Assisted Proof Document Authoring

PROOF CHECKING THE RSA PUBLIC KEY ENCRYPTION ALGORITHM

Most computer checked proofs are tied to the particular technology of a prover’s software. While sharing results between proof assistants is a recognized and desirable goal, the current organization of theorem proving tools makes such sharing an exception instead of the rule. In this talk, I argue that we need to turn the current architecture of proof assistants and formal proofs inside-out. That is, instead of having a few mature theorem provers include within them their formally checked theorems and proofs, I propose that proof assistants should sit on the edge of a web of formal proofs and that proof assistant should be exporting their proofs so that they can exist independently of any theorem prover. While it is necessary to maintain the dependencies between definitions, theories, and theorems, no explicit library structure should be imposed on this web of formal proofs. Thus a theorem and its proofs should not necessarily be located at a particular URL or within a particular prover’s library. While the world of symbolic logic and proof theory certainly allows for proofs to be seen as global and permanent objects, there is a lot of research and engineering work that is needed to make this possible. I describe some of the required research and development that must be done to achieve this goal.

The MathLang project aims at computerizing mathematical texts according to various degrees of formalisations, and without any prior commitment to a particular logical framework or to a particular proof checker. In this paper, the MathLang framework, its developments and its current and future aspects, as well as examples of computerization from original mathematical texts to the fully formalised Mizar versions are given. For each aspect, emphasis will be on its design, formalisation, implementation, the automation available for this aspect and the correctness or trustworthiness of these processes. Then, we discuss how the computerisation path from the original mathematical text to full Mizar will look if Isabelle was the checker chosen instead of Mizar and show that a number of aspects and computerised versions of the original text are common between both path. We also discuss at which stage a commitment to a certain logical framework and a certain proof checker can be made on the path from the original mathematical text to the version fully formalised in that proof checker.

We describe experiments in teaching fundamental informatics notions around mathematical structures for formal concepts, and effective algorithms to manipulate them. The major themes of lambda-calculus and type theory served as guides for the effective implementation of functional programming languages and higher-order proof assistants, appropriate for reflecting the theoretical material into effective tools to represent constructively the concepts and formally certify the proofs of their properties. Progressively, a literate programming and proving style replaced informal mathematics in the presentation of the material as executable course notes. The talk will evoke the various stages of (in)completion of the corresponding set of notes along the years, and tell how their elaboration proved to be essential to the discovery of fundamental results.

An interactive proof checker is a system which is able of building a formal proof (in some deductive calculus) by executing commands provided by the user. Proof checkers are useful both for making experiments in proof construction within various formal systems and for proving theorems in those fields of mathematics (such as mathematical theory of computation) where proofs are necessarily very large and unfeasible by hand. Two levels may be distinguished in a proof checker. The lower one implements the proof management routines, and is independent of any particular logic. The higher one implements the inference rules of a particular logical calculus. Powerful higher level rules are also needed to make the use of the checker practical. Almost all routine steps may be then generated automatically, and the user has just to give some “hints” to the checker, which transforms an “informal argument” into a formal proof.

Intermediate verification languages like Why3 and Boogie have made it much easier to build program verifiers, transforming the process into a logic compilation problem rather than a proof automation one. Why3 in particular implements a rich logic for program specification with polymorphism, algebraic data types, recursive functions and predicates, and inductive predicates; it translates this logic to over a dozen solvers and proof assistants. Accordingly, it serves as a backend for many tools, including Frama-C, EasyCrypt, and GNATProve for Ada SPARK. But how can we be sure that these tools are correct? The alternate foundational approach, taken by tools like VST and CakeML, provides strong guarantees by implementing the entire toolchain in a proof assistant, but these tools are harder to build and cannot directly take advantage of SMT solver automation. As a first step toward enabling automated tools with similar foundational guarantees, we give a formal semantics in Coq for the logic fragment of Why3. We show that our semantics are useful by giving a correct-by-construction natural deduction proof system for this logic, using this proof system to verify parts of Why3’s standard library, and proving sound two of Why3’s transformations used to convert terms and formulas into the simpler logics supported by the backend solvers.

Artificial Intelligence for Theorem Proving (AITP) has given rise to a plethora of benchmarks and methodologies, particularly in Interactive Theorem Proving (ITP). Research in the area is fragmented, with a diverse set of approaches being spread across several ITP systems. This presents a significant challenge to the comparison of methods, which are often complex and difficult to replicate. Addressing this, we present BAIT, a framework for the fair and streamlined comparison of learning approaches in ITP. We demonstrate BAIT’s capabilities with an in-depth comparison, across several ITP benchmarks, of state-of-the-art architectures applied to the problem of formula embedding. We find that Structure Aware Transformers perform particularly well, improving on techniques associated with the original problem sets. BAIT also allows us to assess the end-to-end proving performance of systems built on interactive environments. This unified perspective reveals a novel end-to-end system that improves on prior work. We also provide a qualitative analysis, illustrating that improved performance is associated with more semantically-aware embeddings. By streamlining the implementation and comparison of Machine Learning algorithms in the ITP context, we anticipate BAIT will be a springboard for future research.

International audience

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.

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.

We present a novel propositional proof tracing format that eliminates complex processing, thus enabling efficient (formal) proof checking. The benefits of this format are demonstrated by implementing a proof checker in C, which outperforms a state-of-the-art checker by two orders of magnitude. We then formalize the theory underlying propositional proof checking in Coq, and extract a correct-by-construction proof checker for our format from the formalization. An empirical evaluation using 280 unsatisfiable instances from the 2015 and 2016 SAT competitions shows that this certified checker usually performs comparably to a state-of-the-art non-certified proof checker. Using this format, we formally verify the recent 200 TB proof of the Boolean Pythagorean Triples conjecture.

The formalization of mathematics in practice relies heavily on proof assistants and automatic theorem provers, therefore we studied what are the state of the art proof assitants and their limitations to understand what are the main challenges in making formalized mathematics common practice among mathematicians. We found out that curretly the two major dificulties in formalizing mathematics with proof assistants are due to steep learning curves in how to use these tools and due to a wide gap between the notation employed in these proof assistants and the currently used mathematical notation. We also developed a C++ library to develop proof assistants with great notational flexibility.

Theorem proving procedures for the propositional calculus have traditionally relied on syntactic manipulations of the formula to derive a proof. In particular, clausal theorem provers sometimes lose some of the obvious semantics present in the theorem, in the process of converting the theorem into an unnatural normal form. Most existing propositional theorem provers do not incorporate substitution of equals for equals as an inference rule. In this paper we develop a “natural” proof system for the propositional calculus, with the goal that most succinct mathematical proofs should be encodable as short formal proofs within the proof system. The main distinctive features of NPS are: We show that from a complexity theoretic viewpoint NPS is at least as powerful as the resolution procedure. We further demonstrate formulas on which NPS fares better than resolution. Finally, since proofs in NPS usually resemble manual proofs, we feel that NPS is easily amenable to an interactive theorem prover.

Mutation analysis, which introduces artificial defects into software systems, is the basis of mutation testing, a technique widely applied to evaluate and enhance the quality of test suites. However, despite the deep analogy between tests and formal proofs, mutation analysis has seldom been considered in the context of deductive verification. We propose mutation proving, a technique for analyzing verification projects that use proof assistants. We implemented our technique for the Coq proof assistant in a tool dubbed mCoq. mCoq applies a set of mutation operators to Coq definitions of functions and datatypes, inspired by operators previously proposed for functional programming languages. mCoq then checks proofs of lemmas affected by operator application. To make our technique feasible in practice, we implemented several optimizations in mCoq such as parallel proof checking. We applied mCoq to several medium and large scale Coq projects, and recorded whether proofs passed or failed when applying different mutation operators. We then qualitatively analyzed the mutants, finding many instances of incomplete specifications. For our evaluation, we made several improvements to serialization of Coq files and even discovered a notable bug in Coq itself, all acknowledged by developers. We believe mCoq can be useful both to proof engineers for improving the quality of their verification projects and to researchers for evaluating proof engineering techniques.

The Isabelle/HOL proof assistant provides quite advanced and reliable support for discharging proof goals with external SMT solvers by reconstructing the resulting proof tree within the Isabelle/Pure inference kernel. In particular, currently Isabelle fully and efficiently supports proof reconstruction for the quantifier-free fragments of the theories of equality and uninterpreted functions (QF_UF) and linear integer arithmetic (QF_LIA). Yet there are a number of practically relevant theories that can be decided using relatively efficient algorithms, but are not supported either by the Isabelle proof reconstruction procedure or by the SMT solvers themselves. Meanwhile, if the decision procedure for an extended logical theory can be expressed as a complete quantifier instantiation strategy that reduces the given decision problem into the supported logical fragment (QF_UFLIA), the theory can be fully supported within the existing Isabelle/HOL infrastructure with relatively little additional effort. The goal of our work was to develop a fully formal completeness proof for an efficient quantifier instantiation strategy that translates a satisfiability problem in the logic of bounded linear integer arithmetic (we call it QF_BLIA) into the equisatisfiable problem in the logic of linear integer arithmetic and uninterpreted functions (QF_UFLIA). In this paper we first give the initial informal presentation of the proof, then discuss the most relevant issues of our resulting corresponding formal development of the completeness proof within Isabelle/HOL. The resulting formal proofs tightly follow the provided informal presentation, but at the same time they also contain quite significant amount of auxiliary developments that can potentially be generalized for other similar proof formalizations and automated using theory generation facilities of Isabelle/ML.