Enhancements to ACL2 in Versions 6.2, 6.3, and 6.4

We report on improvements to ACL2 made since the 2013 ACL2 Workshop.Comment: In Proceedings ACL2 2014, arXiv:1406.123

Fix Your Types

When using existing ACL2 datatype frameworks, many theorems require type hypotheses. These hypotheses slow down the theorem prover, are tedious to write, and are easy to forget. We describe a principled approach to types that provides strong type safety and execution efficiency while avoiding type hypotheses, and we present a library that automates this approach. Using this approach, types help you catch programming errors and then get out of the way of theorem proving.Comment: In Proceedings ACL2 2015, arXiv:1509.0552

Formal proofs about rewriting using ACL2

We present an application of the ACL2 theorem prover to reason about rewrite systems theory. We describe the formalization and representation aspects of our work using the firstorder, quantifier-free logic of ACL2 and we sketch some of the main points of the proof effort. First, we present a formalization of abstract reduction systems and then we show how this abstraction can be instantiated to establish results about term rewriting. The main theorems we mechanically proved are Newman’s lemma (for abstract reductions) and Knuth–Bendix critical pair theorem (for term rewriting).Ministerio de Educación y Ciencia TIC2000-1368-CO3-0

Data Definitions in the ACL2 Sedan

We present a data definition framework that enables the convenient specification of data types in ACL2s, the ACL2 Sedan. Our primary motivation for developing the data definition framework was pedagogical. We were teaching undergraduate students how to reason about programs using ACL2s and wanted to provide them with an effective method for defining, testing, and reasoning about data types in the context of an untyped theorem prover. Our framework is now routinely used not only for pedagogical purposes, but also by advanced users. Our framework concisely supports common data definition patterns, e.g. list types, map types, and record types. It also provides support for polymorphic functions. A distinguishing feature of our approach is that we maintain both a predicative and an enumerative characterization of data definitions. In this paper we present our data definition framework via a sequence of examples. We give a complete characterization in terms of tau rules of the inclusion/exclusion relations a data definition induces, under suitable restrictions. The data definition framework is a key component of counterexample generation support in ACL2s, but can be independently used in ACL2, and is available as a community book.Comment: In Proceedings ACL2 2014, arXiv:1406.123

Functional Big-step Semantics

When doing an interactive proof about a piece of software, it is important that the underlying programming language’s semantics does not make the proof unnecessarily difficult or unwieldy. Both smallstep and big-step semantics are commonly used, and the latter is typically given by an inductively defined relation. In this paper, we consider an alternative: using a recursive function akin to an interpreter for the language. The advantages include a better induction theorem, less duplication, accessibility to ordinary functional programmers, and the ease of doing symbolic simulation in proofs via rewriting. We believe that this style of semantics is well suited for compiler verification, including proofs of divergence preservation. We do not claim the invention of this style of semantics: our contribution here is to clarify its value, and to explain how it supports several language features that might appear to require a relational or small-step approach. We illustrate the technique on a simple imperative language with C-like for-loops and a break statement, and compare it to a variety of other approaches. We also provide ML and lambda-calculus based examples to illustrate its generality

A verified Common Lisp implementation of Buchberger's algorithm in ACL2

In this article, we present the formal verification of a Common Lisp implementation of Buchberger's algorithm for computing Gröbner bases of polynomial ideals. This work is carried out in ACL2, a system which provides an integrated environment where programming (in a pure functional subset of Common Lisp) and formal verification of programs, with the assistance of a theorem prover, are possible. Our implementation is written in a real programming language and it is directly executable within the ACL2 system or any compliant Common Lisp system. We provide here snippets of real verified code, discuss the formalization details in depth, and present quantitative data about the proof effort