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Project proposal: A meldable, iteratorvalid priority queue, CPH
, 2005
"... Abstract. The Standard Template Library (STL) is a library of generic algorithms and data structures that has been incorporated in the C++ standard and ships with all modern C++ compilers. In the CPH STL project the goal is to implement an enhanced edition of the STL. The priorityqueue class of the ..."
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Abstract. The Standard Template Library (STL) is a library of generic algorithms and data structures that has been incorporated in the C++ standard and ships with all modern C++ compilers. In the CPH STL project the goal is to implement an enhanced edition of the STL. The priorityqueue class of the STL is just an adapter that makes any resizable array to a queue in which the elements stored are arranged according to a given ordering function. In the C++ standard no compulsory support for the operations delete(), increase(), or meld() is demanded even if those are utilized in many algorithms solving graphtheoretic or geometric problems. In this project, the goal is to implement a CPH STL extension of the priorityqueue class which provides, in addition to the normal priorityqueue functionality, the operations delete(), increase(), and meld(). To make the first two of these operations possible, the class must also guarantee that external references to compartments inside the data structure are kept valid at all times.
AND
"... Abstract. We introduce a framework for reducing the number of element comparisons performed in priorityqueue operations. In particular, we give a priority queue which guarantees the worstcase cost of O(1) per minimum finding and insertion, and the worstcase cost of O(log n) with at most log n + O ..."
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Abstract. We introduce a framework for reducing the number of element comparisons performed in priorityqueue operations. In particular, we give a priority queue which guarantees the worstcase cost of O(1) per minimum finding and insertion, and the worstcase cost of O(log n) with at most log n + O(1) element comparisons per deletion, improving the bound of 2 log n + O(1) known for binomial queues. Here, n denotes the number of elements stored in the data structure prior to the operation in question, and log n equals log2(max {2, n}). As an immediate application of the priority queue developed, we obtain a sorting algorithm that is optimally adaptive with respect to the inversion measure of disorder, and that sorts a sequence having n elements and I inversions with at most n log(I/n) + O(n) element comparisons.
Bslack trees: Space Efficient Btrees
"... Abstract. Bslack trees, a subclass of Btrees that have substantially better worstcase space complexity, are introduced. They store n keys in height O(logb n), where b is the maximum node degree. Updates can be performed in O(log b 2 n) amortized time. A relaxed balance version, which is well suit ..."
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Abstract. Bslack trees, a subclass of Btrees that have substantially better worstcase space complexity, are introduced. They store n keys in height O(logb n), where b is the maximum node degree. Updates can be performed in O(log b 2 n) amortized time. A relaxed balance version, which is well suited for concurrent implementation, is also presented. 1
and
"... We introduce a framework for reducing the number of element comparisons performed in priorityqueue operations. In particular, we give a priority queue which guarantees the worstcase cost of O(1) per minimum finding and insertion, and the worstcase cost of O(log n) with at most log n + O(1) element ..."
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We introduce a framework for reducing the number of element comparisons performed in priorityqueue operations. In particular, we give a priority queue which guarantees the worstcase cost of O(1) per minimum finding and insertion, and the worstcase cost of O(log n) with at most log n + O(1) element comparisons per minimum deletion and deletion, improving the bound of 2log n + O(1) known for binomial queues. Here, n denotes the number of elements stored in the data structure prior to the operation in question, and log n equals log 2 (max {2, n}). As an immediate application of the priority queue developed, we obtain a sorting algorithm that is optimally adaptive with respect to the inversion measure of disorder, and that sorts a sequence having n elements and I inversions with at most n log (I/n) + O(n) element comparisons.