11 Associations

MIT/GNU Scheme provides several mechanisms for associating objects with one another. Each of these mechanisms creates a link between one or more objects, called keys, and some other object, called a datum. Beyond this common idea, however, each of the mechanisms has various different properties that make it appropriate in different situations:

• Association lists are one of Lisp’s oldest association mechanisms. Because they are made from ordinary pairs, they are easy to build and manipulate, and very flexible in use. However, the average lookup time for an association list is linear in the number of associations.
• 1D tables have a very simple interface, making them easy to use, and offer the feature that they do not prevent their keys from being reclaimed by the garbage collector. Like association lists, their average lookup time is linear in the number of associations; but 1D tables aren’t as flexible.
• The association table is MIT/GNU Scheme’s equivalent to the property lists of Lisp. It has the advantages that the keys may be any type of object and that it does not prevent the keys from being reclaimed by the garbage collector. However, two linear-time lookups must be performed, one for each key, whereas for traditional property lists only one lookup is required for both keys.
• Hash tables are a powerful mechanism with constant-time access to large amounts of data. Hash tables are not as flexible as association lists, but because their access times are independent of the number of associations in the table, for most applications they are the mechanism of choice.
• Balanced binary trees are another association mechanism that is useful for applications in which the keys are ordered. Binary trees have access times that are proportional to the logarithm of the number of associations in the tree. While they aren’t as fast as hash tables, they offer the advantage that the contents of the tree can be converted to a sorted alist in linear time. Additionally, two trees can be compared for equality in worst-case linear time.
• Red-Black trees are a kind of balanced binary tree. The implementation supports destructive insertion and deletion operations with a good constant factor.
• Weight-Balanced trees are a kind of balanced binary tree. The implementation provides non-destructive operations. There is a comprehensive set of operations, including: a constant-time size operation; many high-level operations such as the set operations union, intersection and difference; and indexing of elements by position.