Quick call path generation for program analysis

Zhaopeng Liu; Kui Lu

doi:10.1117/12.3034912

11 July 2024 Quick call path generation for program analysis

Zhaopeng Liu, Kui Lu

Proceedings Volume 13210, Third International Symposium on Computer Applications and Information Systems (ISCAIS 2024); 1321003 (2024) https://doi.org/10.1117/12.3034912
Event: Third International Symposium on Computer Applications and Information Systems (ISCAIS 2023), 2024, Wuhan, China

Abstract

The complexity of modern software has resulted in an increase in vulnerabilities and bugs. Identifying all vulnerabilities is challenging due to technological limitations, so patching bugs found during the usage phase is necessary. This leads to high maintenance costs. Furthermore, undisclosed vulnerabilities can be easily exploited by hackers. Static code analysis is a technique used to identify bugs and defects in a program during the development phase. This can greatly improve the reliability and quality of the code. However, it may have the disadvantage of low analysis efficiency. To tackle this issue, we present FCG, an algorithm for rapid call-path generation based on call graphs. FCG can swiftly identify all feasible function call sequences that lead to a particular location in a program, thereby enhancing efficiency for subsequent analysis. In this paper, we conduct an experimental comparison between the FCG algorithm and its closest analogue, DFS. The results demonstrate that FCG outperforms DFS in the presence of a large amount of code.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Zhaopeng Liu and Kui Lu "Quick call path generation for program analysis", Proc. SPIE 13210, Third International Symposium on Computer Applications and Information Systems (ISCAIS 2024), 1321003 (11 July 2024); https://doi.org/10.1117/12.3034912

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KEYWORDS

Analytical research

Detection and tracking algorithms

Software development

Algorithm development

Computing systems

Deep learning

Open source software

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