Abstract Efficient Data Structures for Tamper-Evident Logging
... is known to be internally consistent. However, proving internal consistency requires scanning the full contents of the log. (See Section 3.4 for further analysis of this.) In the same manner, CATS [63], a network-storage service with strong accountability properties, snapshots the internal state, a ...
... is known to be internally consistent. However, proving internal consistency requires scanning the full contents of the log. (See Section 3.4 for further analysis of this.) In the same manner, CATS [63], a network-storage service with strong accountability properties, snapshots the internal state, a ...
Dynamic FM-Index for a Collection of Texts with
... words and store for each word the information where it occurs in the text. Those indices enable fast queries and are space-efficient. A disadvantage is that they are not applicable to biological sequences like DNA, proteins, or audio and video signals. Sequence-based indices allow to search efficien ...
... words and store for each word the information where it occurs in the text. Those indices enable fast queries and are space-efficient. A disadvantage is that they are not applicable to biological sequences like DNA, proteins, or audio and video signals. Sequence-based indices allow to search efficien ...
Burst Tries - Department of Computer Science
... The current capital is modified on each access. On a direct hit, the capital is incremented by a bonus B. If a record is accessed that is already in the container, but is not a direct hit, the capital is decremented by a penalty M. When the capital is exhausted, the container is burst. Thus if the a ...
... The current capital is modified on each access. On a direct hit, the capital is incremented by a bonus B. If a record is accessed that is already in the container, but is not a direct hit, the capital is decremented by a penalty M. When the capital is exhausted, the container is burst. Thus if the a ...
ppt - Texas A&M University
... • Main stack operations: • Push(e): inserts element e at the top of the stack • pop(): removes and returns the top element of the stack (last inserted element) • top(): returns reference to the top element without removing ...
... • Main stack operations: • Push(e): inserts element e at the top of the stack • pop(): removes and returns the top element of the stack (last inserted element) • top(): returns reference to the top element without removing ...
Oblivious Data Structures - Indiana University Computer Science
... patterns. The access pattern graph for an algorithm has memory cells as nodes, and two cells can be accessed in succession only if there is a directed edge between the corresponding nodes. Hence, for general RAM programs, their access pattern can be a complete graph. Our key insight is that common d ...
... patterns. The access pattern graph for an algorithm has memory cells as nodes, and two cells can be accessed in succession only if there is a directed edge between the corresponding nodes. Hence, for general RAM programs, their access pattern can be a complete graph. Our key insight is that common d ...
File manipulation
... Ensures that process has sufficient privileges to access the files. Allocates one or more buffers. Updates an internal table of open files. ...
... Ensures that process has sufficient privileges to access the files. Allocates one or more buffers. Updates an internal table of open files. ...
Lists, Stacks, and Queues
... pushing the entire array down one spot to make room e.g. delete at position 0 requires shifting all the elements in the list up one On average, half of the lists needs to be moved for either operation ...
... pushing the entire array down one spot to make room e.g. delete at position 0 requires shifting all the elements in the list up one On average, half of the lists needs to be moved for either operation ...
CS 130 A: Data Structures and Algorithms
... O(1) time possible but space-inefficient. Linked list space-efficient, but search-inefficient. Insert is O(1) but find and delete are O(n). A sorted array does not help, even with ordered keys. The search becomes fast, but insert/delete take O(n). Balanced search trees (Chap. 4) work but take O(lo ...
... O(1) time possible but space-inefficient. Linked list space-efficient, but search-inefficient. Insert is O(1) but find and delete are O(n). A sorted array does not help, even with ordered keys. The search becomes fast, but insert/delete take O(n). Balanced search trees (Chap. 4) work but take O(lo ...
Sequential Search Search Algorithms
... – Phone number and ID numbers can be converted by removing the hyphens. – Characters can be converted using ASCII. – Strings can be converted by converting each character using ASCII, and then interpreting the string of natural numbers as if it where stored base 128. ...
... – Phone number and ID numbers can be converted by removing the hyphens. – Characters can be converted using ASCII. – Strings can be converted by converting each character using ASCII, and then interpreting the string of natural numbers as if it where stored base 128. ...
Finger Search Trees - Department of Computer Science
... The most prominet properties of treaps are that they have expected O(log n) height, implying that they provide searches in expected O(log n) time. Insertions and deletions of elements can be performed in expected at most two rotations and expected O(1) time, provided that the position of insertion o ...
... The most prominet properties of treaps are that they have expected O(log n) height, implying that they provide searches in expected O(log n) time. Insertions and deletions of elements can be performed in expected at most two rotations and expected O(1) time, provided that the position of insertion o ...
• Data Structures and Data Types
... • A item plus a pointer to another linked list (or empty list). • Unwind recursion: linked list is a sequence of items. ...
... • A item plus a pointer to another linked list (or empty list). • Unwind recursion: linked list is a sequence of items. ...
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.