Certified Decision Procedures for Width-Independent Bitvector Predicates

Modern proof assistants such as Coq and Isabelle provide high degrees of expressiveness and assurance because they support formal reasoning in higher-order logic and supply explicit machine-checkable proof objects. Unfortunately, large scale proof development in these proof assistants is still an extremely difficult and time-consuming task. One major weakness of these proof assistants is the lack of a single language where users can develop complex tactics and decision procedures using a rich programming model and in a typeful manner. This limits the scalability of the proof development process, as users avoid developing domain-specific tactics and decision procedures. In this paper, we present VeriML - a novel language design that couples a type-safe effectful computational language with first-class support for manipulating logical terms such as propositions and proofs. The main idea behind our design is to integrate a rich logical framework - similar to the one supported by Coq - inside a computational language inspired by ML. The language design is such that the added features are orthogonal to the rest of the computational language, and also do not require significant additions to the logic language, so soundness is guaranteed. We have built a prototype implementation of VeriML including both its type-checker and an interpreter. We demonstrate the effectiveness of our design by showing a number of type-safe tactics and decision procedures written in VeriML.

Nowadays, formal methods rely on tools of different kinds: proof assistants with which the user interacts to discover a proof step by step; and fully automated tools which make use of (intricate) decision procedures. But while some proof assistants can check the soundness of a proof, they lack automation. Regarding automated tools, one still has to be satisfied with their answers Yes/No/Do not know, the validity of which can be subject to question, in particular because of the increasing size and complexity of these tools.In the context of rewriting techniques, we aim at bridging the gap between proof assistants that yield formal guarantees of reliability and highly automated tools one has to trust. We present an approach making use of both shallow and deep embeddings. We illustrate this approach with a prototype based on the CiME rewriting toolbox, which can discover involved termination proofs that can be certified by the Coq proof assistant, using the Coccinelle library for rewriting.KeywordsModule TypeAutomate ToolProof AssistantGraph CriterionStrongly Connect ComponentThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

The verification of distributed algorithms is a challenge for formal techniques supported by tools, as model checkers and proof assistants. The difficulties, even for powerful tools, lie in the derivation of proofs of required properties, such as safety and eventuality, for distributed algorithms. Verification by construction can be achieved by using a formal framework in which models are constructed at different levels of abstraction; each level of abstraction is refined by the one below, and this refinement relationships is documented by an abstraction relation namely a gluing invariant. The highest levels of abstraction are used to express the required behavior in terms of the problem domain and the lowest level of abstraction corresponds to an implementation from which an efficient implementation can be derived automatically. In this paper, we describe a methodology based on the general concept of refinement and used for developing distributed algorithms satisfying a given list of safety and liveness properties. The modelling methodology is defined in the Event-B modelling language using the IDE Rodin.

In many verification applications the desired outcome is that the formula is unsatisfiable: a satisfying assignment essentially exhibits a bug and unsatisfiability implies a lack of bugs, at least for the property being verified. Most current high-performance satisfiability solvers and special-theory decision procedures are unable to provide proof of unsatisfiability. Since bugs have been discovered in many such programs long after being put into service, an uncheckable decision poses a significant problem if important economic or safety decisions are to be based upon it. This talk develops the thesis is that decision procedures can and should be designed with the ability to output an independently checkable proof. While finding a proof is hard, checking a proof can be straightforward if the proof system is simple enough. (By a “proof” we mean a real proof, with no steps omitted.) In practice, most underlying theories can produce a resolution proof. We argue that outputting such a proof does not place an undue burden on the decision procedures. We report on practical progress in this area for satisfiability solvers. Experiments have been carried out with what might be the first implementations of solver and proof checker that were developed completely independently, having only the specifications of the proof-file format as common knowledge. There is a trend toward combining high-performance satisfiability solvers with other theorem-proving methods. As the total systems become more complex, the need for “independent audits” becomes greater. Design goals for checkable proofs are proposed.

International audience

Proof Certificates for Equality Reasoning

Modern proof assistants such as Coq and Isabelle provide high degrees of expressiveness and assurance because they support formal reasoning in higher-order logic and supply explicit machine-checkable proof objects. Unfortunately, large scale proof development in these proof assistants is still an extremely difficult and time-consuming task. One major weakness of these proof assistants is the lack of a single language where users can develop complex tactics and decision procedures using a rich programming model and in a typeful manner. This limits the scalability of the proof development process, as users avoid developing domain-specific tactics and decision procedures.In this paper, we present VeriML - a novel language design that couples a type-safe effectful computational language with first-class support for manipulating logical terms such as propositions and proofs. The main idea behind our design is to integrate a rich logical framework - similar to the one supported by Coq - inside a computational language inspired by ML. The language design is such that the added features are orthogonal to the rest of the computational language, and also do not require significant additions to the logic language, so soundness is guaranteed. We have built a prototype implementation of VeriML including both its type-checker and an interpreter. We demonstrate the effectiveness of our design by showing a number of type-safe tactics and decision procedures written in VeriML.

State-based formal methods [e.g. Event-B/RODIN (Abrial in Modeling in Event-B—system and software engineering. Cambridge University Press, Cambridge, 2010; Abrial et al. in Int J Softw Tools Technol Transf (STTT) 12(6):447–466, 2010)] for critical system development and verification are now well established, with track records including tool support and industrial applications. The focus of proof-based verification, in particular, is on safety properties. Liveness properties, which guarantee eventual, or converging computations of some requirements, are less well dealt with. Inductive reasoning about liveness is not explicitly supported. Liveness proofs are often complex and expensive, requiring high-skill levels on the part of the verification engineer. Fairness-based temporal logic approaches have been proposed to address this, e.g. TLA Lamport (ACM Trans Program Lang Syst 16(3):872–923, 1994) and that of Manna and Pnueli (Temporal verification of reactive systems—safety. Springer, New York, 1995). We contribute to this technology need by proposing a fairness-based method integrating temporal and first-order logic, proof and tools for modelling and verification of safety and liveness properties. The method is based on an integration of Event-B and TLA. Building on our previous work (Mery and Poppleton in Integrated formal methods, 10th international conference, IFM 2013, Turku, Finland, pp 208–222, 2013. doi: 10.1007/978-3-642-38613-8_15 ), we present the method via three example population protocols Angluin et al. (Distrib Comput 18(4):235–253, 2006). These were proposed as a theoretical framework for computability reasoning about Wireless Sensor Network and Mobile Ad-Hoc Network algorithms. Our examples present typical liveness and convergence requirements. We prove convergence results for the examples by integrated modelling and proof with Event-B/RODIN and TLA. We exploit existing proof rules, define and apply three new proof rules; soundness proofs are also provided. During the process we observe certain repeating patterns in the proofs. These are easily identified and reused because of the explicit nature of the reasoning.

TLAPS, the TLA + proof system, is a platform for the development and mechanical verification of TLA + proofs. The TLA + proof language is declarative, and understanding proofs requires little background beyond elementary mathematics. The language supports hierarchical and non-linear proof construction and verification, and it is independent of any verification tool or strategy. Proofs are written in the same language as specifications; engineers do not have to translate their high-level designs into the language of a particular verification tool. A proof manager interprets a TLA + proof as a collection of proof obligations to be verified, which it sends to backend verifiers that include theorem provers, proof assistants, SMT solvers, and decision procedures.The first public release of TLAPS is available from [1], distributed with a BSD-like license. It handles almost all the non-temporal part of TLA + as well as the temporal reasoning needed to prove standard safety properties, in particular invariance and step simulation, but not liveness properties. Intuitively, a safety property asserts what is permitted to happen; a liveness property asserts what must happen; for a more formal overview, see [3,10].KeywordsTheorem ProverProof SystemSafety PropertyProof ObligationProof AssistantThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Bounded model checking (BMC) is an attractive alternative to symbolic model checking, since it often allows a more efficient verification. The idea of BMC is to reduce the model checking problem to a satisfiability problem of the underlying base logic, so that sophisticated decision procedures can be utilized to check the resulting formula. We present a new approach to BMC that extends current methods in three ways: First, instead of a reduction to propositional logic which restricts BMC to finite state systems, we focus on infinite state systems and therefore consider more powerful, yet decidable base logics. Second, instead of directly unwinding temporal logic formulas, we use special translations to ?-automata that take into account the temporal logic hierarchy and maintain safety and liveness properties. Third, we employ both global and local model checking procedures to take advantage of the different types of specifications that can be handled by these techniques. Based on three-valued logic, our bounded model checking procedures may either prove or disprove a specification, or they may explicitly state that no information has been obtained due to insufficient bounds.

Preface: Volume 58, Issue 2

Recursive algebraic data types (term algebras, ADTs) are one of the most well-studied theories in logic, and find application in contexts including functional programming, modelling languages, proof assistants, and verification. At this point, several state-of-the-art theorem provers and SMT solvers include tailor-made decision procedures for ADTs, and version~2.6 of the SMT-LIB standard includes support for ADTs. We study an extremely simple approach to decide satisfiability of ADT constraints, the reduction of ADT constraints to equisatisfiable constraints over uninterpreted functions (EUF) and linear integer arithmetic (LIA). We show that the reduction approach gives rise to both decision and Craig interpolation procedures in (extensions of) ADTs.

PVS: Combining specification, proof checking, and model checking

Satisfiability Modulo Theories (SMT) solvers have been widely applied in automated software analysis to reason about the queries that encode the essence of program semantics, relieving the heavy burden of manual analysis. Many SMT solving techniques rely on solving Boolean satisfiability problem (SAT), which is an NP-complete problem, so they use heuristic search strategies to seek possible solutions, especially when no known theorem can efficiently reduce the problem. An emerging challenge, named Mixed-Bitwise-Arithmetic (MBA) obfuscation, impedes SMT solving by constructing identity equations with both bitwise operations (and, or, negate) and arithmetic computation (add, minus, multiply). Common math theorems for bitwise or arithmetic computation are inapplicable to simplifying MBA equations, leading to performance bottlenecks in SMT solving. In this paper, we first scrutinize solvers' performance on solving different categories of MBA expressions: linear, polynomial, and non-polynomial. We observe that solvers can handle simple linear MBA expressions, but facing a severe performance slowdown when solving complex linear and non-linear MBA expressions. The root cause is that complex MBA expressions break the reduction laws for pure arithmetic or bitwise computation. To boost solvers' performance, we propose a semantic-preserving transformation to reduce the mixing degree of bitwise and arithmetic operations. We first calculate a signature vector based on the truth table extracted from an MBA expression, which captures the complete MBA semantics. Next, we generate a simpler MBA expression from the signature vector. Our large-scale evaluation on 3000 complex MBA equations shows that our technique significantly boost modern SMT solvers' performance on solving MBA formulas.

We present several algorithms for simultaneous SAT (propositional satisfiability) based model checking of safety properties. More precisely, we focus on Bounded Model Checking and Temporal Induction methods for simultaneously verifying multiple safety properties on the same model. The most efficient among our proposed algorithms for model checking are based on a simultaneous propositional satisfiability procedure (SSAT for short), which we design for solving related propositional objectives simultaneously, by sharing the learned clauses and the search. The SSAT algorithm is fully incremental in the sense that all clauses learned while solving one objective can be reused for the remaining objectives. Furthermore, our SSAT algorithm ensures that the SSAT solver will never re-visit the same sub-space during the search, even if there are several satisfiability objectives, hence one traversal of the search space is enough. Finally, in SSAT all SAT objectives are watched simultaneously, thus we can solve several other SAT objectives when the search is oriented to solve a particular SAT objective first. Experimental results on Intel designs demonstrate that our new algorithms can be orders of magnitude faster than the previously known techniques in this domain.