Abstract
We describe an efficient representation of purely functional arrays suggested by Holmström and Hughes, here calledversion tree arrays orv-arrays. A collection of arrays is represented by aversion tree where the root array is stored in contiguous memory as usual and every other array is represented as a node that records the difference to its father. Updating is done by adding a new node to the version tree and takes constant time, while the time for subscripting is proportional to the distance to the root. Essential for efficiency is therefore the possibility to reroot the tree without changing the semantics of the subscript operation, i.e. the values that the arrays represent.
We also show howv-arrays can be implemented in Standard ML and compare the efficiency ofv-arrays to other representations, like binary trees, lists and functions, by measuring the execution time of some programs that use sequences.v-arrays turn out to be superior in practice in algorithms that use arrays singlethreadedly and access them randomly.
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This work has been supported by STU, the Swedish Board for Technical Development.