Glass Box Software Model Checking
... to describe heap manipulations such as those used by data structures. Partial order reduction is effective at reducing the number of nondeterministic schedules but it does little to cope with the large number of possible states of a data structure. We present glass box model checking, a type of soft ...
... to describe heap manipulations such as those used by data structures. Partial order reduction is effective at reducing the number of nondeterministic schedules but it does little to cope with the large number of possible states of a data structure. We present glass box model checking, a type of soft ...
Big Idea - Department of Computer Science
... (Oct Tree analogous) Procedure Quad_Tree_Build Quad_Tree = {emtpy} for j = 1 to N … loop over all N particles Quad_Tree_Insert(j, root) … insert particle j in QuadTree endfor … At this point, each leaf of Quad_Tree will have 0 or 1 particles … There will be 0 particles when some sibling has 1 Traver ...
... (Oct Tree analogous) Procedure Quad_Tree_Build Quad_Tree = {emtpy} for j = 1 to N … loop over all N particles Quad_Tree_Insert(j, root) … insert particle j in QuadTree endfor … At this point, each leaf of Quad_Tree will have 0 or 1 particles … There will be 0 particles when some sibling has 1 Traver ...
Fundamental Data Structures
... Tradeoffs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...
... Tradeoffs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...
Wavelet Trees Meet Suffix Trees
... the bitmasks Bv , we do not remove the most significant bit of each character, and instead of partitioning the values based on this bit, we make a decision based on whether the leaf corresponding to the character lies in the left or in the right subtree of v. Our construction algorithm generalizes t ...
... the bitmasks Bv , we do not remove the most significant bit of each character, and instead of partitioning the values based on this bit, we make a decision based on whether the leaf corresponding to the character lies in the left or in the right subtree of v. Our construction algorithm generalizes t ...
Dynamic 3-sided planar range queries with expected - delab-auth
... hB-trees and various R-trees have been proposed. A recent survey can be found in [16]. Often these data structures are used in applications, because they are relatively simple, require linear space and perform well in practice most of the time. However, they all have highly sub-optimal worst case pe ...
... hB-trees and various R-trees have been proposed. A recent survey can be found in [16]. Often these data structures are used in applications, because they are relatively simple, require linear space and perform well in practice most of the time. However, they all have highly sub-optimal worst case pe ...
On Constant Factors in Comparison
... of course is important in practice, and the number of comparisons is a measure that can be formally studied from the theoretical perspective. We do not claim practicality of most of our algorithms, however, because of potentially larger constants in not only the lower-order terms but also the cost o ...
... of course is important in practice, and the number of comparisons is a measure that can be formally studied from the theoretical perspective. We do not claim practicality of most of our algorithms, however, because of potentially larger constants in not only the lower-order terms but also the cost o ...
Data Structures — Lists and Trees
... • Every computational problem can be solved with loops, arrays, non-recursive functions, and an unlimited amount of memory. • I.e., in Fortran! ...
... • Every computational problem can be solved with loops, arrays, non-recursive functions, and an unlimited amount of memory. • I.e., in Fortran! ...
Reducing the Storage Overhead of Main
... As shown in Figure 1, the dual-stage hybrid index architecture is comprised of two stages: the dynamic stage and the static stage. New entries are added to the dynamic stage. This stage is kept small so that queries to the most recent entries, which are likely to be accessed and modified in the near ...
... As shown in Figure 1, the dual-stage hybrid index architecture is comprised of two stages: the dynamic stage and the static stage. New entries are added to the dynamic stage. This stage is kept small so that queries to the most recent entries, which are likely to be accessed and modified in the near ...
pptx - UTA.edu
... • Each node points both to the previous and to the next nodes. • In our list implementation, in addition to keeping track of the first node, we could also keep track of the last node. • Advantages: – To delete a link, we just need that link. – It is as easy to go backwards as it is to go forward. ...
... • Each node points both to the previous and to the next nodes. • In our list implementation, in addition to keeping track of the first node, we could also keep track of the last node. • Advantages: – To delete a link, we just need that link. – It is as easy to go backwards as it is to go forward. ...
Class Notes for CSCI 104: Data Structures and Object
... These lecture notes grew out of class notes provided for the students in CSCI 104 (“Data Structures and Object-Oriented Design”) at the University of Southern California in Fall of 2013. The class is typically taken in the second semester of freshman year or the first semester of sophomore year. Stu ...
... These lecture notes grew out of class notes provided for the students in CSCI 104 (“Data Structures and Object-Oriented Design”) at the University of Southern California in Fall of 2013. The class is typically taken in the second semester of freshman year or the first semester of sophomore year. Stu ...
Accelerating Online LCA with Functional Data Structures
... We store a linked list of complete trees, where we are allowed to have two trees of the same size at the front of the list, but after that all trees are of strictly increasing height. data Tree a = Tip a | Bin a (Tree a) (Tree a) data Path a = Nil | Cons !Int !Int (Tree a) (Path a) length :: Path a ...
... We store a linked list of complete trees, where we are allowed to have two trees of the same size at the front of the list, but after that all trees are of strictly increasing height. data Tree a = Tip a | Bin a (Tree a) (Tree a) data Path a = Nil | Cons !Int !Int (Tree a) (Path a) length :: Path a ...
... Preparata start out with a balanced tree whose nodes are associated with various lists. Then they make the key remark that many elements in these lists can be removed because whenever they are needed by the algorithm they will always have been encountered in other lists before. This simple transform ...
Persistent Data Structures
... empty. If so, we store the updated value in the mod box with the appropriate timestamp. If the box is full, we copy the node and immediately store the new value in this node (keeping the mod box empty). We then recurse all the necessary modifications to the parent. To access a node, we first do a bi ...
... empty. If so, we store the updated value in the mod box with the appropriate timestamp. If the box is full, we copy the node and immediately store the new value in this node (keeping the mod box empty). We then recurse all the necessary modifications to the parent. To access a node, we first do a bi ...
Searching in Metric Spaces - Página del DCC UChile
... information have emerged. Not only new data types such as free text, images, audio and video have to be queried, but also it is not possible anymore to structure the information in keys and records. Such structuring is very dicult (either manually or computationally) and restricts beforehand the ty ...
... information have emerged. Not only new data types such as free text, images, audio and video have to be queried, but also it is not possible anymore to structure the information in keys and records. Such structuring is very dicult (either manually or computationally) and restricts beforehand the ty ...
Programming Embedded Computing Systems using Static Embedded SQL
... (1) A subset of SQL is defined, called µSQL, with the property that operations in this subset can always be supported in time logarithmic in the size of the underlying database. Consequently, programmers have immediate guarantees on worst case response times for control data access and update. (2) A ...
... (1) A subset of SQL is defined, called µSQL, with the property that operations in this subset can always be supported in time logarithmic in the size of the underlying database. Consequently, programmers have immediate guarantees on worst case response times for control data access and update. (2) A ...
A Skip List Cookbook - Computational Geometry Lab
... searched for and travelling up and to the left. The length of this path is one less than the number of comparisons we need to perform. We first examine the number of pointers we have to backtrack to climb from level 1 (of the element immediately before the element searched for) up to level L(n). We ...
... searched for and travelling up and to the left. The length of this path is one less than the number of comparisons we need to perform. We first examine the number of pointers we have to backtrack to climb from level 1 (of the element immediately before the element searched for) up to level L(n). We ...
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.