Collection analysis for Horn clause programs

We consider approximating data structures with collections of the items that they contain. For examples, lists, binary trees, tuples, etc, can be approximated by sets or multisets of the items within them. Such approximations can be used to provide partial correctness properties of logic programs. For example, one might wish to specify than whenever the atom $sort(t,s)$ is proved then the two lists $t$ and $s$ contain the same multiset of items (that is, $s$ is a permutation of $t$). If sorting removes duplicates, then one would like to infer that the sets of items underlying $t$ and $s$ are the same. Such results could be useful to have if they can be determined statically and automatically. We present a scheme by which such collection analysis can be structured and automated. Central to this scheme is the use of linear logic as a omputational logic underlying the logic of Horn clauses

Focusing and Polarization in Intuitionistic Logic

A focused proof system provides a normal form to cut-free proofs that structures the application of invertible and non-invertible inference rules. The focused proof system of Andreoli for linear logic has been applied to both the proof search and the proof normalization approaches to computation. Various proof systems in literature exhibit characteristics of focusing to one degree or another. We present a new, focused proof system for intuitionistic logic, called LJF, and show how other proof systems can be mapped into the new system by inserting logical connectives that prematurely stop focusing. We also use LJF to design a focused proof system for classical logic. Our approach to the design and analysis of these systems is based on the completeness of focusing in linear logic and on the notion of polarity that appears in Girard's LC and LU proof systems

Proof Outlines as Proof Certificates: A System Description

We apply the foundational proof certificate (FPC) framework to the problem of designing high-level outlines of proofs. The FPC framework provides a means to formally define and check a wide range of proof evidence. A focused proof system is central to this framework and such a proof system provides an interesting approach to proof reconstruction during the process of proof checking (relying on an underlying logic programming implementation). Here, we illustrate how the FPC framework can be used to design proof outlines and then to exploit proof checkers as a means for expanding outlines into fully detailed proofs. In order to validate this approach to proof outlines, we have built the ACheck system that allows us to take a sequence of theorems and apply the proof outline "do the obvious induction and close the proof using previously proved lemmas".Comment: In Proceedings WoF'15, arXiv:1511.0252

A framework for proof certificates in finite state exploration

Model checkers use automated state exploration in order to prove various properties such as reachability, non-reachability, and bisimulation over state transition systems. While model checkers have proved valuable for locating errors in computer models and specifications, they can also be used to prove properties that might be consumed by other computational logic systems, such as theorem provers. In such a situation, a prover must be able to trust that the model checker is correct. Instead of attempting to prove the correctness of a model checker, we ask that it outputs its "proof evidence" as a formally defined document--a proof certificate--and that this document is checked by a trusted proof checker. We describe a framework for defining and checking proof certificates for a range of model checking problems. The core of this framework is a (focused) proof system that is augmented with premises that involve "clerk and expert" predicates. This framework is designed so that soundness can be guaranteed independently of any concerns for the correctness of the clerk and expert specifications. To illustrate the flexibility of this framework, we define and formally check proof certificates for reachability and non-reachability in graphs, as well as bisimulation and non-bisimulation for labeled transition systems. Finally, we describe briefly a reference checker that we have implemented for this framework.Comment: In Proceedings PxTP 2015, arXiv:1507.0837

Introduction

The introduction (about 6,000 words) to _The Cambridge Companion to Utilitarianism_, in three sections: utilitarianism’s place in recent and contemporary moral philosophy (including the opinions of critics such as Rawls and Scanlon), a brief history of the view (again, including the opinions of critics, such as Marx and Nietzsche), and an overview of the chapters of the book

Nominal Abstraction

Recursive relational specifications are commonly used to describe the computational structure of formal systems. Recent research in proof theory has identified two features that facilitate direct, logic-based reasoning about such descriptions: the interpretation of atomic judgments through recursive definitions and an encoding of binding constructs via generic judgments. However, logics encompassing these two features do not currently allow for the definition of relations that embody dynamic aspects related to binding, a capability needed in many reasoning tasks. We propose a new relation between terms called nominal abstraction as a means for overcoming this deficiency. We incorporate nominal abstraction into a rich logic also including definitions, generic quantification, induction, and co-induction that we then prove to be consistent. We present examples to show that this logic can provide elegant treatments of binding contexts that appear in many proofs, such as those establishing properties of typing calculi and of arbitrarily cascading substitutions that play a role in reducibility arguments.Comment: To appear in the Journal of Information and Computatio

Structured general corecursion and coinductive graphs [extended abstract]

Bove and Capretta's popular method for justifying function definitions by general recursive equations is based on the observation that any structured general recursion equation defines an inductive subset of the intended domain (the "domain of definedness") for which the equation has a unique solution. To accept the definition, it is hence enough to prove that this subset contains the whole intended domain. This approach works very well for "terminating" definitions. But it fails to account for "productive" definitions, such as typical definitions of stream-valued functions. We argue that such definitions can be treated in a similar spirit, proceeding from a different unique solvability criterion. Any structured recursive equation defines a coinductive relation between the intended domain and intended codomain (the "coinductive graph"). This relation in turn determines a subset of the intended domain and a quotient of the intended codomain with the property that the equation is uniquely solved for the subset and quotient. The equation is therefore guaranteed to have a unique solution for the intended domain and intended codomain whenever the subset is the full set and the quotient is by equality.Comment: In Proceedings FICS 2012, arXiv:1202.317

Formalizing Operational Semantic Specifications in Logic

AbstractWe review links between three logic formalisms and three approaches to specifying operational semantics. In particular, we show that specifications written with (small-step and big-step) SOS, abstract machines, and multiset rewriting, are closely related to Horn clauses, binary clauses, and (a subset of) linear logic, respectively. We shall illustrate how binary clauses form a bridge between the other two logical formalisms. For example, using a continuation-passing style transformation, Horn clauses can be transformed into binary clauses. Furthermore, binary clauses can be seen as a degenerative form of multiset rewriting: placing binary clauses within linear logic allows for rich forms of multiset rewriting which, in turn, provides a modular, big-step SOS specifications of imperative and concurrency primitives. Establishing these links between logic and operational semantics has many advantages for operational semantics: tools from automated deduction can be used to animate semantic specifications; solutions to the treatment of binding structures in logic can be used to provide solutions to binding in the syntax of programs; and the declarative nature of logical specifications provides broad avenues for reasoning about semantic specifications