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2013S
2013S

... b) Suppose the following list of numbers is inserted in order into an empty binary search tree: 45, 32, 90, 34, 68, 72, 15, 24, 30, 66, 11, 50, 10. Construct the binary search tree. (8M+8M) ...
Introduction to Graph with Breadth First Search(BFS) and Depth First
Introduction to Graph with Breadth First Search(BFS) and Depth First

continued
continued

...  A node contains two references (to left and right child nodes)  A node contains a data field  The data field has type Comparable, so that you can compare the values in order to place them in the correct position in the binary search tree ...
data structure(ds) question bank with answer
data structure(ds) question bank with answer

... A Queue is an ordered list in which all insertions take place at one end called the rear, while all deletions take place at the other end called the front. Queue is also referred as First In First Out (FIFO) list. 32. What are the various operations performed on the Queue? 33. How do you test for an ...
VP-tree: Content-Based Image Indexing
VP-tree: Content-Based Image Indexing

Abstract Data Types
Abstract Data Types

... The model above assumes small number, P, of priorities, large number of items entered and removed from queue, as in processing messages with priorities on a communication channel or scheduling threads. Another model, leading to Heap Sort uses a heap structure to handle many priorities (often as many ...
continued
continued

...  A node contains two references (to left and right child nodes)  A node contains a data field  The data field has type Comparable, so that you can compare the values in order to place them in the correct position in the binary search tree ...
Algoritmos y Programacion II
Algoritmos y Programacion II

Link-cut Trees
Link-cut Trees

Lecture15-Trees - Mount Holyoke College
Lecture15-Trees - Mount Holyoke College

Chapter2
Chapter2

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lecture18

B Trees
B Trees

... nodes and internal nodes. B-trees keep values in every node in the tree, and may use the same structure for all nodes. However, since leaf nodes never have children, a specialized structure for leaf nodes in B-trees will improve performance. Unlike a binary-tree, each node of a b-tree may have a var ...
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Multiple choice questions Answer on Scantron Form

Chapter 7 Data Structure Transformations
Chapter 7 Data Structure Transformations

... whose size is a power of two, and only one block of each size. Thus there are at most log n blocks. • This gives a bad worst-case complexity because we might have to rebuild everything into one structure; but the structure of size 2i is rebuilt only when the ith bit of n changes, which is every 2i−1 ...
PRACTICAL: 4(B)
PRACTICAL: 4(B)

... KNOWLEDGE REQUIRED: Binary Tree THEORY/LOGIC: Definition: A binary search tree is a binary tree. It may be empty. If it is not empty then it satisfies the following properties: (1) The root element has a key. (2) The keys (if any) in the left subtree are smaller than the key in the root. (3) The key ...
Interval Sequences: An Object-Relational Approach to
Interval Sequences: An Object-Relational Approach to

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3.3 Path Copying - Transactional Data Structures

Fundamentals of Python: From First Programs Through Data
Fundamentals of Python: From First Programs Through Data

Ternary Tree Optimalization for n-gram Indexing - CEUR
Ternary Tree Optimalization for n-gram Indexing - CEUR

... For sentence indexing is appropriate to use two-level (double) indexing. This approach saves a lot of computer memory, because words in all sentences are many times repeated. Common ternary tree n-gram indexing and n-gram double indexing using ternary trees are two borderline cases. Single ternary t ...
Abstract
Abstract

Balanced Binary Search Trees
Balanced Binary Search Trees

... • balanced BST maintains h = O(lg n) ⇒ all operations run in O(lg n) time. ...
A Fast Contention-Friendly Binary Search Tree
A Fast Contention-Friendly Binary Search Tree

Relativistic Red-Black Trees - PDXScholar
Relativistic Red-Black Trees - PDXScholar

... from the root to the leaf. These invariants are sufficient to guarantee O (log(N )) lookups because the longest possible path (alternating black and red nodes) is at most twice the shortest possible path (all black nodes). The operations required to rebalance a tree following an insert or delete are ...
S(b)-Trees: An Optimal Balancing of Variable Length Keys
S(b)-Trees: An Optimal Balancing of Variable Length Keys

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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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