

Publication series

Name	Proceedings - International Conference on Software Engineering
ISSN (Print)	0270-5257

Conference

Conference	13th ACM/IEEE International Workshop on Automation of Software Test, AST 2018
Country/Territory	Sweden
City	Gothenburg
Period	28/05/18 → 29/05/18

Keywords

memory corruption
memory fault detection
runtime fault detection

Access to Document

10.1145/3194733.3194741

Cite this

Park, J., Park, C., Choi, B., & Chang, G. (2018). Memory corruption detecting method using static variables and dynamic memory usage. In Proceedings 2018 ACM/IEEE 13th International Workshop on Automation of Software Test, AST 2018 (pp. 46-52). (Proceedings - International Conference on Software Engineering). IEEE Computer Society. https://doi.org/10.1145/3194733.3194741

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title = "Memory corruption detecting method using static variables and dynamic memory usage",

abstract = "Memory fault detection has been continuously studied and various detection methods exist. However, there are still remains many memory defects that are difficult to debug. Memory corruption is one of those defects that often cause a system crash. However, there are many cases where the location of the crash is different from the actual location causing the actual memory corruption. These defects are difficult to solve by existing methods. In this paper, we propose a method to detect real time memory defects by using static global variables derived from execution binary file and dynamic memory usage obtained by tracing memory related functions. We implemented the proposed method as a tool and applied it to the application running on the IoTivity platform. Our tool detects defects very accurately with low overhead even for those whose detected location and the location of its cause are different.",

keywords = "memory corruption, memory fault detection, runtime fault detection",

author = "Jihyun Park and Changsun Park and Byoungju Choi and Gihun Chang",

note = "Publisher Copyright: {\textcopyright} 2018 ACM.; 13th ACM/IEEE International Workshop on Automation of Software Test, AST 2018 ; Conference date: 28-05-2018 Through 29-05-2018",

year = "2018",

month = may,

day = "28",

doi = "10.1145/3194733.3194741",

language = "English",

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Park, J, Park, C, Choi, B & Chang, G 2018, Memory corruption detecting method using static variables and dynamic memory usage. in Proceedings 2018 ACM/IEEE 13th International Workshop on Automation of Software Test, AST 2018. Proceedings - International Conference on Software Engineering, IEEE Computer Society, pp. 46-52, 13th ACM/IEEE International Workshop on Automation of Software Test, AST 2018, Gothenburg, Sweden, 28/05/18. https://doi.org/10.1145/3194733.3194741

Memory corruption detecting method using static variables and dynamic memory usage. / Park, Jihyun; Park, Changsun; Choi, Byoungju et al.
Proceedings 2018 ACM/IEEE 13th International Workshop on Automation of Software Test, AST 2018. IEEE Computer Society, 2018. p. 46-52 (Proceedings - International Conference on Software Engineering).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - Memory fault detection has been continuously studied and various detection methods exist. However, there are still remains many memory defects that are difficult to debug. Memory corruption is one of those defects that often cause a system crash. However, there are many cases where the location of the crash is different from the actual location causing the actual memory corruption. These defects are difficult to solve by existing methods. In this paper, we propose a method to detect real time memory defects by using static global variables derived from execution binary file and dynamic memory usage obtained by tracing memory related functions. We implemented the proposed method as a tool and applied it to the application running on the IoTivity platform. Our tool detects defects very accurately with low overhead even for those whose detected location and the location of its cause are different.

AB - Memory fault detection has been continuously studied and various detection methods exist. However, there are still remains many memory defects that are difficult to debug. Memory corruption is one of those defects that often cause a system crash. However, there are many cases where the location of the crash is different from the actual location causing the actual memory corruption. These defects are difficult to solve by existing methods. In this paper, we propose a method to detect real time memory defects by using static global variables derived from execution binary file and dynamic memory usage obtained by tracing memory related functions. We implemented the proposed method as a tool and applied it to the application running on the IoTivity platform. Our tool detects defects very accurately with low overhead even for those whose detected location and the location of its cause are different.

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Memory corruption detecting method using static variables and dynamic memory usage

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