Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications

Static memory leak detection based on a new memory model

Authors
Hangyuan Liu, Hua Zhang
Corresponding Author
Hangyuan Liu
Available Online November 2016.
DOI
10.2991/aiea-16.2016.69How to use a DOI?
Keywords
Memory leaks; Static detection; Memory model.
Abstract

Memory leaks of static analysis need to be more accurate to determine memory state of different times. The current static memory model has a high false positive rate and false negative rate, mainly because the current memory model cannot accurately represent memory state and memory hierarchy. In this paper, a domain-sensitive memory model that can represent the memory hierarchy is proposed. On this basis, a static memory leak detection method is implemented. The experimental results show that the model has high accuracy and detection efficiency.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications
Series
Advances in Computer Science Research
Publication Date
November 2016
ISBN
10.2991/aiea-16.2016.69
ISSN
2352-538X
DOI
10.2991/aiea-16.2016.69How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Hangyuan Liu
AU  - Hua Zhang
PY  - 2016/11
DA  - 2016/11
TI  - Static memory leak detection based on a new memory model
BT  - Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications
PB  - Atlantis Press
SP  - 389
EP  - 394
SN  - 2352-538X
UR  - https://doi.org/10.2991/aiea-16.2016.69
DO  - 10.2991/aiea-16.2016.69
ID  - Liu2016/11
ER  -