Data Structure and Algorithm Analysis part 4
... Like binary search trees, binary heaps have two properties, namely, a structure property and a heap order property. ...
... Like binary search trees, binary heaps have two properties, namely, a structure property and a heap order property. ...
advanced algorithms
... Proof: By definition, every path from a node to any leaf contains the same number of black nodes. By Theorem1, a least ½ the nodes on any such path are black. Therefore, there can no more than twice as many nodes on any path from N to a leaf as on any other path. Therefore the length of every path i ...
... Proof: By definition, every path from a node to any leaf contains the same number of black nodes. By Theorem1, a least ½ the nodes on any such path are black. Therefore, there can no more than twice as many nodes on any path from N to a leaf as on any other path. Therefore the length of every path i ...
PDS-II 2 marks and 16 marks
... • Functions share global data. • Data move openly around the system from function to function. • Functions transform data from one form to another. • Employs top-down approach in program design. 2. What are the features of Object Oriented Programming? • Emphasis is on data rather than procedure. • P ...
... • Functions share global data. • Data move openly around the system from function to function. • Functions transform data from one form to another. • Employs top-down approach in program design. 2. What are the features of Object Oriented Programming? • Emphasis is on data rather than procedure. • P ...
Data Structure Analysis: An Efficient Context
... of the potential cost, as explained below. In contrast, “shape analysis” algorithms are powerful enough to provide the information we require and more, e.g., enough to identify a particular structure as a “linked-list” or “binary tree” [10, 19]. Shape analysis, however, is too expensive to be pract ...
... of the potential cost, as explained below. In contrast, “shape analysis” algorithms are powerful enough to provide the information we require and more, e.g., enough to identify a particular structure as a “linked-list” or “binary tree” [10, 19]. Shape analysis, however, is too expensive to be pract ...
Data Structures
... 2. Edges or arcs, or lines defined by two or more nodes, sometimes called 1dimensional cells 3. Polygons or Areas defined by 3 or more arcs and nodes, sometimes called 2dimensional cells For a topological database the points, lines, and areas exist in 2-D space. The rules for this space say that lin ...
... 2. Edges or arcs, or lines defined by two or more nodes, sometimes called 1dimensional cells 3. Polygons or Areas defined by 3 or more arcs and nodes, sometimes called 2dimensional cells For a topological database the points, lines, and areas exist in 2-D space. The rules for this space say that lin ...
Self-Adjusting Binary Search Trees
... 1. Introduction In this paper we apply the related concepts of amortized complexity and se& adjustment to binary search trees. We are motivated by the observation that the known kinds of efficient search trees have various drawbacks. Balanced trees, such as height-balanced trees [2, 221, weight-bala ...
... 1. Introduction In this paper we apply the related concepts of amortized complexity and se& adjustment to binary search trees. We are motivated by the observation that the known kinds of efficient search trees have various drawbacks. Balanced trees, such as height-balanced trees [2, 221, weight-bala ...
Balanced Search Trees
... – A 2-node (has two children) must contain single data item greater than left child’s item(s) and less than right child’s item(s) – A 3-node (has three children) must contain two data items, S and L , such that • S is greater than left child’s item(s) and less than middle child’s item(s); • L is gre ...
... – A 2-node (has two children) must contain single data item greater than left child’s item(s) and less than right child’s item(s) – A 3-node (has three children) must contain two data items, S and L , such that • S is greater than left child’s item(s) and less than middle child’s item(s); • L is gre ...
Dynamic point-region quadtrees for particle simulations
... The pseudo-code of the refine procedure called within the step method is given in Algorithm 3. The refine procedure continuously refines the nodes until the maximum refinement level is reached or no node containing more than one point is left. The refine procedure may trigger a coarsening process if the ...
... The pseudo-code of the refine procedure called within the step method is given in Algorithm 3. The refine procedure continuously refines the nodes until the maximum refinement level is reached or no node containing more than one point is left. The refine procedure may trigger a coarsening process if the ...
20 Introduction to Lists
... • A list is a linear collection that supports access, replacement, insertion, and removal at any position • Lists are more general-purpose than stacks and queues • No standard set of operations, but most lists support many typical ones ...
... • A list is a linear collection that supports access, replacement, insertion, and removal at any position • Lists are more general-purpose than stacks and queues • No standard set of operations, but most lists support many typical ones ...
Structures
... Passing structures to functions • Unlike an array, a structure variable name is not a pointer but represents the actual structure • If we pass a structure to a function as a parameter, the entire structure gets copied • (all parameters are passed by value) • Changes made to a structure by the calle ...
... Passing structures to functions • Unlike an array, a structure variable name is not a pointer but represents the actual structure • If we pass a structure to a function as a parameter, the entire structure gets copied • (all parameters are passed by value) • Changes made to a structure by the calle ...
Heaps Simplified Bernhard Haeupler , Siddhartha Sen , and Robert E. Tarjan
... be its actual time plus the change in potential it causes. Then for any sequence of operations the sum of the actual times is at most the sum of the amortized times. Since n numbers can be sorted by doing n insertions into an initially empty heap followed by n minimum deletions, the classical Ω(n lo ...
... be its actual time plus the change in potential it causes. Then for any sequence of operations the sum of the actual times is at most the sum of the amortized times. Since n numbers can be sorted by doing n insertions into an initially empty heap followed by n minimum deletions, the classical Ω(n lo ...
Data structures
... 38. Frequently, the memory space required by an algorithm is a multiple of the size of input. State if the statement is True or False or Maybe. A. True B. False C. Maybe D. None of the above 39. In which algorithm, the number of times comparison to be done is also affected by the location of the val ...
... 38. Frequently, the memory space required by an algorithm is a multiple of the size of input. State if the statement is True or False or Maybe. A. True B. False C. Maybe D. None of the above 39. In which algorithm, the number of times comparison to be done is also affected by the location of the val ...
powerpoint lecture
... Each node has at most two child nodes Node can have zero, one, or two child nodes Left child: child node to the left of the parent node Right child: child node to the right of the parent node Root: node that begins the tree Leaf node: node that has no child nodes Depth (level): distance from root no ...
... Each node has at most two child nodes Node can have zero, one, or two child nodes Left child: child node to the left of the parent node Right child: child node to the right of the parent node Root: node that begins the tree Leaf node: node that has no child nodes Depth (level): distance from root no ...
pq - Green Cedars
... •Heap: store elements in an array satisfying the heap condition. •Heap condition: the key in each node is >= keys in children (if any) •Definition: a heap is a complete binary tree, represented as an array, in which every node satisfies the heap condition. The largest key is the 1st position of the ...
... •Heap: store elements in an array satisfying the heap condition. •Heap condition: the key in each node is >= keys in children (if any) •Definition: a heap is a complete binary tree, represented as an array, in which every node satisfies the heap condition. The largest key is the 1st position of the ...
word - Courses
... This function will be used to compute the array index into which a pair with key k is to be stored. The header file for this project is identical to that found in lab5, and also to the header file for the Binary Search Tree based Dictionary posted on the website. There is however one ADT operation ...
... This function will be used to compute the array index into which a pair with key k is to be stored. The header file for this project is identical to that found in lab5, and also to the header file for the Binary Search Tree based Dictionary posted on the website. There is however one ADT operation ...
I/O-Efficient Data Structures for Colored Range and Prefix
... Notation. We always use n to denote the size of data in number of elements. For colored prefix reporting this means that we have m subsets of {1, . . . , σ} of total size n. As mentioned, we use b to denote the number of bits in a disk block. Since a block may store B pointers and input elements, we ...
... Notation. We always use n to denote the size of data in number of elements. For colored prefix reporting this means that we have m subsets of {1, . . . , σ} of total size n. As mentioned, we use b to denote the number of bits in a disk block. Since a block may store B pointers and input elements, we ...
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.