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Complete Inverted Files for Efficient Text Retrieval and Analysis
Complete Inverted Files for Efficient Text Retrieval and Analysis

Efficient External-Memory Bisimulation on DAGs
Efficient External-Memory Bisimulation on DAGs

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Parallel Synchronization-Free Approximate Data Structure
Parallel Synchronization-Free Approximate Data Structure

... construction algorithms. The data races present in these algorithms may cause them to drop inserted or appended elements. Nevertheless, the algorithms 1) do not crash and 2) may produce a data structure that is accurate enough for its clients to use successfully. We advocate an approach in which the ...
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(pdf of the updated version.)

Semi-Indexing Semi-Structured Data in Tiny Space
Semi-Indexing Semi-Structured Data in Tiny Space

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BINARY TREES AND HEAPS IN JAVA

Tree: A New Overlay with Deterministic Bounds
Tree: A New Overlay with Deterministic Bounds

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Comparison of Skip List Algorithms to Alternative Data Structures

Scalable Distributed Data Structures: A Survey
Scalable Distributed Data Structures: A Survey

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Lecture Notes - McMaster Computing and Software

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... Let X denote the last node encountered that has a balance factor 1 or –1 prior to the insertion If the tree is unbalanced following the insertion, X exists ...
Stacks Stack Abstract Data Type Stack (supporting methods) Stack
Stacks Stack Abstract Data Type Stack (supporting methods) Stack

root parent child leaf node edge
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Decision Procedures for Algebraic Data Types with - LARA
Decision Procedures for Algebraic Data Types with - LARA

... sealed means that the hierarchy cannot be extended outside of the module. The module BSTSet provides its clients with functions to create empty sets and to insert elements into existing sets. Because the client has no information on the type Tree, they use the abstraction function content to view th ...
Structural Signatures for Tree Data Structures
Structural Signatures for Tree Data Structures

Lists - Dr. Manal Helal Moodle Site
Lists - Dr. Manal Helal Moodle Site

Data Structures (810:052) Name:___________________________ / -
Data Structures (810:052) Name:___________________________ / -

... d. children of the node containing “+” e. parent of the node containing “3” f. siblings of the node containing “*” g. leaf nodes of the tree h. subtree who’s root is node contains “+” i. path from node containing “+” to node containing “5” j. branch from root node to “3” k. mark the levels of the tr ...
Data Structures (CS 1520) Name:___________________________ / -
Data Structures (CS 1520) Name:___________________________ / -

... # Methods not supported but in the interface for all # binary trees def getRoot(self): raise AttributeError, "Empty tree" def getLeft(self): raise AttributeError, "Empty tree" def getRight(self): raise AttributeError, "Empty tree" def setRoot(self, item): raise AttributeError, "Empty tree" def setLe ...
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Binary Heap

Efficient Similarity Search for Hierarchical Data in Large Databases
Efficient Similarity Search for Hierarchical Data in Large Databases

< 1 ... 13 14 15 16 17 18 19 20 21 ... 62 >

Red–black tree

A red–black tree is a binary search tree with an extra bit of data per node, its color, which can be either red or black. The extra bit of storage ensures an approximately balanced tree by constraining how nodes are colored from any path from the root to the leaf. Thus, it is a data structure which is a type of self-balancing binary search tree.Balance is preserved by painting each node of the tree with one of two colors (typically called 'red' and 'black') in a way that satisfies certain properties, which collectively constrain how unbalanced the tree can become in the worst case. When the tree is modified, the new tree is subsequently rearranged and repainted to restore the coloring properties. The properties are designed in such a way that this rearranging and recoloring can be performed efficiently.The balancing of the tree is not perfect but it is good enough to allow it to guarantee searching in O(log n) time, where n is the total number of elements in the tree. The insertion and deletion operations, along with the tree rearrangement and recoloring, are also performed in O(log n) time.Tracking the color of each node requires only 1 bit of information per node because there are only two colors. The tree does not contain any other data specific to its being a red–black tree so its memory footprint is almost identical to a classic (uncolored) binary search tree. In many cases the additional bit of information can be stored at no additional memory cost.
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