11. Implementations and Experimental Studies of Dynamic Graph
... (but not both). In the case of edge insertions (resp. deletions), the partially dynamic algorithm or problem is called incremental (resp. decremental). The main goal of a dynamic algorithm is to use structural properties of the current graph G in order to handle updates efficiently, i.e., without reso ...
... (but not both). In the case of edge insertions (resp. deletions), the partially dynamic algorithm or problem is called incremental (resp. decremental). The main goal of a dynamic algorithm is to use structural properties of the current graph G in order to handle updates efficiently, i.e., without reso ...
Data Structures
... network and the maximization of disk space. Therefore people have started solving more and more complex problems. As computer applications are becoming complex, so there is need for more resources. This does not mean that we should buy a new computer to make the application execute faster. Our effor ...
... network and the maximization of disk space. Therefore people have started solving more and more complex problems. As computer applications are becoming complex, so there is need for more resources. This does not mean that we should buy a new computer to make the application execute faster. Our effor ...
Data Structure and Algorithm
... Printed in the United States of America First Printing: May 1999 ...
... Printed in the United States of America First Printing: May 1999 ...
Indexing Structures for Searching in Metric Spaces
... the work and additional references. In some applications, the metric space turns out to be of a particular type called vector space, where the elements consist of k coordinates (often termed feature vectors). For example, images are often represented by color and shape histograms [38, 48], typically ...
... the work and additional references. In some applications, the metric space turns out to be of a particular type called vector space, where the elements consist of k coordinates (often termed feature vectors). For example, images are often represented by color and shape histograms [38, 48], typically ...
6. Lists
... 2.Insert(L:TypeList,x:TypeElement,p:TypePosition); - inserts x at position p in list L, moving elements at p and following positions to the next higher position. That is, if L is a1,a2,...,an then L becomes a1,a2,...,ap-1,x,ap,...an. If p is End(L), then L becomes a1,a2,...an,x. If list L has no pos ...
... 2.Insert(L:TypeList,x:TypeElement,p:TypePosition); - inserts x at position p in list L, moving elements at p and following positions to the next higher position. That is, if L is a1,a2,...,an then L becomes a1,a2,...,ap-1,x,ap,...an. If p is End(L), then L becomes a1,a2,...an,x. If list L has no pos ...
OpenVMS Distributed Lock Manager Performance
... rules: LOCKDIRWT must be equal for lock activity levels to control choice of lock master node PE1 can be used to control movement of lock trees OFF of a node, but not ONTO a node RSB stores lock activity counts, so even high activity counts can be lost if the last lock is DEQueued on a given nod ...
... rules: LOCKDIRWT must be equal for lock activity levels to control choice of lock master node PE1 can be used to control movement of lock trees OFF of a node, but not ONTO a node RSB stores lock activity counts, so even high activity counts can be lost if the last lock is DEQueued on a given nod ...
estructuras de datos sucintas para recuperación de
... is called an index. The most naive index will pre-store the answer to every possible query. This, of course, would be very fast at answering the queries (just the time required to look at the table of answers) but, in most cases, extremely space-inefficient. On the other hand, using no index at all ...
... is called an index. The most naive index will pre-store the answer to every possible query. This, of course, would be very fast at answering the queries (just the time required to look at the table of answers) but, in most cases, extremely space-inefficient. On the other hand, using no index at all ...
Glass Box Software Model Checking
... state control circuits with up to a few hundred bits of state information; but not circuits in general that have large data paths or memories. Similarly, for software, model checkers have primarily verified event sequences with respect to temporal properties; but not much work has been done to verif ...
... state control circuits with up to a few hundred bits of state information; but not circuits in general that have large data paths or memories. Similarly, for software, model checkers have primarily verified event sequences with respect to temporal properties; but not much work has been done to verif ...
Class Notes for CSCI 104: Data Structures and Object-Oriented Design
... In principle, these features are enough to solve any programming problem. In fact, in principle, it is enough to have nothing except while loops, if tests, integers, and arithmetic. Everything that we learn beyond those basics is “just” there to help us write better, faster, or more easily maintaine ...
... In principle, these features are enough to solve any programming problem. In fact, in principle, it is enough to have nothing except while loops, if tests, integers, and arithmetic. Everything that we learn beyond those basics is “just” there to help us write better, faster, or more easily maintaine ...
Kernel Data Structures
... search of Linux’s page cache for a chunk of a file Each inode has its own rbtree, keyed off of page offsets into file This function thus searches the given inode’s rbtree for a matching offset ...
... search of Linux’s page cache for a chunk of a file Each inode has its own rbtree, keyed off of page offsets into file This function thus searches the given inode’s rbtree for a matching offset ...
Towards Optimal Range Medians - Department of Computer Science
... Our algorithm is based on the following key observation (see also Figure 1): Suppose we partition the elements in array A of length n into two smaller arrays: A.low which contains all elements with the n/2 smallest6 values in A, and A.high which contains all elements with the n/2 largest values. Th ...
... Our algorithm is based on the following key observation (see also Figure 1): Suppose we partition the elements in array A of length n into two smaller arrays: A.low which contains all elements with the n/2 smallest6 values in A, and A.high which contains all elements with the n/2 largest values. Th ...
Quadtree
A quadtree is a tree data structure in which each internal node has exactly four children. Quadtrees are most often used to partition a two-dimensional space by recursively subdividing it into four quadrants or regions. The regions may be square or rectangular, or may have arbitrary shapes. This data structure was named a quadtree by Raphael Finkel and J.L. Bentley in 1974. A similar partitioning is also known as a Q-tree. All forms of quadtrees share some common features: They decompose space into adaptable cells Each cell (or bucket) has a maximum capacity. When maximum capacity is reached, the bucket splits The tree directory follows the spatial decomposition of the quadtree.