Two Constant-Factor-Optimal Realizations of Adaptive Heapsort

In this paper we introduce two efficient priority queues. For both, insert requires O(1) amortized time and extract-min O(lgn) worstcase time including at most lgn+O(1) element comparisons, where n is the number of elements stored. One priority queue is based on a weak heap (array-based) and the other on a weak queue (pointer-based). In both, the main idea is to temporarily store the inserted elements in a buffer, and once it is full to move its elements to the main queue using an efficient bulk-insertion procedure. By employing the new priority queues in adaptive heapsort, we guarantee, for several measures of disorder, that the formula expressing the number of element comparisons performed by the algorithm is optimal up to the constant factor of the high-order term. We denote such performance as constant-factor optimality. Unlike some previous constant-factor-optimal adaptive sorting algorithms, adaptive heapsort relying on the developed priority queues is practically workable.