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Triemaps that match

Simon Peyton Jones, Sebastian Graf

Abstract

The trie data structure is a good choice for finite maps whose keys are data structures (trees) rather than atomic values. But what if we want the keys to be patterns, each of which matches many lookup keys? Efficient matching of this kind is well studied in the theorem prover community, but much less so in the context of statically typed functional programming. Doing so yields an interesting new viewpoint -- and a practically useful design pattern, with good runtime performance.

Triemaps that match

Abstract

The trie data structure is a good choice for finite maps whose keys are data structures (trees) rather than atomic values. But what if we want the keys to be patterns, each of which matches many lookup keys? Efficient matching of this kind is well studied in the theorem prover community, but much less so in the context of statically typed functional programming. Doing so yields an interesting new viewpoint -- and a practically useful design pattern, with good runtime performance.
Paper Structure (35 sections, 2 equations, 3 figures, 3 tables)

This paper contains 35 sections, 2 equations, 3 figures, 3 tables.

Table of Contents

  1. Introduction
  2. The problem we address
  3. Expressions as keys
  4. Alpha-renaming
  5. Lookup modulo matching
  6. Non-solutions
  7. Tries
  8. The interface of a finite map
  9. Tries: the basic idea
  10. Modifying tries
  11. Unions of maps
  12. Folds and the empty map
  13. A type class for triemaps
  14. Singleton maps, and empty maps revisited
  15. Generic programming
  16. ...and 20 more sections

Figures (3)

  • Figure 1: API for various library functions used in this work
  • Figure 2: De Bruijn leveling
  • Figure 3: Benchmarks comparing our trie map (TM) to ordered maps (OM) and hash maps (HM)