Chapter 11 - Introduction to Abstract Data Types (ADTs)
... A complete graph is one in which there is an edge between every pair of vertices. A cycle or ring is a connected graph in which there is exactly one path from any node back to itself. Many local area networks (LANs) are based on ring topologies in which each computer is represented by a node in the ...
... A complete graph is one in which there is an edge between every pair of vertices. A cycle or ring is a connected graph in which there is exactly one path from any node back to itself. Many local area networks (LANs) are based on ring topologies in which each computer is represented by a node in the ...
Optimizing Query Time in a Bounding Volume
... Our first optimization efforts concentrated on reducing memory segmentation and the size of the data. Rather than allocating each node individually on the heap, we instead store the tree nodes in a large, contiguous 1D array. This already improves performance due to less memory segmentation, but als ...
... Our first optimization efforts concentrated on reducing memory segmentation and the size of the data. Rather than allocating each node individually on the heap, we instead store the tree nodes in a large, contiguous 1D array. This already improves performance due to less memory segmentation, but als ...
Mod 10 - nptel
... The largest element is at the root, but its position in sorted array should be at last. So, swap the root with the last element. We have placed the highest element in its correct position. We left with an array of n-1 elements. repeat the same of these remaining n-1 elements to place the next larg ...
... The largest element is at the root, but its position in sorted array should be at last. So, swap the root with the last element. We have placed the highest element in its correct position. We left with an array of n-1 elements. repeat the same of these remaining n-1 elements to place the next larg ...
Data Structures (CS 1520) Lecture 24 Name:_________________
... Implementation of Files on Disk- how are blocks allocated? 4. non-contiguous - scattered across linear address space of OS and disk ...
... Implementation of Files on Disk- how are blocks allocated? 4. non-contiguous - scattered across linear address space of OS and disk ...
Lecture 10
... such that for every node except for the root, the node’s key is greater than or equal to its parent’s ► The root of a heap contains the element with the minimum-valued key (highest priority) ► Insertion and removal operations for a heap both run in O( log n ) time ...
... such that for every node except for the root, the node’s key is greater than or equal to its parent’s ► The root of a heap contains the element with the minimum-valued key (highest priority) ► Insertion and removal operations for a heap both run in O( log n ) time ...
Elementary Data Structures
... whose key is from a totally ordered set S , returns the next largest (smallest) element in S , or NIL if x is the maximum (minimum) element. ...
... whose key is from a totally ordered set S , returns the next largest (smallest) element in S , or NIL if x is the maximum (minimum) element. ...
Amortization - Jeff Erickson
... (More precisely, the number of flips is exactly 2n − #1(n), where #1(n) is the number of 1 bits in the binary representation of n.) Thus, on average, each call to Increment flips just less than two bits, and therefore runs in constant time. This sense of “on average” is quite different from the aver ...
... (More precisely, the number of flips is exactly 2n − #1(n), where #1(n) is the number of 1 bits in the binary representation of n.) Thus, on average, each call to Increment flips just less than two bits, and therefore runs in constant time. This sense of “on average” is quite different from the aver ...
Linked List data structure
... When comparing implementations based on singly or doubly-linked lists, there is in fact no overall winner. Both have their pros and cons, making one of them the better choice in some instances, but less than ideal in others. For each data structure mentioned above, we will decide whether a singly or ...
... When comparing implementations based on singly or doubly-linked lists, there is in fact no overall winner. Both have their pros and cons, making one of them the better choice in some instances, but less than ideal in others. For each data structure mentioned above, we will decide whether a singly or ...
Lecture1MRM
... Using the union-find algorithm We put rooms into an equivalence class if there is a path connecting them. Before adding an edge (x,y) to the tree, make sure that x and y are not in the same equivalence class. ...
... Using the union-find algorithm We put rooms into an equivalence class if there is a path connecting them. Before adding an edge (x,y) to the tree, make sure that x and y are not in the same equivalence class. ...
ppt - York University
... • An ADT does not specify how the data are stored or how the operations are implemented. • The abstraction of an ADT facilitates – Design of complex systems. Representing complex data structures by concise ADTs, facilitates reasoning about and designing large systems of many interacting data structu ...
... • An ADT does not specify how the data are stored or how the operations are implemented. • The abstraction of an ADT facilitates – Design of complex systems. Representing complex data structures by concise ADTs, facilitates reasoning about and designing large systems of many interacting data structu ...
Algorithm Cost
... • Used when we only know the asymptotic upper bound. • If you are not guaranteed certain input, then it is a valid upper bound that even the worstcase input will be below. • May often be determined by inspection of an algorithm. • Thus we don’t have to do a proof! ...
... • Used when we only know the asymptotic upper bound. • If you are not guaranteed certain input, then it is a valid upper bound that even the worstcase input will be below. • May often be determined by inspection of an algorithm. • Thus we don’t have to do a proof! ...
Queues 2
... Heaps Heaps are often used for priority queues Heap is a binary tree Complete – every level full but the last Children are smaller (min)/larger (max) than the parent ...
... Heaps Heaps are often used for priority queues Heap is a binary tree Complete – every level full but the last Children are smaller (min)/larger (max) than the parent ...
Binary search tree
In computer science, binary search trees (BST), sometimes called ordered or sorted binary trees, are a particular type of containers: data structures that store ""items"" (such as numbers, names and etc.) in memory. They allow fast lookup, addition and removal of items, and can be used to implement either dynamic sets of items, or lookup tables that allow finding an item by its key (e.g., finding the phone number of a person by name).Binary search trees keep their keys in sorted order, so that lookup and other operations can use the principle of binary search: when looking for a key in a tree (or a place to insert a new key), they traverse the tree from root to leaf, making comparisons to keys stored in the nodes of the tree and deciding, based on the comparison, to continue searching in the left or right subtrees. On average, this means that each comparison allows the operations to skip about half of the tree, so that each lookup, insertion or deletion takes time proportional to the logarithm of the number of items stored in the tree. This is much better than the linear time required to find items by key in an (unsorted) array, but slower than the corresponding operations on hash tables.They are a special case of the more general B-tree with order equal to two.