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1 23 Data Structures on Event Graphs Bernard Chazelle & Wolfgang Mulzer Algorithmica
1 23 Data Structures on Event Graphs Bernard Chazelle & Wolfgang Mulzer Algorithmica

Efficient and Reliable Lock-Free Memory Reclamation Based on
Efficient and Reliable Lock-Free Memory Reclamation Based on

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Data Structures - Test 1 Ο

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... • Separate what you can do with data from how it is represented • Other parts of the program interacts with data through provided operations according to their specifications • Implementation chooses how to represent data and implement its operations ...
Linked Lists ADT By Omieno K.Kelvin Department of Computer
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... determine the location of the next item; Links are usually array subscripts or pointers; The position of the first item is stored separately ...
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... Since each node v has even degree, when we first enter v, there is an unused edge that can be used to get out v.  The only exception is when v is a starting node.  Then we get a circuit (may not contain all edges in G) ...
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Cache-Oblivious Dynamic Search Trees Zardosht Kasheff

... B. Each node of size B holds as many pairs of keys and pointers as it may. The B-tree has uniform depth and is nearly balanced. Traversing an edge down the tree reduces the search space by a factor proportional to 1/B. Thus, B-trees perform data searches in Θ(1 + logB N ) memory transfers. An inform ...
Protein Family Classification using Sparse Markov Transducers
Protein Family Classification using Sparse Markov Transducers

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Linked List - asyrani.com

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Scaling Similarity Joins over Tree-Structured Data

... node in a general rooted ordered labeled tree, a node edit operation (e.g., the deletion of a node) may involve an arbitrary number of changes to the parent-child relationships between nodes. On the other hand, in a binary tree, the number of nodes affected by a node edit operation is strictly const ...
Dynamic Planar Convex Hull
Dynamic Planar Convex Hull

... Saxe [3]. Using the semidynamic deletions only data structure of Hershberger and Suri [12], and a constant number of bootstrapping steps, the construction achieves update times of O(log1+ε n) for any constant ε > 0. The construction uses an augmented variant of an interval tree to store the convex ...
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Advantages of Shared Data Structures for Sequences of Balanced

... We can use rr enclose to compute LCAs in a BPS S[0, 2n − 1] as follows: given two nodes i < j (we identify nodes with the position of their opening parenthesis), first compute k = rr enclose(S, i, j). Now if k 6= ⊥, return enclose(S, k) as LCA(i, j). The other possibility is that k = ⊥, which happen ...
Dynamic Planar Convex Hull - Department of Computer Science
Dynamic Planar Convex Hull - Department of Computer Science

... Saxe [3]. Using the semidynamic deletions only data structure of Hershberger and Suri [12], and a constant number of bootstrapping steps, the construction achieves update times of O(log1+" n) for any constant " > 0. The construction uses an augmented variant of an interval tree to store the convex ...
Slides - IfIS - Technische Universität Braunschweig
Slides - IfIS - Technische Universität Braunschweig

... – There is a total order on all values – Left subtree of a node contains only values less than node value – Right subtree of a node contains only values larger than the node value – Aiming for O(log n) search complexity • Structurally resembles bisection search ...
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... Spatial data management is an active area of research over the past ten years [Same90a, Sameg0b, Laur92, Guti94]. Research interests focused mainly on the design of robust and efficient spatial data structures [Gutt84, Henr89, Guen89, Beck90, Kame94], the invention of new spatial data models [Laur92 ...
Geometric Data Structures
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... discuss some methods for representing convexity, and in Section 1.6 we describe some data structures for representing data that is rectilinear (i.e., aligned with the coordinate axes). Finally, in Section 1.7 we discuss some general techniques for designing geometric data structures. Since geometric ...
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Comparison of Skip List Algorithms to Alternative Data Structures

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Lecture Notes - McMaster Computing and Software

... Finiteness: - the algorithm will terminate after a finite number of steps for all cases. ...
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57:017, Computers in Engineering Dynamic Data Structures

... node pointed to by currentPtr is less than the new data 2.2.2.1 Advance PreviousPtr and CurrentPtr by one node. ...
4.4 B+Trees - IfIS - Technische Universität Braunschweig
4.4 B+Trees - IfIS - Technische Universität Braunschweig

... – In worst case, all cells need to be shifted and all blocks need to be accessed ...
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Lecture 2 Student Notes

... • First, we maintain the lowest leftmost crossing. This is equivalent to the leftmost lowest crossing. This is because of the invariant that all crossings involve horizontal segments with left endpoint left of all errors. • Next, we maintain the left most floating error on each row separately. Exam ...
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CS-240 Data Structures
CS-240 Data Structures

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Interval tree

In computer science, an interval tree is a tree data structure to hold intervals. Specifically, it allows one to efficiently find all intervals that overlap with any given interval or point. It is often used for windowing queries, for instance, to find all roads on a computerized map inside a rectangular viewport, or to find all visible elements inside a three-dimensional scene. A similar data structure is the segment tree.The trivial solution is to visit each interval and test whether it intersects the given point or interval, which requires O(n) time, where n is the number of intervals in the collection. Since a query may return all intervals, for example if the query is a large interval intersecting all intervals in the collection, this is asymptotically optimal; however, we can do better by considering output-sensitive algorithms, where the runtime is expressed in terms of m, the number of intervals produced by the query. Interval trees have a query time of O(log n + m) and an initial creation time of O(n log n), while limiting memory consumption to O(n). After creation, interval trees may be dynamic, allowing efficient insertion and deletion of an interval in O(log n). If the endpoints of intervals are within a small integer range (e.g., in the range [1,...,O(n)]), faster data structures exist with preprocessing time O(n) and query time O(1+m) for reporting m intervals containing a given query point.
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