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 |
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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 | |
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 |
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ISSN (Print) | 0270-5257 |
Conference
Conference | 13th ACM/IEEE International Workshop on Automation of Software Test, AST 2018 |
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Country/Territory | Sweden |
City | Gothenburg |
Period | 28/05/18 → 29/05/18 |
Bibliographical note
Publisher Copyright:© 2018 ACM.
Keywords
- memory corruption
- memory fault detection
- runtime fault detection