arXiv subjects

Nian-Ze Lee

Publications and source records attributed to Nian-Ze Lee.

6 recordsLinked to original sources

arXiv2026

Circuit-Based Program Verification: Sequential Circuits as an Intermediate Representation for Verifying C Programs

Formal verification of software programs and hardware designs shares the common goal of reasoning about state-transition systems, yet the two communities have largely developed separate intermediate representations and verification algorithms. This paper investigates sequential circuits as an intermediate representation for software verification, with the goal of enabling direct application of hardware-model-checking techniques. We present Circuit-Based Program Verification (CPV), a modular framework that translates C programs into sequential circuits and employs off-the-shelf hardware model checkers as backends. Unlike traditional software verifiers, which typically rely on path-based exploration, CPV reasons over sequential circuits, where a program's control and data flows are folded into a monolithic transition relation that can be analyzed as a whole. The framework supports reachability-safety and termination analyses and integrates multiple state-of-the-art hardware model checkers, which together provide access to diverse verification algorithms, including bounded model checking, $k$-induction, and IC3/PDR. Counterexamples found by hardware model checkers are automatically translated back into software-verification witnesses for users to interpret verification results. We conducted a comprehensive evaluation on a benchmark suite of more than 16000 tasks. Our results show that CPV achieved competitive performance against five well-established software verifiers and exhibited complementary strengths by uniquely solving tasks that other verifiers cannot handle.

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arXiv2024

Augmenting Interpolation-Based Model Checking with Auxiliary Invariants (Extended Version)

Software model checking is a challenging problem, and generating relevant invariants is a key factor in proving the safety properties of a program. Program invariants can be obtained by various approaches, including lightweight procedures based on data-flow analysis and intensive techniques using Craig interpolation. Although data-flow analysis runs efficiently, it often produces invariants that are too weak to prove the properties. By contrast, interpolation-based approaches build strong invariants from interpolants, but they might not scale well due to expensive interpolation procedures. Invariants can also be injected into model-checking algorithms to assist the analysis. Invariant injection has been studied for many well-known approaches, including k-induction, predicate abstraction, and symbolic execution. We propose an augmented interpolation-based verification algorithm that injects external invariants into interpolation-based model checking (McMillan, 2003), a hardware model-checking algorithm recently adopted for software verification. The auxiliary invariants help prune unreachable states in Craig interpolants and confine the analysis to the reachable parts of a program. We implemented the proposed technique in the verification framework CPAchecker and evaluated it against mature SMT-based methods in CPAchecker as well as other state-of-the-art software verifiers. We found that injecting invariants reduces the number of interpolation queries needed to prove safety properties and improves the run-time efficiency. Consequently, the proposed invariant-injection approach verified difficult tasks that none of its plain version (i.e., without invariants), the invariant generator, or any compared tools could solve.

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arXiv2024

Software Verification with CPAchecker 3.0: Tutorial and User Guide (Extended Version)

This tutorial provides an introduction to CPAchecker for users. CPAchecker is a flexible and configurable framework for software verification and testing. The framework provides many abstract domains, such as BDDs, explicit values, intervals, memory graphs, and predicates, and many program-analysis and model-checking algorithms, such as abstract interpretation, bounded model checking, Impact, interpolation-based model checking, k -induction, PDR, predicate abstraction, and symbolic execution. This tutorial presents basic use cases for CPAchecker in formal software verification, focusing on its main verification techniques with their strengths and weaknesses. It also shows further use cases of CPAchecker for test-case generation and witness-based result validation. The envisioned readers are assumed to possess a background in automatic formal verification and program analysis, but prior knowledge of CPAchecker is not required. This tutorial and user guide is based on CPAchecker in version 3.0. This user guide's latest version and other documentation are available at https://cpachecker.sosy-lab.org/doc.php.

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arXiv2024

MoXIchecker: An Extensible Model Checker for MoXI

MoXI is a new intermediate verification language introduced in 2024 to promote the standardization and open-source implementations for symbolic model checking by extending the SMT-LIB 2 language with constructs to define state-transition systems. The tool suite of MoXI provides a translator from MoXI to Btor2, which is a lower-level intermediate language for hardware verification, and a translation-based model checker, which invokes mature hardware model checkers for Btor2 to analyze the translated verification tasks. The extensibility of such a translation-based model checker is restricted because more complex theories, such as integer or real arithmetics, cannot be precisely expressed with bit-vectors of fixed lengths in Btor2. We present MoXIchecker, the first model checker that solves MoXI verification tasks directly. Instead of translating MoXI to lower-level languages, MoXIchecker uses the solver-agnostic library PySMT for SMT solvers as backend for its verification algorithms. MoXIchecker is extensible because it accommodates verification tasks involving more complex theories, not limited by lower-level languages, facilitates the implementation of new algorithms, and is solver-agnostic by using the API of PySMT. In our evaluation, MoXIchecker uniquely solved tasks that use integer or real arithmetics, and achieved a comparable performance against the translation-based model checker from the MoXI tool suite.

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arXiv2024

Interpolation and SAT-Based Model Checking Revisited: Adoption to Software Verification

The article "Interpolation and SAT-Based Model Checking" (McMillan, 2003) describes a formal-verification algorithm, which was originally devised to verify safety properties of finite-state transition systems. It derives interpolants from unsatisfiable BMC queries and collects them to construct an overapproximation of the set of reachable states. Although 20 years old, the algorithm is still state-of-the-art in hardware model checking. Unlike other formal-verification algorithms, such as k-induction or PDR, which have been extended to handle infinite-state systems and investigated for program analysis, McMillan's interpolation-based model-checking algorithm from 2003 has not been used to verify programs so far. Our contribution is to close this significant, two decades old gap in knowledge by adopting the algorithm to software verification. We implemented it in the verification framework CPAchecker and evaluated the implementation against other state-of-the-art software-verification techniques on the largest publicly available benchmark suite of C safety-verification tasks. The evaluation demonstrates that McMillan's interpolation-based model-checking algorithm from 2003 is competitive among other algorithms in terms of both the number of solved verification tasks and the run-time efficiency. Our results are important for the area of software verification, because researchers and developers now have one more approach to choose from.

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arXiv2021

Dependency Stochastic Boolean Satisfiability: A Logical Formalism for NEXPTIME Decision Problems with Uncertainty

Stochastic Boolean Satisfiability (SSAT) is a logical formalism to model decision problems with uncertainty, such as Partially Observable Markov Decision Process (POMDP) for verification of probabilistic systems. SSAT, however, is limited by its descriptive power within the PSPACE complexity class. More complex problems, such as the NEXPTIME-complete Decentralized POMDP (Dec-POMDP), cannot be succinctly encoded with SSAT. To provide a logical formalism of such problems, we extend the Dependency Quantified Boolean Formula (DQBF), a representative problem in the NEXPTIME-complete class, to its stochastic variant, named Dependency SSAT (DSSAT), and show that DSSAT is also NEXPTIME-complete. We demonstrate the potential applications of DSSAT to circuit synthesis of probabilistic and approximate design. Furthermore, to study the descriptive power of DSSAT, we establish a polynomial-time reduction from Dec-POMDP to DSSAT. With the theoretical foundations paved in this work, we hope to encourage the development of DSSAT solvers for potential broad applications.

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