Journal of Functional Programming
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This paper presents a very general technique for the implementation of mergeable priority queues. \par The amortized running time is $O(\log n)$ for {\it DeleteMin} and {\it Delete}, and $\Theta(1)$ for all other standard operations. In particular, the operation {\it DecreaseKey} runs in amortized constant time. The worst-case running time is $O(\log n)$ or better for all operations. \par Several examples of mergeable priority queues are given. The examples include priority queues that are particularly well suited for external storage. The space requirement is only two pointers and one information field per item. \par The technique is also used to implement mergeable, double-ended priority queues. For these queues, the worst-case time bound for insertion is $\Theta(1)$, which improves the best previously known bound. For the other operations, the time bounds are the same as the best previously known bounds, worst-case as well as amortized.