Source Code Analysis for Static Prediction of Dynamic Memory Usage
Sangwho Kim, Jae‐Cheol Ryou · 2019
We studied source code analysis techniques to predict statically how real programs work and use memory. If we can recognize problems of memory usage in the source code, we are able to prevent them and improve security in the software development phase. The problem detection techniques which are already existed can detect whether the program includes weak code such as Common Vulnerabilities and Exposures, Common Weakness Enumeration. However, these methods are not useful for finding problems in programs that do not include OpenSource. because they use hash value or pattern of weak code contained in OpenSource. Therefore, we propose a static prediction technique for dynamic memory usage with source code analysis without using techniques such as similarity detection. Also, we present how to calculate the values used for static prediction from the source code.