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Abstract - Department of Computer Science and Engineering
Abstract - Department of Computer Science and Engineering

... ephemeral – that is, the sequence of revisions leading to the current one was not kept, and thus changes were permanent. Now, with persistent data structures, information no longer has to be flattened to be stored and data that had once been altered is no longer lost. The key to all these improvemen ...
part4-trees
part4-trees

CS 61B Data Structures and Programming Methodology
CS 61B Data Structures and Programming Methodology

1 3,9, ,32,11,50,7
1 3,9, ,32,11,50,7

1. The memory address of the first element of an array is called A
1. The memory address of the first element of an array is called A

... A. Bubble sort B. Insertion sort C. Quick sort D. All of above 33. An algorithm that calls itself directly or indirectly is known as A. Sub algorithm B. Recursion C. Polish notation D. Traversal algorithm 34. In a binary tree, certain null entries are replaced by special pointers which point to node ...
II. Dictionaries
II. Dictionaries

... In this example, the root of the tree is node A. It has two children, B and C. There are many different restrictions you can put on different trees: some require each node to have a specific number of children, others have a maximum depth to which the tree can grow. (The depth of the tree is how ma ...
Answer
Answer

... (g) [10 marks] This question is about a program called SongsOrganiser, that manages a collection of music using a tree structure. The root of the tree is the whole music collection. Below that are nodes that represent music genres. (A genre describes the style of music, for example, rap music, rock, ...
09-trees-bintree
09-trees-bintree

... • Identical (deep) copy of a binary tree – Need to create as many nodes as there are in the binary tree to be copied – Nodes must appear in the same order as in the original binary tree ...
ppt - Dave Reed
ppt - Dave Reed

Persistent Data Structures 2.1 Introduction and motivation
Persistent Data Structures 2.1 Introduction and motivation

II Mid Examination - DATA STRUCTURES THROUGH C
II Mid Examination - DATA STRUCTURES THROUGH C

... b) many non-zero entries c) higher dimension d) none of above 9. Which of the following is a Two-way list? a) Singly linked list b) Doubly linked list c) Circular linked list d) None 10. Two dimensional arrays are also called_____________. a) b) c) d) ...
The data structures presented so far are linear in that items are one
The data structures presented so far are linear in that items are one

... previous slide this has 4 levels. Using this notion of level instead of the conventional notion of depth of a node, we can provide a recursive definition of height of a tree, as shown in this slide. So again, according to this definition, the height of the expression tree given in the previous slide ...
Class Notes for Week 4
Class Notes for Week 4

lecture 6
lecture 6

Binary Trees - jprodriguez.net
Binary Trees - jprodriguez.net

... • Visit order: left subtree, right subtree, node • Must track for the node whether the left and right subtrees have been visited – Solution: Save a pointer to the node, and also save an integer value of 1 before moving to the left subtree and value of 2 before moving to the right subtree – When the ...
General Trees
General Trees

... We can find the root node by following parent pointers upward as far as possible. For this problem, no other type of traversal is necessary, so the parent "pointer" representation described earlier is sufficient. ...
Data Structure for Association Rule Mining: T-Trees and P
Data Structure for Association Rule Mining: T-Trees and P

... enumerate the itemsets according to this ordering. If we consider a data set comprised of just three records with combinations of six items: f1; 3; 4g, f2; 4; 5g, and f2; 4; 6g (and a very low support threshold), then the tree would include one node for each large I (with its support count). The top ...
No Slide Title
No Slide Title

Advanced Data Structure
Advanced Data Structure

data structures used in spatial data mining - TKS
data structures used in spatial data mining - TKS

... minimize the area of all nodes of the tree. But R*–tree combines more criteria: • the area covered by a bounding rectangle • the margin of a rectangle: Minimization of the margin of a bounding rectangle prefers the squares. • the overlap between rectangles: Minimization of the overlap between rectan ...
Lecture 20: Priority Queues
Lecture 20: Priority Queues

... – At least one of the operations, push or pop, will cost linear time, at least if we think of the container as a linear structure. • Binary search trees – If we use the priority as a key, then we can use a combination of finding the minimum key and erase to implement pop. An ordinary binary-search-t ...
ppt - Dave Reed`s
ppt - Dave Reed`s

... tricky, since removing an internal node means rerouting pointers must maintain binary tree structure ...
The Union-Find Problem Kruskal`s algorithm for finding an MST
The Union-Find Problem Kruskal`s algorithm for finding an MST

... then O(1) time, but we have to change a separate pointer for each node in y’s list. This could certainly be O(n) in the worst case. But we noted before that we could either merge x’s set into y’s or vice versa. Does it make a difference? ...
pptx
pptx

Single and Doubly Linked Lists
Single and Doubly Linked Lists

... The polynomial 3x9 + 7x3 + 5 can be represented in a list as follows: (3,9) --> (7,3) --> (5,0) where each pair of integers represent a node, and the arrow represents a link to its neighbouring node. Derivatives of polynomials can be easily computed by proceeding node by node. In our previous exampl ...
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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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