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We present an efficient algorithm which can check the answers given by the fundamental abstract data types priority queues and mergeable priority queues. This is the first linear-time checker for mergeable priority queues. These abstract data types are widely used in routing, scheduling, simulation, computational geometry and many other algorithmic domains. We have implemented our answer checker and have performed experiments comparing the speed of our checker to recently benchmarked priority queue and mergeable priority queue implementations, and our checker is substantially faster than the best of these implementations. 1 Introduction This paper concerns the fundamental abstract data types of priority queues (PQs) and mergeable priority queues (MPQs). These abstract data types have been recognized as centrally important from the early days of computer-algorithm design. They appear in seminal algorithm texts such as Knuth's [10] and Aho, Hopcroft and Ullman's [1]. Data structure impl...

Brodal recently introduced the first implementation of imperative priority queues to support findMin, insert, and meld in O(1) worst-case time, and deleteMin in O(log n) worst-case time. These bounds are asymptotically optimal among all comparison-based priority queues. In this paper, we adapt Brodal's data structure to a purely functional setting. In doing so, we both simplify the data structure and clarify its relationship to the binomial queues of Vuillemin, which support all four operations in O(log n) time. Specifically, we derive our implementation from binomial queues in three steps: first, we reduce the running time of insert to O(1) by eliminating the possibility of cascading links; second, we reduce the running time of findMin to O(1) by adding a global root to hold the minimum element; and finally, we reduce the running time of meld to O(1) by allowing priority queues to contain other priority queues. Each of these steps is expressed using ML-style functors. The last transformation, known as data-structural bootstrapping, is an interesting application of higher-order functors and recursive structures.

Edison is a library of functional data structures implemented in Haskell. It supports three main families of abstractions: sequences, collections (e.g., sets and priority queues), and associative collections (e.g., nite maps). This paper summarizes the design of Edison, with particular attention to how that design is inuenced by details of Haskell. 1 Introduction There is a growing recognition that a useful set of libraries is at least as important to the acceptance of a programming language as the design of the language itself. A library of fundamental data structures such as queues, sets, and nite maps is particularly important in this regard. However, high-quality examples of such libraries, such as the STL [14] in C++ or the the collection classes [3] in Smalltalk, are rare. Edison is a library of ecient data structures suitable for implementation and use in functional programming languages. It is named after Thomas Alva Edison and for the mnemonic value of EDiSon (Ecient Data ...

The ability to perform efficient collision detection is essential in virtual reality environments and their applications, such as walkthroughs. In this paper we re-explore a classical structure used for collision detection -- the binary space partitioning tree. Unlike the common approach, which attributes equal likelihood to each possible query, we assume events that happened in the past are more likely to happen again in the future. This leads us to the definition of self-customized data structures. We report encouraging results obtained while experimenting with this concept in the context of self-customized bsp trees. Keywords: Collision detection, binary space partitioning, self-customization. 1 Introduction Virtual reality refers to the use of computer graphics to simulate physical worlds or to generate synthetic ones, where a user is to feel immersed in the environment to the extent that the user feels as if "objects" seen are really there. For example, "objects" should m...

views of amortization : : : : : : : : : : : : : : : : : : : 44 4 Implementation aspects 49 4.1 Functional program notation : : : : : : : : : : : : : : : : : : : : 50 4.2 Eager evaluation : : : : : : : : : : : : : : : : : : : : : : : : : : : 51 4.3 Pointer implementation of stacks : : : : : : : : : : : : : : : : : : 52 4.4 Destructivity : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 54 4.5 Queues and concatenable deques : : : : : : : : : : : : : : : : : : Contents iii 4.6 Linear usage of destructive monoalgebras : : : : : : : : : : : : : 58 4.7 Benevolent side-effects : : : : : : : : : : : : : : : : : : : : : : : : 61 5 Analysis of functional programs and algebras 63 5.1 Cost measures : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 63 5.2 Worst-case analysis : : : : : : : : : : : : : : : : : : : : : : : : : : 67 5.3 Amortized cost of functions : : : : : : : : : : : : : : : : : : : : : 69 5.4 Amortized analysis : : : : : : : : : : : : : : : : : : : : : : : : : ...

this paper, we are concerned primarily with the insert and delete min operations. The different data structures that have been proposed for the representation of a priority queue differ in terms of the performance guarantees they provide. Some guarantee good performance on a per operation basis while others do this only in the amortized sense. Heaps permit one to delete the min element and insert an arbitrary element into an n element priority queue in O(logn) time per operation; a find min takes O(1) time. Additionally, a heap is an implicit data structure that has no storage overhead associated with it. All other priority queue structures are pointer-based and so require additional storage for the pointers. Leftist trees also support the insert and delete min operations in O(log n) time per operation and the find min operation in O(1) time. Additionally, they permit us to meld pairs of priority queues in logarithmic time

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Part of this work has been presented in [17]. This paper analyzes the performances of portable distributed priority queues by examining the theoretical features required and by comparing various implementations. In spite of intrinsic bottlenecks and induced hot-spots, we argue that tree topologies are attractive to manage the natural centralized control required for the deletemin operation in order to detect the site which holds the item with the largest priority. We introduce an original perfect balancing to cope with the load variation due to the priority queue operations which continuously modify the overall number of items in the network. For comparison, we introduce the d-heap and the binomial distributed priority queue. The purpose of this experiment is to convey, through executions on Cray-T3D and MeikoT800, an understanding of the nature of the distributed priority queues, the range of their concurrency and a comparison of their efficiency to reduce requests latency. In particu...

We introduce a new technique to bound the asymptotic performance of splay trees. The basic idea is to transcribe, in an indirect fashion, the rotations performed by the splay tree as a Davenport-Schinzel sequence S, none of whose subsequences are isomorphic to fixed forbidden subsequence. We direct this technique towards Tarjan’s deque conjecture and prove that n deque operations require O(nα ∗ (n)) time, where α ∗ (n) is the minimum number of applications of the inverse-Ackermann function mapping n to a constant. We are optimistic that this approach could be directed towards other open conjectures on splay trees such as the traversal and split conjectures.