Design Patterns for the Implementation of Graph Algorithms
... avoid implementing an algorithm multiply times, algorithms are implemented once and made available in a library which can then be used by any program needing an algorithm from the library. Examples for algorithms found in libraries are sorting algorithms, algorithms to solve linear equations, or alg ...
... avoid implementing an algorithm multiply times, algorithms are implemented once and made available in a library which can then be used by any program needing an algorithm from the library. Examples for algorithms found in libraries are sorting algorithms, algorithms to solve linear equations, or alg ...
public boolean - Pitt Computer Science
... subclass objects If a method is defined in both the superclass and subclass (with identical signatures), the version corresponding to each class will be used in a call from the array • Idea is that the methods are similar in nature but the redefinition in the subclass gears the method more specific ...
... subclass objects If a method is defined in both the superclass and subclass (with identical signatures), the version corresponding to each class will be used in a call from the array • Idea is that the methods are similar in nature but the redefinition in the subclass gears the method more specific ...
Estimating Quantiles from the Union of Historical and Streaming Data
... versus the desired rank, and the approximation error is defined to be the worst case difference between the rank of the element that is returned and the derived rank. Given an approximation parameter ∈ (0, 1], and a constant φ ∈ (0, 1], our goal is to design a method that identifies an approximate ...
... versus the desired rank, and the approximation error is defined to be the worst case difference between the rank of the element that is returned and the derived rank. Given an approximation parameter ∈ (0, 1], and a constant φ ∈ (0, 1], our goal is to design a method that identifies an approximate ...
SnapQueue: Lock-Free Queue with Constant Time Snapshots
... When SnapQueue size is less than L, the elements are stored as a segment. SnapQueue overcomes segment’s Loperations limit by reallocating the segment when it becomes full. To overcome boundedness, SnapQueue uses a secondary representation: a segment-support pair. When the number of elements exceeds ...
... When SnapQueue size is less than L, the elements are stored as a segment. SnapQueue overcomes segment’s Loperations limit by reallocating the segment when it becomes full. To overcome boundedness, SnapQueue uses a secondary representation: a segment-support pair. When the number of elements exceeds ...
Minimum Bounding Boxes
... spatial indexing by Guttman in [2]. Guttman’s idea was to have each index record in a leaf node of an R-Tree be identified by the smallest enclosing rectangle that spatially contains the n-dimensional data object and a pointer to the file containing the actual representation of the object. It has si ...
... spatial indexing by Guttman in [2]. Guttman’s idea was to have each index record in a leaf node of an R-Tree be identified by the smallest enclosing rectangle that spatially contains the n-dimensional data object and a pointer to the file containing the actual representation of the object. It has si ...
CPSC 3200 Algorithm Analysis and Advanced Data Structure
... • Java is strongly-typed, which means that all variables must first be declared before they can be used. • A collection of values along with a set of operations that can be performed on those values. (the definition of a class). • Java has a large library of classes that have been written for us to ...
... • Java is strongly-typed, which means that all variables must first be declared before they can be used. • A collection of values along with a set of operations that can be performed on those values. (the definition of a class). • Java has a large library of classes that have been written for us to ...
A Hardware Processing Unit for Point Sets
... for maximum throughput and for moderate chip area consumption. We furthermore designed every functional unit to take maximum advantage of hardware parallelism. Multithreading and pipelining were applied to hide memory and arithmetic latencies. The fixed function data path also allows for minimal thr ...
... for maximum throughput and for moderate chip area consumption. We furthermore designed every functional unit to take maximum advantage of hardware parallelism. Multithreading and pipelining were applied to hide memory and arithmetic latencies. The fixed function data path also allows for minimal thr ...
lecture10
... when tables are sparse • Double hashing is space efficient, fast (get initial hash and increment at the same time), needs careful implementation ...
... when tables are sparse • Double hashing is space efficient, fast (get initial hash and increment at the same time), needs careful implementation ...
Mining Frequent Patterns without Candidate Generation
... set generation-and-test approach. However, candidate set generation is still costly, especially when there exist proli c patterns and/or long patterns. In this study, we propose a novel frequent pattern tree (FP-tree) structure, which is an extended pre xtree structure for storing compressed, crucia ...
... set generation-and-test approach. However, candidate set generation is still costly, especially when there exist proli c patterns and/or long patterns. In this study, we propose a novel frequent pattern tree (FP-tree) structure, which is an extended pre xtree structure for storing compressed, crucia ...
Optimal Encodings for Range Min-Max and Top-k
... U together in blocks of lg4n each, using the lookup table L: note that we can advance in U correctly by determining t by counting the number of 1 bits in either in √ s1 or s3 . This can be done using either an additional lookup table of size Θ( n) using constant time, or by storing the answer explic ...
... U together in blocks of lg4n each, using the lookup table L: note that we can advance in U correctly by determining t by counting the number of 1 bits in either in √ s1 or s3 . This can be done using either an additional lookup table of size Θ( n) using constant time, or by storing the answer explic ...
Interval Sequences: An Object-Relational Approach to
... intersections of interval sequences. By following this approach, derived index data is stored in one or more index tables besides the original data table. An index table is organized by a built-in index structure, e.g. a B+-tree. Queries and updates on relational storage structures are processed by ...
... intersections of interval sequences. By following this approach, derived index data is stored in one or more index tables besides the original data table. An index table is organized by a built-in index structure, e.g. a B+-tree. Queries and updates on relational storage structures are processed by ...
Represent the given sparse matrix using Linked List
... 4. If ch=2 to check if list =0 then print “Empty list” else if n is list then delete the node n 5. If ch=3 then read position value and set n as malloc size and read num value and store in n. 6. If ch =4 then check list as NULL or not. If NULL then print “ Empty list” Else check I not equal to pos t ...
... 4. If ch=2 to check if list =0 then print “Empty list” else if n is list then delete the node n 5. If ch=3 then read position value and set n as malloc size and read num value and store in n. 6. If ch =4 then check list as NULL or not. If NULL then print “ Empty list” Else check I not equal to pos t ...
Quick Start Guide for Server Clusters
... This guide provides system requirements, installation instructions, and other, step-by-step instructions that you can use to deploy server clusters with installed FIX Edge if you are using Microsoft® Windows Server™ 2003, Enterprise Edition operating system. The server cluster technology in Windows ...
... This guide provides system requirements, installation instructions, and other, step-by-step instructions that you can use to deploy server clusters with installed FIX Edge if you are using Microsoft® Windows Server™ 2003, Enterprise Edition operating system. The server cluster technology in Windows ...
When to use splay trees
... predictor for these data structures. A randomly built BST is often a good choice for an application that requires fast insertion, deletion, and lookup of items, as well as fast ‘ordered’ operations such as traversals or range queries§ . However, if the lookup distribution is heavily skewed, a splay ...
... predictor for these data structures. A randomly built BST is often a good choice for an application that requires fast insertion, deletion, and lookup of items, as well as fast ‘ordered’ operations such as traversals or range queries§ . However, if the lookup distribution is heavily skewed, a splay ...
Oblivious Data Structures - Cryptology ePrint Archive
... Blanton, Steele and Alisagari [8] present oblivious graph algorithms, such as breadth-first search, singlesource single-destination (SSSD), minimum spanning tree and maximum flow with nearly optimal complexity on dense graphs. Our work provides asymptotically better algorithms for special types of s ...
... Blanton, Steele and Alisagari [8] present oblivious graph algorithms, such as breadth-first search, singlesource single-destination (SSSD), minimum spanning tree and maximum flow with nearly optimal complexity on dense graphs. Our work provides asymptotically better algorithms for special types of s ...
Skip List Data Structures for Multidimensional Data
... As defined in Knuth [1973], a range query asks for records (in a file F containing n records) whose attributes fall within a specific range of values (e.g. height > 6’2” or $23,000 ≤ annual income ≤ $65,000). We will call these limits L for low and H for high. Boolean combinations of range queries o ...
... As defined in Knuth [1973], a range query asks for records (in a file F containing n records) whose attributes fall within a specific range of values (e.g. height > 6’2” or $23,000 ≤ annual income ≤ $65,000). We will call these limits L for low and H for high. Boolean combinations of range queries o ...
B-tree
In computer science, a B-tree is a tree data structure that keeps data sorted and allows searches, sequential access, insertions, and deletions in logarithmic time. The B-tree is a generalization of a binary search tree in that a node can have more than two children (Comer 1979, p. 123). Unlike self-balancing binary search trees, the B-tree is optimized for systems that read and write large blocks of data. B-trees are a good example of a data structure for external memory. It is commonly used in databases and filesystems.