Abstract

We present a tree difference algorithm with expected sequential execution time O(n log log n) and expected parallel execution time of O(log n), for trees of size n. The algorithm assumes unique labels and permits operations only on leaves and frontier subtrees. Despite these limitations, it can be useful in the analysis of structured text. 1 Applications of Tree Difference In this paper we describe an algorithm for determining the difference between two trees under the assumption that each node has a unique label chosen from an ordered set. The algorithm uses a novel form of hashing to quickly extract neighbourhood information for each node. In a second phase, this neighbourhood information is processed to determine what differences exist between the trees. We assume that trees may be arbitrarily branching, and that the following operations may have been applied to them: 1. a node was inserted to become a new leaf; 2. a leaf node was deleted; 3. a leaf node was moved to become a lea...

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