CSS314 Parallel Computing
... An alternative to this iterative version uses partial tours as stack records. This gives code that is closer to the recursive function. However, it also results in a slower version, since it’s necessary for the function that pushes onto the stack to create a copy of the tour before actually pushin ...
... An alternative to this iterative version uses partial tours as stack records. This gives code that is closer to the recursive function. However, it also results in a slower version, since it’s necessary for the function that pushes onto the stack to create a copy of the tour before actually pushin ...
TREES
... always form a minimum height tree but not necessarily of optimum shape. If another node were to be added to a full tree it would become the new root and the resulting tree would be very unbalanced since all nodes below the root would be in the left subtree of the root. This is not really as bad as i ...
... always form a minimum height tree but not necessarily of optimum shape. If another node were to be added to a full tree it would become the new root and the resulting tree would be very unbalanced since all nodes below the root would be in the left subtree of the root. This is not really as bad as i ...
Chapter 2--Basic Data Structures
... ADT uses an array We add elements from left to right A variable keeps track of the index of the top element The array storing the stack elements may become full A push operation will then throw a FullStackException – Limitation of the arraybased implementation – Not intrinsic to the Stack ADT ...
... ADT uses an array We add elements from left to right A variable keeps track of the index of the top element The array storing the stack elements may become full A push operation will then throw a FullStackException – Limitation of the arraybased implementation – Not intrinsic to the Stack ADT ...
CS II: Data Structures Discussion worksheet: Week 9
... if (start > end) return null; // same as (start+end)/2, avoids overflow. int mid = start + (end - start) / 2; Node node = new Node(arr[mid]); node.left = sortedArrayToBST(arr, start, mid-1); node.right = sortedArrayToBST(arr, mid+1, end); return node; ...
... if (start > end) return null; // same as (start+end)/2, avoids overflow. int mid = start + (end - start) / 2; Node node = new Node(arr[mid]); node.left = sortedArrayToBST(arr, start, mid-1); node.right = sortedArrayToBST(arr, mid+1, end); return node; ...
Trees
... – Nodes with the same parents are called siblings – If there is a path from node u to node v, then u is an ancestor of v and v is a descendant of u – Size of a node is the number of descendants the node has including the node itself. The size of a tree is the size of the root. – A node may be consid ...
... – Nodes with the same parents are called siblings – If there is a path from node u to node v, then u is an ancestor of v and v is a descendant of u – Size of a node is the number of descendants the node has including the node itself. The size of a tree is the size of the root. – A node may be consid ...
Binary Tree - WordPress.com
... • A node in the binary tree is called a leaf if it has no left and right children. • The depth (Level) of a node A, in a binary tree is the length of the path from A to the root of the tree. Thus the root is at depth 0. • The depth of the tree is equal to the deepest leaf • The height of a nod A is ...
... • A node in the binary tree is called a leaf if it has no left and right children. • The depth (Level) of a node A, in a binary tree is the length of the path from A to the root of the tree. Thus the root is at depth 0. • The depth of the tree is equal to the deepest leaf • The height of a nod A is ...
Final Solutions
... way is to compute the reverse graph at once and access the adjacency lists). We must do this for each vertex s. Thus, the overall running time is O(EV ). (c) The memory usage is O(E + V ). BFS uses O(V ) extra memory and we only need to run one at a time. (A less efficient solution is to compute a V ...
... way is to compute the reverse graph at once and access the adjacency lists). We must do this for each vertex s. Thus, the overall running time is O(EV ). (c) The memory usage is O(E + V ). BFS uses O(V ) extra memory and we only need to run one at a time. (A less efficient solution is to compute a V ...
fa10 - University of Illinois at Urbana
... MC3 (2.5pts) Suppose we implement a stack using a dynamically allocated array. If the array fills, we are faced with a dilemma. From among the following choices, select the one that best describes our strategy for handling a filled array. (a) We declare a new array, twice as big as the original, an ...
... MC3 (2.5pts) Suppose we implement a stack using a dynamically allocated array. If the array fills, we are faced with a dilemma. From among the following choices, select the one that best describes our strategy for handling a filled array. (a) We declare a new array, twice as big as the original, an ...
pptx
... use these things. Defined in package java.util. Homework: Peruse these two classes in the API package: ArrayList: Implement a list or sequence –some methods:
...
... use these things. Defined in package java.util. Homework: Peruse these two classes in the API package: ArrayList
PPT on Frac_Casc
... is the smallest one larger than or equal to y (O(log(n) with binary search). • While we search further with x and x’ in the main tree we keep track of the entry in the associated arrays. • They can be maintained in constant time by following the pointers. • If v is one of the O(log(n)) nodes we sele ...
... is the smallest one larger than or equal to y (O(log(n) with binary search). • While we search further with x and x’ in the main tree we keep track of the entry in the associated arrays. • They can be maintained in constant time by following the pointers. • If v is one of the O(log(n)) nodes we sele ...
File System Caching Journaling File Systems
... Function: main secondary data storage; also permanent Two possibilities: Extreme speed bottleneck! Capacity not a problem nowadays: 2 TB disks even for PC. But backup becoming a problem. Logical view (view of programmer): Have a tree structure of files together with read/write operation and creation ...
... Function: main secondary data storage; also permanent Two possibilities: Extreme speed bottleneck! Capacity not a problem nowadays: 2 TB disks even for PC. But backup becoming a problem. Logical view (view of programmer): Have a tree structure of files together with read/write operation and creation ...
New_Laboratory_2
... Wikipedia1 defines a tree as: In graph theory, a tree is a graph in which any two vertices are connected by exactly one path. Alternatively, any connected graph with no cycles is a tree. A forest is a disjoint union of trees. Trees are widely used in computer science data structures such as binary s ...
... Wikipedia1 defines a tree as: In graph theory, a tree is a graph in which any two vertices are connected by exactly one path. Alternatively, any connected graph with no cycles is a tree. A forest is a disjoint union of trees. Trees are widely used in computer science data structures such as binary s ...
CIS 321 Data Communications & Networking
... Structured in nodes (tree like structure) Each child node has one and only one parent node (a parent may have more than one child node). We refer to this as a 1-to-many relationship. Progress top down to traverse fields. To find information, you must start at the top with a parent node and trace dow ...
... Structured in nodes (tree like structure) Each child node has one and only one parent node (a parent may have more than one child node). We refer to this as a 1-to-many relationship. Progress top down to traverse fields. To find information, you must start at the top with a parent node and trace dow ...
B-tree
In computer science, a B-tree is a tree data structure that keeps data sorted and allows searches, sequential access, insertions, and deletions in logarithmic time. The B-tree is a generalization of a binary search tree in that a node can have more than two children (Comer 1979, p. 123). Unlike self-balancing binary search trees, the B-tree is optimized for systems that read and write large blocks of data. B-trees are a good example of a data structure for external memory. It is commonly used in databases and filesystems.