Dictionary Data Structures
... Van Emde Boas Priority Queues A Van Emde Boas Priority Queue is efficient when n > lg N for a universe U = {0, . . . , N − 1} of keys. In this implementation, all priority queue operations reduce to successor computation, which takes O(lg lg N) time. The space requirements are O(N lg lg N). We start ...
... Van Emde Boas Priority Queues A Van Emde Boas Priority Queue is efficient when n > lg N for a universe U = {0, . . . , N − 1} of keys. In this implementation, all priority queue operations reduce to successor computation, which takes O(lg lg N) time. The space requirements are O(N lg lg N). We start ...
Skip Ring/Circular Skip List: Circular Linked List Based
... linked list is linked in a way that it points back to the first element (head) (Figure 4), and this process is performed for entire levels. When Rings in skip ring data structure are created (Ring 0, Ring 1,.., Ring Ɩ), levels are created randomly. Let us say that the number of ordered nodes in our ...
... linked list is linked in a way that it points back to the first element (head) (Figure 4), and this process is performed for entire levels. When Rings in skip ring data structure are created (Ring 0, Ring 1,.., Ring Ɩ), levels are created randomly. Let us say that the number of ordered nodes in our ...
An arrangement of lines: A(H)
... A cut is a sequence of edges (c1, c2, ...,cn), one from each line of A(H), such that for each i (1.. n-1) there is a (unique) face fi such that ci is above fi , and c(i+1) is below fi c1 is below the top-most face and cn is above the bottom-most face ...
... A cut is a sequence of edges (c1, c2, ...,cn), one from each line of A(H), such that for each i (1.. n-1) there is a (unique) face fi such that ci is above fi , and c(i+1) is below fi c1 is below the top-most face and cn is above the bottom-most face ...
Lower Bounds for Orthogonal Range Searching:
... an integer, label(u), between 0 and n. If i = label(u) is not 0, the node u is associated with point pi. Note that many nodes can be labeled the same way. Given a query q, the answering algorithm begins a traversal of G at the source u. We place only two restrictions on the algorithm. To begin with, ...
... an integer, label(u), between 0 and n. If i = label(u) is not 0, the node u is associated with point pi. Note that many nodes can be labeled the same way. Given a query q, the answering algorithm begins a traversal of G at the source u. We place only two restrictions on the algorithm. To begin with, ...
QSplat: A Multiresolution Point Rendering System for Large Meshes Szymon Rusinkiewicz
... to its parent, a normal, the width of a cone of normals, an optional color, and a few bits used in representing the structure of the tree. We discuss the structure of the tree and the layout of nodes within the file in Section 3.2. Position and radius: The position and radius of each sphere is encod ...
... to its parent, a normal, the width of a cone of normals, an optional color, and a few bits used in representing the structure of the tree. We discuss the structure of the tree and the layout of nodes within the file in Section 3.2. Position and radius: The position and radius of each sphere is encod ...
Suffix Trees and their Applications in String Algorithms
... represented by the leaves numbered 2 and 4. Otherwise, if the pattern y does not occur in the text x there is no pathstring spelled by y in T : in Fig. 1, the pattern y = abaa does not occur in the text x, since the last a does not match the pathstring spelled by aba. Therefore, in both cases, compu ...
... represented by the leaves numbered 2 and 4. Otherwise, if the pattern y does not occur in the text x there is no pathstring spelled by y in T : in Fig. 1, the pattern y = abaa does not occur in the text x, since the last a does not match the pathstring spelled by aba. Therefore, in both cases, compu ...
Spatial Data Structures
... root node. Root node has two entries unless it is a leaf node. • R-tree is not unique, rectangles depend on how objects are inserted and deleted from the tree. • Problem is that to find some object you might have to go through several rectangles or whole database. Snehal Thakkar ...
... root node. Root node has two entries unless it is a leaf node. • R-tree is not unique, rectangles depend on how objects are inserted and deleted from the tree. • Problem is that to find some object you might have to go through several rectangles or whole database. Snehal Thakkar ...
ppt
... – Nodes high in the tree do not split very often – Used when secondary structures are used More later! • Level-balanced B-trees – Global instead of local balancing strategy – Whole subtrees rebuilt when too many nodes on a level – Used when parent pointers and divide/merge operations needed • String ...
... – Nodes high in the tree do not split very often – Used when secondary structures are used More later! • Level-balanced B-trees – Global instead of local balancing strategy – Whole subtrees rebuilt when too many nodes on a level – Used when parent pointers and divide/merge operations needed • String ...
24slide - KSU Web Home
... Array is a fixed-size data structure. Once an array is created, its size cannot be changed. Nevertheless, you can still use array to implement dynamic data structures. The trick is to create a new larger array to replace the current array if the current array cannot hold new elements in the list. In ...
... Array is a fixed-size data structure. Once an array is created, its size cannot be changed. Nevertheless, you can still use array to implement dynamic data structures. The trick is to create a new larger array to replace the current array if the current array cannot hold new elements in the list. In ...
Open Data Structures (in Java)
... There are plenty of books that teach introductory data structures. Some of them are very good. Most of them cost money, and the vast majority of computer science undergraduate students will shell out at least some cash on a data structures book. Several free data structures books are available onlin ...
... There are plenty of books that teach introductory data structures. Some of them are very good. Most of them cost money, and the vast majority of computer science undergraduate students will shell out at least some cash on a data structures book. Several free data structures books are available onlin ...
A D S COS
... 15 minutes during which he’d sketched out a fundamental optimization algorithm. He regarded the previous years of thought and investigation as a sunk cost that might or might not have paid off. Researchers have cracked many hard problems since 1 January 1900, but we are passing some even harder ones ...
... 15 minutes during which he’d sketched out a fundamental optimization algorithm. He regarded the previous years of thought and investigation as a sunk cost that might or might not have paid off. Researchers have cracked many hard problems since 1 January 1900, but we are passing some even harder ones ...
IndexedFiles
... • Bucket Factor: the number of records which can fit in a leaf node. • Fan-out : the average number of children of an internal node. • A B+tree index can be used either as a primary index or a secondary index. – Primary index: determines the way the records are actually stored (also called a sparse ...
... • Bucket Factor: the number of records which can fit in a leaf node. • Fan-out : the average number of children of an internal node. • A B+tree index can be used either as a primary index or a secondary index. – Primary index: determines the way the records are actually stored (also called a sparse ...
◦ § 5.19 9.11
... None of the implementations that we have considered admit implementations of join, remove the maximum, and insert that are all efficient in the worst case. Unordered linked lists have fast join and insert, but slow remove the maximum; ordered linked lists have fast remove the maximum, but slow join ...
... None of the implementations that we have considered admit implementations of join, remove the maximum, and insert that are all efficient in the worst case. Unordered linked lists have fast join and insert, but slow remove the maximum; ordered linked lists have fast remove the maximum, but slow join ...
View
... We will find that with certain more complicated data types or structures we need and are able to carry out other operations and that in fact to define the type fully we will need to specify what operations can be carried out. The resulting definitions create what are called ...
... We will find that with certain more complicated data types or structures we need and are able to carry out other operations and that in fact to define the type fully we will need to specify what operations can be carried out. The resulting definitions create what are called ...
6: linked lists
... changing various link pointers and then physically deleting the node from dynamic memory. Delete can be done at the first node, at the last node or at a specified position of the list. ...
... changing various link pointers and then physically deleting the node from dynamic memory. Delete can be done at the first node, at the last node or at a specified position of the list. ...
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.