Interactive Theorem Proving Modulo Fuzzing

Formal verification involves the use of logical and computational methods to establish claims that are expressed in precise mathematical terms. These can include ordinary mathematical theorems, as well as claims that pieces of hardware or software, network protocols, and mechanical and hybrid systems meet their specifications. In practice, there is not a sharp distinction between verifying a piece of mathematics and verifying the correctness of a system: formal verification requires describing hardware and software systems in mathematical terms, at which point establishing claims as to their correctness becomes a form of theorem proving. Conversely, the proof of a mathematical theorem may require a lengthy computation, in which case verifying the truth of the theorem requires verifying that the computation does what it is supposed to do. The gold standard for supporting a mathematical claim is to provide a proof, and twentieth-century developments in logic show most if not all conventional proof methods can be reduced to a small set of axioms and rules in any of a number of foundational systems. With this reduction, there are two ways that a computer can help establish a claim: it can help find a proof in the first place, and it can help verify that a purported proof is correct. Automated theorem proving focuses on the “finding” aspect. Resolution theorem provers, tableau theorem provers, fast satisfiability solvers, and so on provide means of establishing the validity of formulas in propositional and first-order logic. Other systems provide search procedures and decision procedures for specific languages and domains, such as linear or nonlinear expressions over the integers or the real numbers. Architectures like SMT (“satisfiability modulo theories”) combine domain-general search methods with domain-specific procedures. Computer algebra systems and specialized mathematical software packages provide means of carrying out mathematical computations, establishing mathematical bounds, or finding mathematical objects. A calculation can be viewed as a proof as well, and these systems, too, help establish mathematical claims. Automated reasoning systems strive for power and efficiency, often at the expense of guaranteed soundness. Such systems can have bugs, and it can be difficult to ensure that the results they deliver are correct. In contrast, interactive theorem proving focuses on the “verification” aspect of theorem proving, requiring that every claim is supported by a proof in a suitable axiomatic foundation. This sets a very high standard: every rule of inference and every step of a calculation has to be justified by appealing to prior definitions and theorems, all the way down to basic axioms and rules. In fact, most such systems provide fully elaborated “proof objects” that can be communicated to other systems and checked independently. Constructing such proofs typically requires much more input and interaction from users, but it allows us to obtain deeper and more complex proofs. The Lean Theorem Prover aims to bridge the gap between interactive and automated theorem proving, by situating automated tools and methods in a framework that supports user interaction and the construction of fully specified axiomatic proofs. The goal is to support both mathematical reasoning and reasoning about complex systems, and to verify claims in both domains.

Verification condition generators (VCGs) can reduce overall correctness statements about sequential programs to verification conditions (VCs) that can then be proved independently by automatic theorem provers like SMT solvers. SMT solvers became not only more powerful in recent years in that they can now solve much bigger problems than before, they can now also solve problems of less restricted logics, for example, by covering non-linear arithmetic as required by some hybrid systems. However, there is so far still no VCG procedure that could generate VCs of hybrid programs for these SMT solvers. We therefore propose in this paper a first VCG procedure for hybrid systems that is based on induction proofs on the strongly connected components (SCCs) of the underlying state transition diagrams. Given the right invariants for a safety property, the VCs can be automatically generated for the considered hybrid system. The validity of the VCs is then independently proved by SMT solvers and implies the correctness of the considered safety property.

We introduce BWare, an industrial research project that aims to provide a mechanized framework to support the automated verification of proof obligations coming from the development of industrial applications using the B method and requiring high integrity. The adopted methodology consists in building a generic verification platform relying on different automated theorem provers, such as first order provers and SMT (Satisfiability Modulo Theories) solvers. Beyond the multi-tool aspect of our methodology, the originality of this project also resides in the requirement for the verification tools to produce proof objects, which are to be checked independently. In this paper, we present some preliminary results of BWare, as well as some current major lines of work.Keywords B MethodProof ObligationsFirst Order ProversSMT SolversLogical FrameworksIndustrial UseLarge Scale Study

This paper introduces a new technique for reasoning with quantifiers and theories. Traditionally, first-order theorem provers (ATPs) are well suited to reasoning with first-order problems containing many quantifiers and satisfiability modulo theories (SMT) solvers are well suited to reasoning with first-order problems in ground theories such as arithmetic. A recent development in first-order theorem proving has been the AVATAR architecture which uses a SAT solver to guide proof search based on a propositional abstraction of the first-order clause space. The approach turns a single proof search into a sequence of proof searches on (much) smaller sub-problems. This work extends the AVATAR approach to use a SMT solver in place of the SAT solver, with the effect that the first-order solver only needs to consider ground-theory-consistent sub-problems. The new architecture has been implemented using the Vampire theorem prover and Z3 SMT solver. Our experimental results, and the results of recent competitions, show that such a combination can be highly effective.

Explainable predictive modeling for limited spectral data

Satisfiability Modulo Theories (SMT) is the problem of deciding the satisfiability of a first-order formula with respect to some theory or combination of theories; Verification Modulo Theories (VMT) is the problem of analyzing the reachability for transition systems represented in terms of SMT formulae. In this article, we tackle the problems of SMT and VMT over the theories of nonlinear arithmetic over the reals (NRA) and of NRA augmented with transcendental (exponential and trigonometric) functions (NTA). We propose a new abstraction-refinement approach for SMT and VMT on NRA or NTA, called Incremental Linearization . The idea is to abstract nonlinear multiplication and transcendental functions as uninterpreted functions in an abstract space limited to linear arithmetic on the rationals with uninterpreted functions. The uninterpreted functions are incrementally axiomatized by means of upper- and lower-bounding piecewise-linear constraints. In the case of transcendental functions, particular care is required to ensure the soundness of the abstraction. The method has been implemented in the M ath SAT SMT solver and in the nu X mv model checker. An extensive experimental evaluation on a wide set of benchmarks from verification and mathematics demonstrates the generality and the effectiveness of our approach.

Large Language Models (LLMs) have emerged as a promising alternative to traditional static program analysis methods, such as symbolic execution, offering the ability to reason over code directly without relying on theorem provers or SMT solvers. However, LLMs are also inherently approximate by nature, and therefore face significant challenges in relation to the accuracy and scale of analysis in real-world applications. Such issues often necessitate the use of larger LLMs with higher token limits, but this requires enterprise-grade hardware (GPUs) and thus limits accessibility for many users. In this paper, we propose LLM-based symbolic execution —a novel approach that enhances LLM inference via a path-based decomposition of the program analysis tasks into smaller (more tractable) subtasks. The core idea is to generalize path constraints using a generic code-based representation that the LLM can directly reason over, and without translation into another (less-expressive) formal language. We implement our approach in the form of AutoBug, an LLM-based symbolic execution engine that is lightweight and language-agnostic, making it a practical tool for analyzing code that is challenging for traditional approaches. We show that AutoBug can improve both the accuracy and scale of LLM-based program analysis, especially for smaller LLMs that can run on consumer-grade hardware.

Encoding TLA+ into unsorted and many-sorted first-order logic

A complete and terminating approach to linear integer solving

This volume contains the proceedings of the Workshop on Partiality and Recursion in Interactive Theorem Provers (PAR 2010) which took place on July 15 in Edinburgh, UK. This workshop was held as a satellite workshop of the International Conference on Interactive Theorem Proving (ITP 2010), itself part of the Federated Logic Conference 2010 (FLoC 2010). This workshop is a venue for researchers working on new approaches to cope with partial functions and terminating general (co)recursion in theorem provers.

Input/Output Automata (IOA) is an expressive specification framework with built-in properties for compositional reasoning. It has been shown to be effective in specifying and analyzing distributed and networked systems. The available verification engines for IOA are based on interactive theorem provers such as Isabelle, Larch, PVS, and Coq, and are expressive but require heavy human interaction. Motivated by the advances in SMT solvers, in this work we explore a different expressivity-automation tradeoff for IOA. We present Dione, the first IOA analysis system built with Dafny and its SMT-powered toolchain and demonstrate its effectiveness on four distributed applications. Our translator tool converts Python-esque Dione language specification of IOA and their properties to parameterized Dafny modules. Dione automatically generates the relevant compatibility and composition lemmas for the IOA specifications,which can then be checked with Dafny on a per module-basis. We ensure that all resulting formulas are expressed mostly in fragments solvable by SMT solvers and hence enables Bounded Model Checking and k-induction-based invariant checking using Z3. We present successful applications of Dione in verification of an asynchronous leader election algorithm, two self-stabilizing mutual exclusion algorithms, and CAN bus Arbitration. We automatically prove key invariants of all four protocols; for the last three this involves reasoning about arbitrary number of participants. These analyses are largely automatic with minimal manual inputs needed, and they demonstrate the effectiveness of this approach in analyzing networked and distributed systems.

Satisfiability Modulo Theories (SMT) solvers are used in many modern program verification, analysis and testing tools. They owe their scale and efficiency thanks to advances in search algorithms underlying modern SAT solvers and first-order theorem provers. They owe their versatility in software development applications thanks to specialized algorithms supporting theories, such as numbers and algebraic data-types, of relevance for software engineering. This lecture introduces algorithmic principles of SMT solving, taking as basis modern SAT solvers and integration with specialized theory solvers and quantifier reasoning. We detail some of the algorithms used for main theories used in current SMT solvers and survey newer theories and approaches to integrating solvers. The lectures also outline some application scenarios where SMT solvers have found use, including program verification, network analysis, symbolic model checking, test-case generation, and white-box fuzzing.

The Girth-Chromatic number theorem is a theorem from graph theory, stating that graphs with arbitrarily large girth and chromatic number exist. We formalize a probabilistic proof of this theorem in the Isabelle/HOL theorem prover, closely following a standard textbook proof and use this to explore the use of the probabilistic method in a theorem prover.

Watson is a general-purpose system for formal reasoning. It is an interactive equational higher-order theorem prover. The higher-order logic supported by the prover is distinctive in being type free (it is a safe variant of Quine's i>NF). Watson allows the development of automated proof strategies, which are represented and stored by the prover in the same way as theorems. The mathematical foundations of the prover and the way these are presented to a user are discussed. The paper also contains discussions of experiences with the prover and relations of the prover to other systems.

Automated theorem proving: a quarter century review by D. W. Loveland Citation to Hao Wang Computer theorem proving and artificial intelligence by H. Wang Citation to Lawrence Wos and Steven Winker Open questions solved with the assistance of AURA by L. Wos and S. Winker Some automatic proofs in analysis by W. W. Bledsoe Proof-checking, theorem-proving, and program verification by R. S. Boyer and J. S. Moore A mechanical proof of the turing completeness of pure LISP by R. S. Boyer and J. S. Moore Automating higher-order logic by P. B. Andrews, D. A. Miller, E. L. Cohen, and F. Pfenning Abelian group unification algorithms for elementary terms by D. Lankford, G. Butler, and B. Brady Combining satisfiability procedures by equality sharing by G. Nelson On the decision problem and the mechanization of theorem-proving in elementary geometry by W. Wen-Tsun Some recent advances in mechanical theorem-proving of geometries by W. Wen-Tsun Proving elementary geometry theorems using Wu's algorithm by S.-C. Chou Automated theory formation in mathematics by D. B. Lenat Student use of an interactive theorem prover by J. McDonald and P. Suppes.