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CS II: Data Structures Discussion worksheet: Week 9
CS II: Data Structures Discussion worksheet: Week 9

VIST: The Virtual Suffix Tree
VIST: The Virtual Suffix Tree

B+ Tree Comparisons
B+ Tree Comparisons

... single node, which is the maximum number of children it can have. In a regular Binary tree b=2. In a B+ tree b can be any number, but for convenience it is preferred to use multiples of 2. B+ Tree is an external tree, which means that traversal (or internal) nodes contain only keys and pointer/refer ...
Final exam. Spring`03 (Yen)
Final exam. Spring`03 (Yen)

... 3. (10 pts) It is known that Dijkstra’s algorithm does not work for graphs with negative edges. Consider the following modification to Dijkstra’s algorithm for `solving’ the shortest path problem for graphs with negative edges but without negative cycles. If some of the edge weights in a graph are ...
The ND-Tree - Department of Computer Science
The ND-Tree - Department of Computer Science

- Free Documents
- Free Documents

Review: Pastry routing tables - Stanford Secure Computer Systems
Review: Pastry routing tables - Stanford Secure Computer Systems

Programming for GCSE - Teaching London Computing
Programming for GCSE - Teaching London Computing

... • Where do lists and dictionaries come from? • Understand the problem • Introduce the following data structures ...
Resource-Optimized Quality-Assured Ambiguous Context Mediation
Resource-Optimized Quality-Assured Ambiguous Context Mediation

B+ Trees
B+ Trees

6.18_Exam2Review - Help-A-Bull
6.18_Exam2Review - Help-A-Bull

... Quicksort uses a divide-and-conquer strategy A recursive approach  The original problem partitioned into simpler subproblems,  Each sub problem considered independently. ...
Recurrence Relations
Recurrence Relations

... • Every path from the root to a leaf must have the same number of black nodes. How balanced of a tree will this produce? How hard will it be to maintain? ...
Radix tree - Wikipedia, the free encyclopedia
Radix tree - Wikipedia, the free encyclopedia

lec_B_Tree
lec_B_Tree

Chapter 10: Efficient Collections (skip lists, trees)
Chapter 10: Efficient Collections (skip lists, trees)

... class non-deterministic. If you twice insert the same values into a skip list, you may end up with very different internal links. Random chance used in the right way can be a very powerful tool. In one experiment to test the execution time of the skip list we compared the insertion time to that of a ...
Kinetic data structures
Kinetic data structures

... than O(log n) envelopes Use a BB[alpha] tree  think of each pair of nodes participating in a rotation as new nodes, then the total size of envelopes corresponding to new nodes is O(nlog(n)) ...
Binary Trees
Binary Trees

...  lLink: points to the root node of the left subtree  rLink: points to the root node of the right subtree ...
Algorithms and Data Structures
Algorithms and Data Structures

power point
power point

Worst Case Constant Time Priority Queue
Worst Case Constant Time Priority Queue

... Since we can not lower the worst case time to The super node is both a left and a right splitting constant time for the different vEB operations in node for all the elements in the set. Hence, all any of the above models of computation we need a elements, even minimum and maximum, have both new mode ...
Checking Data Structure Properties Orders of Magnitude Faster
Checking Data Structure Properties Orders of Magnitude Faster

... Intuitively, we memoize whatever the program’s formal contracts need, and use the data structure itself as the storage space. A function is eligible to be memoized, if 1) it is called (directly or indirectly) from a formal contract (otherwise its value is not needed for runtime checks), 2) it has a ...
Docs
Docs

... club is divided into several different teams and each person is a member of exactly one team. How could you quickly determine who was on who's team? That is where a Disjoint Set Data Structure comes into play. A disjoint set data structure groups elements into disjoint sets so that elements in the s ...
Binary tree
Binary tree

... Maximum number of nodes in a binary tree of height k is 2k+1 -1. A full binary tree with height k is a binary tree which has 2k+1 - 1 nodes. A complete binary tree with height k is a binary tree which has maximum number of nodes possible in levels 0 through k -1, and in (k -1)’th level all nodes wit ...
An Efficient Local Search Algorithm for the Linear Ordering
An Efficient Local Search Algorithm for the Linear Ordering

Trees - Applied Computer Science
Trees - Applied Computer Science

... The public preorder method below has the responsibility of creating an empty list for the snapshot buffer, and invoking the recursive method at the root of the tree (assuming the tree is nonempty). We rely on a java.util.ArrayList instance as an Iterable instance for the snapshot buffer. ...
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Interval tree

In computer science, an interval tree is a tree data structure to hold intervals. Specifically, it allows one to efficiently find all intervals that overlap with any given interval or point. It is often used for windowing queries, for instance, to find all roads on a computerized map inside a rectangular viewport, or to find all visible elements inside a three-dimensional scene. A similar data structure is the segment tree.The trivial solution is to visit each interval and test whether it intersects the given point or interval, which requires O(n) time, where n is the number of intervals in the collection. Since a query may return all intervals, for example if the query is a large interval intersecting all intervals in the collection, this is asymptotically optimal; however, we can do better by considering output-sensitive algorithms, where the runtime is expressed in terms of m, the number of intervals produced by the query. Interval trees have a query time of O(log n + m) and an initial creation time of O(n log n), while limiting memory consumption to O(n). After creation, interval trees may be dynamic, allowing efficient insertion and deletion of an interval in O(log n). If the endpoints of intervals are within a small integer range (e.g., in the range [1,...,O(n)]), faster data structures exist with preprocessing time O(n) and query time O(1+m) for reporting m intervals containing a given query point.
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