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Model Viva Questions for “Name of the Lab: Data structure lab”
... link, pointer, to connect them. Since we can't use ordinary pointers for this, we use the void pointer. Void pointer is a generic pointer type, and capable of storing pointer to any type. Q3: What issue do auto_ptr objects address? A3: If you use auto_ptr objects you would not have to be concerned w ...
... link, pointer, to connect them. Since we can't use ordinary pointers for this, we use the void pointer. Void pointer is a generic pointer type, and capable of storing pointer to any type. Q3: What issue do auto_ptr objects address? A3: If you use auto_ptr objects you would not have to be concerned w ...
Sandhya Dasu
... • A bitmap is used to indicate if a counter is above or below the threshold • The following operations are required to be implemented on the bitmap to support LR(T) • Add(i) – To update bit for a counter to indicate its value is above threshold • Delete(i) – After updating a counter’s value it, this ...
... • A bitmap is used to indicate if a counter is above or below the threshold • The following operations are required to be implemented on the bitmap to support LR(T) • Add(i) – To update bit for a counter to indicate its value is above threshold • Delete(i) – After updating a counter’s value it, this ...
Tables As Trees: Merging with Wildcards Using Tree Traversal and Pruning
... leaves. The number of levels in a tree is equal to the longest path in the tree from the root to any leaf (the root is typically considered to occupy level 0; the root’s children occupy level 1, and so on). Finally, a tree is a recursive data structure: every child node forms a sub-tree in which it ...
... leaves. The number of levels in a tree is equal to the longest path in the tree from the root to any leaf (the root is typically considered to occupy level 0; the root’s children occupy level 1, and so on). Finally, a tree is a recursive data structure: every child node forms a sub-tree in which it ...
Fast Compressed Tries through Path Decompositions
... We define a binary tree as a tree where each node is either an internal node that has exactly two children or a leaf . It follows immediately that a binary tree with n internal nodes has n + 1 leaves. An example of binary trees is given by binary compacted tries. Note that there is another popular d ...
... We define a binary tree as a tree where each node is either an internal node that has exactly two children or a leaf . It follows immediately that a binary tree with n internal nodes has n + 1 leaves. An example of binary trees is given by binary compacted tries. Note that there is another popular d ...
Dynamic Optimality---Almost
... by the pointer. The access algorithm’s choice of the next operation to perform is a function of the data and augmented data stored in the node currently pointed to. In particular, the algorithm’s behavior depends only on the past. The amount of augmented information at each node should be as small a ...
... by the pointer. The access algorithm’s choice of the next operation to perform is a function of the data and augmented data stored in the node currently pointed to. In particular, the algorithm’s behavior depends only on the past. The amount of augmented information at each node should be as small a ...
Engineering the LOUDS Succinct Tree Representation*
... bound, which come from augmenting a bit-string of 2n + O(1) bits representing the tree with a number of directories, or auxiliary data structures, that are used to support operations in O(1) time. The space used by each directory is, of course, asymptotically o(n) bits, but is usually a function lik ...
... bound, which come from augmenting a bit-string of 2n + O(1) bits representing the tree with a number of directories, or auxiliary data structures, that are used to support operations in O(1) time. The space used by each directory is, of course, asymptotically o(n) bits, but is usually a function lik ...
Scalable Classification Algorithms
... Have to calculate the value of the impurity function at every x not in the confidence interval Need to check if i’ is the global minimum without constructing all of the impurity functions in memory ...
... Have to calculate the value of the impurity function at every x not in the confidence interval Need to check if i’ is the global minimum without constructing all of the impurity functions in memory ...
Red-black tree
... (and is sometimes called a 'phantom' leaf). And we can safely delete it at the end as n will remain a leaf after all operations, as shown above. If both N and its original parent are black, then deleting this original parent causes paths which proceed through N to have one fewer black node than path ...
... (and is sometimes called a 'phantom' leaf). And we can safely delete it at the end as n will remain a leaf after all operations, as shown above. If both N and its original parent are black, then deleting this original parent causes paths which proceed through N to have one fewer black node than path ...
Richard Tarjent
... The most interesting thing about this problem, in my opinion, is the surprising result involving (n) . I was able to obtain this result because I imagined that it wasn’t linear, (and I was right), so what could it be? Since this result, the inverse of Ackerman’s function has turned up in a number ...
... The most interesting thing about this problem, in my opinion, is the surprising result involving (n) . I was able to obtain this result because I imagined that it wasn’t linear, (and I was right), so what could it be? Since this result, the inverse of Ackerman’s function has turned up in a number ...
CSE 326: Data Structures Lecture #20 Multidimensional Search Trees
... k-D Trees Can Be Inefficient (but not when built in batch!) insert(<5,0>) insert(<6,9>) insert(<9,3>) insert(<6,5>) insert(<7,7>) insert(<8,6>) ...
... k-D Trees Can Be Inefficient (but not when built in batch!) insert(<5,0>) insert(<6,9>) insert(<9,3>) insert(<6,5>) insert(<7,7>) insert(<8,6>) ...
Slide 1
... An ordered collection of data in which each element contains the location of the next element. Each element contains two part ...
... An ordered collection of data in which each element contains the location of the next element. Each element contains two part ...
CS2006Ch04A
... Fast, easy to perform search but Difficult to insert and delete items Must specify size at construction time ...
... Fast, easy to perform search but Difficult to insert and delete items Must specify size at construction time ...
Bulk-Loading the ND-Tree in Non-ordered Discrete Data Spaces, Best Paper Award, 13th International Conference, DASFAA 2008 (pp. 156-172), New Delhi, India, Hyun-Jeon Seik, Gang Qian, Qiang Zhu, Alexander R. Oswald and Sakti Pramanik.
... of them are sorting-based bulk-loading [5,9,10,14,15,20]. Some of these adopt the bottom-up approach, while the others employ the top-down approach. The former algorithms [9,14,20] typically sort all input vectors according to a chosen one-dimensional criterion first, place them into the leaves of th ...
... of them are sorting-based bulk-loading [5,9,10,14,15,20]. Some of these adopt the bottom-up approach, while the others employ the top-down approach. The former algorithms [9,14,20] typically sort all input vectors according to a chosen one-dimensional criterion first, place them into the leaves of th ...
Analysis of Algorithms CS 465/665
... set of nodes that either: – Contains no nodes, or – Is composed of three disjoint sets of nodes: a root node, a left subtree and a right subtree ...
... set of nodes that either: – Contains no nodes, or – Is composed of three disjoint sets of nodes: a root node, a left subtree and a right subtree ...
A Forest of Hashed Binary Search Trees with Reduced Internal Path
... Height of the worst tree in the forest = A tree with the maximum height in the forest. Collective path-length of the forest = The sum of the pathlengths of all 11 trees in the forest Table 1 is obtained as a result of several tests conducted with Borland C++ compiler 5.5 under windows, and GNU C++ c ...
... Height of the worst tree in the forest = A tree with the maximum height in the forest. Collective path-length of the forest = The sum of the pathlengths of all 11 trees in the forest Table 1 is obtained as a result of several tests conducted with Borland C++ compiler 5.5 under windows, and GNU C++ c ...
Octal Numbering System
... To convert decimal to octal is slightly more difficult. The typical method to convert from decimal to octal is repeated division by 8. While we may also use repeated subtraction by the weighted position value, it is more difficult for large decimal numbers. Repeated Division By 8 For this method, di ...
... To convert decimal to octal is slightly more difficult. The typical method to convert from decimal to octal is repeated division by 8. While we may also use repeated subtraction by the weighted position value, it is more difficult for large decimal numbers. Repeated Division By 8 For this method, di ...
Lecture L16 — April 19, 2012 1 Overview 2 Predecessor Problem
... are at node y in the weight balanced BST representing node x in the trie. Consider all trie children c1 , c2 , ..., cm of node x present in y’s subtree. Let D be the total number of descendant leaves of c1 , c2 , ..., cm . If the number of descendant leaves of any child ci is at most D/3 then follow ...
... are at node y in the weight balanced BST representing node x in the trie. Consider all trie children c1 , c2 , ..., cm of node x present in y’s subtree. Let D be the total number of descendant leaves of c1 , c2 , ..., cm . If the number of descendant leaves of any child ci is at most D/3 then follow ...
SPST-Index : A Self Pruning Splay Tree Index for
... database columns into pieces, called cracked pieces, and generating an index to keep track of those pieces. For example, assuming the following predicate A < 10. The idea of database cracking is clustering all tuples within A < 10 in the beginning of the column and pushing the remaining tuples to th ...
... database columns into pieces, called cracked pieces, and generating an index to keep track of those pieces. For example, assuming the following predicate A < 10. The idea of database cracking is clustering all tuples within A < 10 in the beginning of the column and pushing the remaining tuples to th ...
A Space Efficient Persistent Implementation of an Index for DNA Sequences
... text. The most detailed logical data structure is the suffix tree. The most sporadic the suffix array. For all these structures, the primary text must be accessed by each search operation. For texts stored on secondary memory, this is very time expensive. In all cases, DNA strings with a size of abo ...
... text. The most detailed logical data structure is the suffix tree. The most sporadic the suffix array. For all these structures, the primary text must be accessed by each search operation. For texts stored on secondary memory, this is very time expensive. In all cases, DNA strings with a size of abo ...
Authentic Time-Stamps for Archival Storage
... When a new string is inserted in the trie, its position is uniquely determined by its value. The trie is traversed starting from the root and following the left path if the first bit of the string is 0, and the right path, otherwise. The process is repeated until all bits of the string are exhausted ...
... When a new string is inserted in the trie, its position is uniquely determined by its value. The trie is traversed starting from the root and following the left path if the first bit of the string is 0, and the right path, otherwise. The process is repeated until all bits of the string are exhausted ...
ADS@Unit-2[Balanced Trees] Unit II : Balanced Trees : AVL Trees
... Tree: Tree is non-linear data structure that consists of root node and potentially many levels of additional nodes that form a hierarchy. A tree can be empty with no nodes called the null or empty tree. A tree is a structure consisting of one node call the root and one or more subtrees. Descen ...
... Tree: Tree is non-linear data structure that consists of root node and potentially many levels of additional nodes that form a hierarchy. A tree can be empty with no nodes called the null or empty tree. A tree is a structure consisting of one node call the root and one or more subtrees. Descen ...
Sidebar: Data Structures Binary Search Tree
... API is in place, you should initially choose the data structure with the simplest implementation, to minimize development time. If you need to optimize your system later, you will be able to switch in a more efficient data structure easily, because you thought of that possibility in advance, when de ...
... API is in place, you should initially choose the data structure with the simplest implementation, to minimize development time. If you need to optimize your system later, you will be able to switch in a more efficient data structure easily, because you thought of that possibility in advance, when de ...
Linked List
... Deletion is also expensive with arrays until unless some special techniques are used. For example, to delete 1010 in id[], everything after 1010 has to be moved. Advantages over arrays 1) Dynamic size 2) Ease of insertion/deletion Drawbacks: 1) Random access is not allowed. We have to access element ...
... Deletion is also expensive with arrays until unless some special techniques are used. For example, to delete 1010 in id[], everything after 1010 has to be moved. Advantages over arrays 1) Dynamic size 2) Ease of insertion/deletion Drawbacks: 1) Random access is not allowed. We have to access element ...
Binary tree
In computer science, a binary tree is a tree data structure in which each node has at most two children, which are referred to as the left child and the right child. A recursive definition using just set theory notions is that a (non-empty) binary tree is a triple (L, S, R), where L and R are binary trees or the empty set and S is a singleton set. Some authors allow the binary tree to be the empty set as well.From a graph theory perspective, binary (and K-ary) trees as defined here are actually arborescences. A binary tree may thus be also called a bifurcating arborescence—a term which actually appears in some very old programming books, before the modern computer science terminology prevailed. It is also possible to interpret a binary tree as an undirected, rather than a directed graph, in which case a binary tree is an ordered, rooted tree. Some authors use rooted binary tree instead of binary tree to emphasize the fact that the tree is rooted, but as defined above, a binary tree is always rooted. A binary tree is a special case of an ordered K-ary tree, where k is 2.In computing, binary trees are seldom used solely for their structure. Much more typical is to define a labeling function on the nodes, which associates some value to each node. Binary trees labelled this way are used to implement binary search trees and binary heaps, and are used for efficient searching and sorting. The designation of non-root nodes as left or right child even when there is only one child present matters in some of these applications, in particular it is significant in binary search trees. In mathematics, what is termed binary tree can vary significantly from author to author. Some use the definition commonly used in computer science, but others define it as every non-leaf having exactly two children and don't necessarily order (as left/right) the children either.