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We propose proof script refactorings as a robust tool for constructing, restructuring, and maintaining formal proof developments. We argue that a formal approach is vital, and illustrate by defining and proving correct a number of valuable refactorings in a simplified proof script and declarative proof language of our own design.

Rippling is a heuristic used to guide rewriting and is typically used for inductive theorem proving. We introduce a method to support case-analysis within rippling. Like earlier work, this allows goals containing if-statements to be proved automatically. The new contribution is that our method also supports case-analysis on datatypes. By locating the case-analysis as a step within rippling we also maintain the termination. The work has been implemented in IsaPlanner and used to extend the existing inductive proof method. We evaluate this extended prover on a large set of examples from Isabelle’s theory library and from the inductive theorem proving literature. We find that this leads to a significant improvement in the coverage of inductive theorem proving. The main limitations of the extended prover are identified, highlight the need for advances in the treatment of assumptions during rippling and when conjecturing lemmas.

We have implemented a program for inductive theory formation, called IsaCoSy, which synthesises conjectures about recursively defined datatypes and functions. Only irreducible terms are generated, which keeps the search space tractably small. The synthesised terms are filtered through counter-example checking and then passed on to the automatic inductive prover IsaPlanner. Experiments have given promising results, with high recall of 83% for natural numbers and 100% for lists when compared to libraries for the Isabelle theorem prover. However, precision is somewhat lower, 38-63%.

Centre for Intelligent Systems and their Applications Proof planning is a paradigm for the automation of proof that focuses on encoding intelligence to guide the proof process. The idea is to capture common patterns of reasoning which can be used to derive abstract descriptions of proofs known as proof plans. These can then be executed to provide fully formal proofs. This thesis concerns the development and analysis of a novel approach to proof planning that focuses on an explicit representation of choices during search. We embody our approach as a proof planner for the generic proof assistant Isabelle and use the Isar language, which is human-readable and machine-checkable, to represent proof plans. Within this framework we develop an inductive theorem prover as a case study of our approach to proof planning. Our prover uses the difference reduction heuristic known as rippling to automate the step cases of the inductive proofs. The development of a flexible approach to rippling that supports its various modifications and extensions is the second major focus of this thesis. Here, our inductive theorem prover provides a context in which to evaluate rippling experimentally. This work results in an efficient and powerful inductive theorem prover for Isabelle as well as proposals for further improving the efficiency of rippling. We also draw observations in order to direct further work on proof planning. Overall, we aim to make it easier for mathematical techniques, and those specific to mechanical theorem proving, to be encoded and applied to problems.

We describe novel computational techniques for constructing induction rules for deductive synthesis proofs. Deductive synthesis holds out the promise of automated construction of correct computer programs from specifications of their desired behaviour. Synthesis of programs with iteration or recursion requires inductive proof

Refactoring is an important Software Engineering technique for improving the structure of a program after it has been written. Refactorings improve the maintainability, readability, and design of a program without affecting its external behaviour. In analogy, this thesis introduces proof refactoring to make structured, semantics preserving changes to the proof documents constructed by interactive theorem provers as part of a formal proof development. In order to formally study proof refactoring, the first part of this thesis constructs a proof language framework, Hiscript. The Hiscript framework consists of a procedural tactic language, a declarative proof language, and a modular theory language. Each level of this framework is equipped with a formal semantics based on a hierarchical notion of proof trees. Furthermore, this framework is generic as it does not prescribe an underlying logical kernel. This part contributes an investigation of semantics for formal proof documents, which is proved to construct valid proofs. Moreover, in analogy with type-checking, static well-formedness checks of proof documents are separated from evaluation of the proof. Furthermore, a subset of the SSReflect language for Coq, called eSSence, is also encoded using hierarchical proofs. Both Hiscript and eSSence are shown to have language elements with a natural hierarchical representation. In the second part, proof refactoring is put on a formal footing with a definition using the Hiscript framework. Over thirty refactorings are formally specified and proved to preserve the semantics in a precise way for the Hiscript language, including traditional structural refactorings, such as rename item, and proof specific refactorings such as backwards proof to forwards proof and declarative to procedural. Finally, a concrete, generic refactoring framework, called Polar, is introduced. Polar is based on graph rewriting and has been implemented with over ten refactorings and for two proof languages, including Hiscript. Finally, the third part concludes with some wishes for the future.

In this thesis we describe an approach to automatically invent/explore new mathematical theories, with the goal of producing results comparable to those produced by humans, as represented, for example, in the libraries of the Isabelle proof assistant. Our approach is based on ‘schemes’, which are formulae in higher-order logic. We show that it is possible to automate the instantiation process of schemes to generate conjectures and definitions. We also show how the new definitions and the lemmata discovered during the exploration of a theory can be used, not only to help with the proof obligations during the exploration, but also to reduce redundancies inherent in most theory-formation systems. We exploit associative-commutative (AC) operators using ordered rewriting to avoid AC variations of the same instantiation. We implemented our ideas in an automated tool, called IsaScheme, which employs Knuth-Bendix completion and recent automatic inductive proof tools. We have evaluated our system in a theory of natural numbers and a theory of lists.