Archive for the 'Unification' Category

Unification of simply-typed λ-terms as logic programming

By Dale Miller, from ICLP 1991, available from CiteSeer X:

The unification of simply typed λ-terms modulo the rules of β- and η-conversions is often called “higher-order” unification because of the possible presence of variables of functional type. This kind of unification is undecidable in general and if unifiers exist, most general unifiers may not exist. In this paper, we show that such unification problems can be coded as a query of the logic programming language Lλ in a natural and clear fashion. In a sense, the translation only involves explicitly axiomatizing in Lλ the notions of equality and substitution of the simply
typed λ-calculus: the rest of the unification process can be viewed as simply an interpreter of Lλ searching for proofs using those axioms.


Practical higher-order pattern unification with on-the-fly raising

By Gopalan Nadathur and Natalie Linnell, from ICLP 2005, available from Gopalan Nadathur’s website:

Higher-order pattern unification problems arise often in computations within systems such as Twelf, λProlog and Isabelle. An important characteristic of such problems is that they are given by equations appearing under a prefix of alternating universal and existential quantifiers. Most existing algorithms for solving these problems assume that such prefixes are simplified to a ∀∃∀ form by an a priori application of a transformation known as raising. There are drawbacks to this approach. Mixed quantifier prefixes typically manifest themselves in the course of computation, thereby requiring a dynamic form of preprocessing that is difficult to support in low-level implementations. Moreover, raising may be redundant in many cases and its effect may have to be undone by a subsequent pruning transformation. We propose a method to overcome these difficulties. In particular, a unification algorithm is described that proceeds by recursively descending through the structures of terms, performing raising and other transformations on-the-fly and only as needed.

Equivariant unification

By James Cheney, from RTA 2005, available from James Cheney’s website:

Nominal logic is a variant of first-order logic with special facilities for reasoning about names and binding based on the underlying concepts of swapping and freshness. It serves as the basis of logic programming and term rewriting techniques that provide similar advantages to, but remain simpler than, higher-order logic programming or term rewriting systems. Previous work on nominal rewriting and logic programming has relied on nominal unification, that is, unification up to equality in nominal logic. However, because of nominal logic’s equivariance property, these applications require a stronger form of unification, which we call equivariant unification. Unfortunately, equivariant unification and matching are NP-hard decision problems. This paper presents an algorithm for equivariant unification that produces a complete set of finitely many solutions, as well as NP decision procedure and a version that enumerates solutions one at a time. In addition, we present a polynomial time algorithm for swapping-free equivariant matching, that is, for matching problems in which the swapping operation does not appear.

Higher-order Lazy Narrowing Calculus: a Solver for Higher-order Equations

By Tetsuo Ida, Mircea Marin, and Taro Suzuki, from EUROCAST 2001, available from the SCORE website:

This paper introduces a higher-order lazy narrowing calculus (HOLN for short) that solves higher-order equations over the domain of simply typed λ-terms. HOLN is an extension and refinement of Prehofer’s higher-order narrowing calculus LN using the techniques developed in the refinement of a first-order lazy narrowing calculus LNC. HOLN is defined to deal with both unoriented and oriented equations. It keeps track of the variables which are to be bound to normalized answers. We discuss the operating principle of HOLN, its main properties, i.e. soundness and completeness, and its further refinements. The solving capability of HOLN is illustrated with an example of program calculation.

Optimizing higher-order pattern unification

By Brigitte Pientka and Frank Pfenning, from CADE 2003, available from Frank Pfenning’s website:

We present an abstract view of existential variables in a dependently typed lambda-calculus based on modal type theory. This allows us to justify optimizations to pattern unification such as linearization, which eliminates many unnecessary occurs-checks. The presented modal framework explains a number of features of the current implementation of higher-order unification in Twelf and provides insight into several optimizations. Experimental results demonstrate significant performance improvement in many example applications of Twelf, including those in the area of proof-carrying code.

Higher-order term indexing using substitution trees

By Brigitte Pientka, from ACM Transactions on Computational Logic, available from Brigitte Pientka’s website:

We present a higher-order term indexing strategy based on substitution trees for simply typed lambda-terms. There are mainly two problems in adapting first-order indexing techniques. First many operations used in building an efficient term index and retrieving a set of candidate terms from a large collection are undecidable in general for higher-order terms. Second, the scoping of variables and binders in the higher-order case presents challenges. The approach taken in this paper is to reduce the problem to indexing linear higher-order
patterns, a decidable fragment of higher-order terms, and delay solving terms outside of this fragment. We present insertion of terms into the index based on computing the most specific linear generalization of two linear higher-order patterns, and retrieval based on matching two linear higher-order patterns. Our theoretical framework maintains that terms are in βη-normal form, thereby eliminating the need to re-normalize and raise terms during insertion and retrieval. Finally, we prove correctness of our presented algorithms. This indexing structure is implemented as part of the Twelf system to speed up the execution of the tabled higher-logic programming interpreter.

Higher-order unification via explicit substitutions

By Gilles Dowek, Therese Hardin and Claude Kirchner, from Information and Computation, available from ScienceDirect:

Higher order unification is equational unification for βη-conversion. But it is not first order equational  unification, as substitution has to avoid capture. Thus, the methods for equational unification (such as narrowing) built upon grafting (i.e., substitution without renaming) cannot be used for higher order unification, which needs specific algorithms. Our goal in this paper is to reduce higher order unification to first order equational unification in a suitable theory. This is achieved by replacing substitution by grafting, but this replacement is not straightforward as it raises two major problems. First, some unification problems have solutions with grafting but no solution with substitution. Then equational unification algorithms rest upon the fact that grafting and reduction commute. But grafting and βη-reduction do not commute in λ-calculus and reducing an equation may change the set of its solutions. This difficulty comes from the interaction between the substitutions initiated by βη-reduction and the ones initiated by the unification process. Two kinds of variables are involved: those of βη-conversion and those of unification. So, we need to set up a calculus which distinguishes between these two kinds of variables and such that reduction and grafting commute. For this purpose, the application of a substitution of a reduction variable to a unification one must be delayed until this variable is instantiated. Such a separation and delay are provided by a calculus of explicit substitutions. Unification in such a calculus can be performed by well-known algorithms such as narrowing, but we present a specialised algorithm for greater efficiency. At last we show how to relate unification in λ-calculus and in a calculus with explicit substitutions. Thus, we come up with a new higher order unification algorithm which eliminates some burdens of the previous algorithms, in particular the functional handling of scopes. Huet’s algorithm can be seen as a specific strategy for our algorithm, since each of its steps can be decomposed into elementary ones, leading to a more atomic description of the unification process. Also, solved forms in λ-calculus can easily be computed from solved forms in λσ-calculus.