Comparing Methods for the Cross-Level Verification of SystemC Peripherals with Symbolic Execution
September 05, 2025 Β· Declared Dead Β· π IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Karl Aaron Rudkowski, Sallar Ahmadi-Pour, Rolf Drechsler
arXiv ID
2509.05504
Category
cs.PL: Programming Languages
Cross-listed
cs.AR
Citations
0
Venue
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Last Checked
4 months ago
Abstract
Virtual Prototypes (VPs) are important tools in modern hardware development. At high abstractions, they are often implemented in SystemC and offer early analysis of increasingly complex designs. These complex designs often combine one or more processors, interconnects, and peripherals to perform tasks in hardware or interact with the environment. Verifying these subsystems is a well-suited task for VPs, as they allow reasoning across different abstraction levels. While modern verification techniques like symbolic execution can be seamlessly integrated into VP-based workflows, they require modifications in the SystemC kernel. Hence, existing approaches modify and replace the SystemC kernel, or ignore the opportunity of cross-level scenarios completely, and would not allow focusing on special challenges of particular subsystems like peripherals. We propose CrosSym and SEFOS, two opposing approaches for a versatile symbolic execution of peripherals. CrosSym modifies the SystemC kernel, while SEFOS instead modifies a modern symbolic execution engine. Our extensive evaluation applies our tools to various peripherals on different levels of abstractions. Both tools' extensive sets of features are demonstrated for (1) different verification scenarios, and (2) identifying 300+ mutants. In comparison with each other, SEFOS convinces with the unmodified SystemC kernel and peripheral, while CrosSym offers slightly better runtime and memory usage. In comparison to the state-of-the-art, that is limited to Transaction Level Modelling (TLM), our tools offered comparable runtime, while enabling cross-level verification with symbolic execution.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Programming Languages
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions
R.I.P.
π»
Ghosted
Glow: Graph Lowering Compiler Techniques for Neural Networks
R.I.P.
π»
Ghosted
Learnable Programming: Blocks and Beyond
R.I.P.
π»
Ghosted
Scenic: A Language for Scenario Specification and Scene Generation
R.I.P.
π»
Ghosted
Vandal: A Scalable Security Analysis Framework for Smart Contracts
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted