Outrunning Big KATs: Efficient Decision Procedures for Variants of GKAT
By: Cheng Zhang , Qiancheng Fu , Hang Ji and more
This paper presents several efficient decision procedures for trace equivalence of GKAT automata, which make use of on-the-fly symbolic techniques via SAT solvers. To demonstrate applicability of our algorithms, we designed symbolic derivatives for CF-GKAT, a practical system based on GKAT designed to validate control-flow transformations. We implemented the algorithms in Rust and evaluated them on both randomly generated benchmarks and real-world control-flow transformations. Indeed, we observed order-of-magnitude performance improvements against existing implementations for both KAT and CF-GKAT. Notably, our experiments also revealed a bug in Ghidra, an industry-standard decompiler, highlighting the practical viability of these systems.
Similar Papers
Weighted GKAT: Completeness and Complexity
Logic in Computer Science
Makes computer programs easier to check for mistakes.
KG-Augmented Executable CoT for Mathematical Coding
Artificial Intelligence
Helps computers solve math and write code better.
KAT-Coder Technical Report
Computation and Language
Helps computers write code like a human.