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Generalizing Generalized Tries
, 1999
"... A trie is a search tree scheme that employs the structure of search keys to organize information. Tries were originally devised as a means to represent a collection of records indexed by strings over a fixed alphabet. Based on work by C.P. Wadsworth and others, R.H. Connelly and F.L. Morris generali ..."
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Cited by 31 (8 self)
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A trie is a search tree scheme that employs the structure of search keys to organize information. Tries were originally devised as a means to represent a collection of records indexed by strings over a fixed alphabet. Based on work by C.P. Wadsworth and others, R.H. Connelly and F.L. Morris generalized the concept to permit indexing by elements of an arbitrary monomorphic datatype. Here we go one step further and define tries and operations on tries generically for arbitrary firstorder polymorphic datatypes. The derivation is based on techniques recently developed in the context of polytypic programming. It is well known that for the implementation of generalized tries nested datatypes and polymorphic recursion are needed. Implementing tries for polymorphic datatypes places even greater demands on the type system: it requires rank2 type signatures and higherorder polymorphic nested datatypes. Despite these requirements the definition of generalized tries for polymorphic datatypes is...
Numerical Representations as HigherOrder Nested Datatypes
, 1998
"... Number systems serve admirably as templates for container types: a container object of size n is modelled after the representation of the number n and operations on container objects are modelled after their numbertheoretic counterparts. Binomial queues are probably the first data structure that wa ..."
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Cited by 7 (2 self)
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Number systems serve admirably as templates for container types: a container object of size n is modelled after the representation of the number n and operations on container objects are modelled after their numbertheoretic counterparts. Binomial queues are probably the first data structure that was designed with this analogy in mind. In this paper we show how to express these socalled numerical representations as higherorder nested datatypes. A nested datatype allows to capture the structural invariants of a numerical representation, so that the violation of an invariant can be detected at compiletime. We develop a programming method which allows to adapt algorithms to the new representation in a mostly straightforward manner. The framework is employed to implement three different container types: binary randomaccess lists, binomial queues, and 23 finger search trees. The latter data structure, which is treated in some depth, can be seen as the main innovation from a datastruct...
Dependently Typed Data Structures \Lambda
"... Abstract The mechanism for declaring datatypes in functional programming languages such as ML and Haskellis of great use in practice. This mechanism, however, often suffers from its imprecision in capturing the invariants inherent in data structures. We remedy the situation with the introduction of ..."
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Abstract The mechanism for declaring datatypes in functional programming languages such as ML and Haskellis of great use in practice. This mechanism, however, often suffers from its imprecision in capturing the invariants inherent in data structures. We remedy the situation with the introduction of dependent datatypesso that we can model data structures with significantly more accuracy. We present a few interesting examples such as implementations of redblack trees and binomial heaps to illustrate the use of dependentdatatypes in capturing some sophisticated invariants in data structures. We claim that dependent datatypes can enable the programmer to implement algorithms in a way that is more robust and easier to understand.