Do you have 5 min? Improving Call Graph Analysis with Runtime Information
Constructing precise and sound call graphs is fundamental for effective static analysis, yet it remains a significant challenge in today's software. Traditionally, researchers have developed sophisticated algorithms to address this issue, often resulting in increased computational costs. But what if we could provide a simple, cost-effective way to improve call graphs drastically?
Authors
- Marc Miltenberger (ORCID: https://orcid.org/0000-0002-3806-0522)
- Steven Arzt (ORCID: https://orcid.org/0000-0002-5807-9431)
- Jacques Klein (ORCID: https://orcid.org/0000-0003-4052-475X)
- Marco Alecci (ORCID: https://orcid.org/0000-0002-5963-4599)
- Tegawendé François Bissyandé (ORCID: https://orcid.org/0000-0001-7270-9869)
- Jordan Samhi (ORCID: https://orcid.org/0000-0001-6052-6184)
Institutions
- University of Luxembourg (LU)
- Fraunhofer Institute for Secure Information Technology (DE)
Publication Details
- Published
- 2025-06-23
- DOI
- https://doi.org/10.1145/3696630.3728495
- Primary Topic
- Advanced Malware Detection Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Fonds National de la Recherche Luxembourg
- Bundesministerium für Bildung und Forschung