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Traversal of a Binary Tree
Traversal of a Binary Tree

heap
heap

Splay Trees
Splay Trees

Advanced pointers and structures
Advanced pointers and structures

... • Finding an element is O(log n) • Adding an element is O(log n) – O(1) if we already know where to add it. • Deleting an element may be complex • Programming complexity is higher than a linked list (just about) ...
3581 - Allama Iqbal Open University
3581 - Allama Iqbal Open University

... Note: All questions carry equal marks. Q. 1 (a) ...
Data Structures CSCI 262, Spring 2002 Lecture 2 Classes and
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... Worst case: Number of comparisons = O(n2) Average case: Number of comparisons = O(n lg n) Approximately: 1.39 n lg(n) + O(n) ...
Data Structures
Data Structures

... repeat if letter <= node_letter take left branch if letter > node_letter take right branch until pointer is nil make new node To see sorted order ... traverse tree with inorder traversal in_order_traverse(ptr) if left_branch_not_nil in_order_traverse (left_branch) list node letter if right_branch_no ...
LinkedDateStructure-PartB
LinkedDateStructure-PartB

Binary Search Tree (Part 1)
Binary Search Tree (Part 1)

... structure of this course: the binary search tree (BST). This is without a doubt one of the most important data structures in computer science. In this lecture, we will focus on the static version of the BST (namely, without considering insertions and deletions), leaving the dynamic version to the ne ...
plaxton_current
plaxton_current

... – Leave back-pointers to object at each hop – If root or best approximate node reached and no Benefits: pointer to object, then it has not been inserted – Decouples tree traversal from any single node – Exploits locality with short-cutting back-pointers – Guaranteed # of hops O(Log(N)) where N = siz ...
pptx - Department of Math and Computer Science
pptx - Department of Math and Computer Science

... • Bottom-visit: print value or operator stored at node • Right-visit: if node is internal, print “)” ...
Advanced Data Structures Spring Semester 2017 Exercise Set 8
Advanced Data Structures Spring Semester 2017 Exercise Set 8

... Invariant 3. Every cycle C has a non-tree edge of maximum weight and maximum level among all the edges in C. Please complete the following two tasks: • Prove that among all the replacement edges, the lightest edge is on the minimum level. • Assume the level of e to be `, and describe how to find the ...
Implementation of a Binary Tree Driver (OAKc) in Cactus
Implementation of a Binary Tree Driver (OAKc) in Cactus

... search could still not achieve better results than O(log 2N). But with parallel processing, speedup can be achieved. Even in galaxy modeling or adaptive mesh refinement, all nodes must be traversed. This is because the algorithm to solve the scientific problem requires us to calculate results from e ...
Implementation of a Binary Tree Driver (OAKc) in
Implementation of a Binary Tree Driver (OAKc) in

... search could still not achieve better results than O(log 2N). But with parallel processing, speedup can be achieved. Even in galaxy modeling or adaptive mesh refinement, all nodes must be traversed. This is because the algorithm to solve the scientific problem requires us to calculate results from e ...
Lists, Hash Tables, Trees - NEMCC Math/Science Division
Lists, Hash Tables, Trees - NEMCC Math/Science Division

... else if (searchTree(current.getLeft()) found = true; else if (searchTree(current.getRight()) found = true; else Note: If binary search tree, one achieves improved search found = false; performance by comparing the return found; current node to item, limiting } // searchTree search to left or right s ...
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Scapegoat tree

CIS 2520 Data Structures: Review Linked list: Ordered Linked List:
CIS 2520 Data Structures: Review Linked list: Ordered Linked List:

CS503: First Lecture, Fall 2008
CS503: First Lecture, Fall 2008

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Slides - UF CISE

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Spanning Trees
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... Build a priority queue of edges with priority being lowest cost Repeat until |V| -1 edges have been accepted { Delete min edge from priority queue If it forms a cycle then discard it else accept the edge – It will join 2 existing trees yielding a larger tree and reducing the forest by one tree ...
Data Structures
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... 12.2 The ArrayList and LinkedList Classes 12.3 Example: A Stack Application and Class 12.4 Example: A Queue Class 12.5 An Introduction to Trees Part of the Picture: Data Structures 12.6 Graphical/Internet Java: A PolygonSketcher Class ...
Binary Trees - Monmouth University
Binary Trees - Monmouth University

Data Structures
Data Structures

... u  Parent, Child: each directed edge defines parent-child u  Sibling: a node that shares the same parent u  Ancestor (Descendant): all nodes on path to root (leaf) u  Left child, right child: if children are ordered, then this ...
$doc.title

Chapter 6
Chapter 6

< 1 ... 58 59 60 61 62 63 64 65 66 ... 76 >

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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