Computer Theorem Proving and HoTT

Theorem-proving is a one-player game. The history of computer programs being the players goes back to 1956 and the ‘LT’ LOGIC THEORY MACHINE of Newell, Shaw and Simon. In game-playing terms, the ‘initial position’ is the core set of axioms chosen for the particular logic and the ‘moves’ are the rules of inference. Now, the Univalent Foundations Program at IAS Princeton and the resulting ‘HoTT’ book on Homotopy Type Theory have demonstrated the success of a new kind of experimental mathematics using computer theorem proving

A Verified Theorem Prover for Higher-Order Logic

This thesis is about mechanically establishing the correctness of computer programs.\ua0In particular, we are interested in establishing the correctness of tools used in computer-aided mathematics. We build on tools for proof-producing program synthesis, and verified compilation, and a verified theorem proving kernel.\ua0With these, we have produced an interactive theorem prover for higher-order logic, called Candle, that is verified to accept only true theorems.\ua0To the best of our knowledge, Candle is the only interactive theorem prover for higher-order logic that has been verified to this degree.Candle and all technology that underpins it is developed using the HOL4 theorem prover.\ua0We use proof-producing synthesis and the verified CakeML compiler to obtain a machine code executable for the Candle theorem prover.\ua0Because the CakeML compiler is verified to preserve program semantics, we are able to obtain a soundness result about the machine code which implements the Candle theorem prover

Providing a formal linkage between MDG and HOL based on a verified MDG system.

Formal verification techniques can be classified into two categories: deductive theorem proving and symbolic state enumeration. Each method has complementary advantages and disadvantages. In general, theorem provers are high reliability systems. They can be applied to the expressive formalisms that are capable of modelling complex designs such as processors. However, theorem provers use a glass-box approach. To complete a verification, it is necessary to understand the internal structure in detail. The learning curve is very steep and modeling and verifying a system is very time-consuming. In contrast, symbolic state enumeration tools use a black-box approach. When verifying a design, the user does not need to understand its internal structure. Their advantages are their speed and ease of use. But they can only be used to prove relatively simple designs and the system security is much lower than the theorem proving system. Many hybrid tools have been developed to reap the benefits of both theorem proving Systems and symbolic state enumeration Systems. Normally, the verification results from one system are translated to another system. In other words, there is a linkage between the two Systems. However, how can we ensure that this linkage can be trusted? How can we ensure the verification system itself is correct? The contribution of this thesis is that we have produced a methodology which can provide a formal linkage between a symbolic state enumeration system and a theorem proving system based on a verified symbolic state enumeration system. The methodology has been partly realized in two simplified versions of the MDG system (a symbolic state enumeration system) and the HOL system (a theorem proving system) which involves the following three steps. First, we have verified aspects of correctness of two simplified versions of the MDG system. We have made certain that the semantics of a program is preserved in those of its translated form. Secondly, we have provided a formal linkage between the MDG system and the HOL system based on importing theorems. The MDG verification results can be formally imported into HOL to form the HOL theorems. Thirdly, we have combined the translator correctness theorems with the importing theorems. This combination allows the low level MDG verification results to be imported into HOL in terms of the semantics of a high level language (MDG-HDL). We have also summarized a general method which is used to prove the existential theorem for the specification and implementation of the design. The feasibility of this approach has been demonstrated in a case study: the verification of the correctness and usability theorems of a vending machine

Learning to Prove Theorems via Interacting with Proof Assistants

Humans prove theorems by relying on substantial high-level reasoning and problem-specific insights. Proof assistants offer a formalism that resembles human mathematical reasoning, representing theorems in higher-order logic and proofs as high-level tactics. However, human experts have to construct proofs manually by entering tactics into the proof assistant. In this paper, we study the problem of using machine learning to automate the interaction with proof assistants. We construct CoqGym, a large-scale dataset and learning environment containing 71K human-written proofs from 123 projects developed with the Coq proof assistant. We develop ASTactic, a deep learning-based model that generates tactics as programs in the form of abstract syntax trees (ASTs). Experiments show that ASTactic trained on CoqGym can generate effective tactics and can be used to prove new theorems not previously provable by automated methods. Code is available at https://github.com/princeton-vl/CoqGym.Comment: Accepted to ICML 201