SEPE-SQED: Symbolic Quick Error Detection by Semantically Equivalent Program Execution
April 04, 2024 Β· Declared Dead Β· π Design Automation Conference
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Yufeng Li, Qiusong Yang, Yiwei Ci, Enyuan Tian
arXiv ID
2404.03172
Category
cs.SE: Software Engineering
Cross-listed
cs.AR,
eess.SY
Citations
2
Venue
Design Automation Conference
Last Checked
4 months ago
Abstract
Symbolic quick error detection (SQED) has greatly improved efficiency in formal chip verification. However, it has a limitation in detecting single-instruction bugs due to its reliance on the self-consistency property. To address this, we propose a new variant called symbolic quick error detection by semantically equivalent program execution (SEPE-SQED), which utilizes program synthesis techniques to find sequences with equivalent meanings to original instructions. SEPE-SQED effectively detects single-instruction bugs by differentiating their impact on the original instruction and its semantically equivalent program (instruction sequence). To manage the search space associated with program synthesis, we introduce the CEGIS based on the highest priority first algorithm. The experimental results show that our proposed CEGIS approach improves the speed of generating the desired set of equivalent programs by 50% in time compared to previous methods. Compared to SQED, SEPE-SQED offers a wider variety of instruction combinations and can provide a shorter trace for triggering bugs in certain scenarios.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Software Engineering
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Microservices: yesterday, today, and tomorrow
π
π
The Cartographer
A Survey of Machine Learning for Big Code and Naturalness
R.I.P.
π»
Ghosted
An Overview on Smart Contracts: Challenges, Advances and Platforms
R.I.P.
π»
Ghosted
Slither: A Static Analysis Framework For Smart Contracts
R.I.P.
π»
Ghosted
ContractFuzzer: Fuzzing Smart Contracts for Vulnerability Detection
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