FM2021Top-tier venue
Trace Abstraction-Based Verification for Uninterpreted Programs
Weijiang Hong, Zhenbang Chen, Yide Du, Ji Wang
Abstract
The verification of uninterpreted programs is undecidable in general. This paper proposes to employ counterexample-guided abstraction refinement (CEGAR) framework for verifying uninterpreted programs. Different from the existing interpolant-based trace abstraction, we propose a congruence-based trace abstraction method for infeasible counterexample paths to refine the program's abstraction model, which is designed specifically for uninterpreted programs. Besides, we propose an optimization method that utilizes the decidable verification result for coherent uninterpreted programs to improve the CEGAR framework's efficiency. We have implemented our verification method and evaluated it on two kinds of benchmark programs. Compared with the state-ofthe-art, our method is more effective and efficient, and achieves 3.6x speedups on average.
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Install the CLIlune papers fulltext 35154a50-1f8d-496e-9d60-a8813ba69553Cited by top-tier papers2
- TAAF: A Trace Abstraction and Analysis Framework Synergizing Knowledge Graphs and LLMsAlireza Ezaz, Ghazal Khodabandeh, Majid Babaei, Naser Ezzati-JivanICSE 2026
- EUFⁿ: A Decidable Extension to the Theory of Equality with Uninterpreted FunctionsYide Du, Zhenbang Chen, Weijiang Hong, Wei DongOOPSLA 2026
Builds on2
- Deciding memory safety for single-pass heap-manipulating programsUmang Mathur, Adithya Murali, Paul Krogmeier, P. Madhusudan et al.POPL 2020 · 11 citations
- Decidable Synthesis of Programs with Uninterpreted FunctionsPaul Krogmeier, Umang Mathur, Adithya Murali, P. Madhusudan et al.CAV 2020 · 8 citations
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