A Second Year Course on Data Structures Based on Functional
... reasons for this choice are the same as in the imperative case: a first advanced programming course must put the emphasis more in fundamental concepts and techniques than in broading the programmer catalog of available algorithms. Next courses can play this role. As one of the main concerns is efficien ...
... reasons for this choice are the same as in the imperative case: a first advanced programming course must put the emphasis more in fundamental concepts and techniques than in broading the programmer catalog of available algorithms. Next courses can play this role. As one of the main concerns is efficien ...
A Second Year Course on Data Structures Based on Functional
... of this are given in the paper. When there is not such an alternative, it seems unavoidable the use of arrays updated in place. For this reason, we include a last part of the course based on mutable arrays. There are now enough proposals to have this feature in a functional language without losing t ...
... of this are given in the paper. When there is not such an alternative, it seems unavoidable the use of arrays updated in place. For this reason, we include a last part of the course based on mutable arrays. There are now enough proposals to have this feature in a functional language without losing t ...
Representing and Matching multi-object Images with Holes using Concavity Trees
... and provides maximum performance only for a finite set of applications, while pro11 ...
... and provides maximum performance only for a finite set of applications, while pro11 ...
An Evaluation of Generic Bulk Loading Techniques
... methods for processing a set of homogenous operations on an index in bulk. Among the different bulk operations, bulk loading of an index has attracted most of the research attention. In this paper, we address the problem of bulk loading an index for a given data set as fast as possible. We are prima ...
... methods for processing a set of homogenous operations on an index in bulk. Among the different bulk operations, bulk loading of an index has attracted most of the research attention. In this paper, we address the problem of bulk loading an index for a given data set as fast as possible. We are prima ...
Slider: Incremental Sliding Window Analytics
... sub-computations, and then a dependence graph is constructed to track control and data dependencies between all sub-computations. Thereafter, a change propagation algorithm is used to update the output by propagating the changes through the graph. The idea behind change propagation is to initially i ...
... sub-computations, and then a dependence graph is constructed to track control and data dependencies between all sub-computations. Thereafter, a change propagation algorithm is used to update the output by propagating the changes through the graph. The idea behind change propagation is to initially i ...
A Fully Retroactive Priority Queues
... each non-leaf node x, we store a single partially retroactive priority queue that tracks all updates to the subtree rooted at x. Before continuing, it is important to note that a fully retroactive priority queue can be built from scratch, given k updates, in O(k log k) time. We see later that this p ...
... each non-leaf node x, we store a single partially retroactive priority queue that tracks all updates to the subtree rooted at x. Before continuing, it is important to note that a fully retroactive priority queue can be built from scratch, given k updates, in O(k log k) time. We see later that this p ...
11. Linked lists
... 1. There is a provision for finding the first entry of the list. In the barbershop, the first entry in the current list is the one in the barber chair. Anyone entering the shop would know very little about the complete ordering of customers, but would know that the person in the chair is at the head ...
... 1. There is a provision for finding the first entry of the list. In the barbershop, the first entry in the current list is the one in the barber chair. Anyone entering the shop would know very little about the complete ordering of customers, but would know that the person in the chair is at the head ...
Engineering a Compressed Suffix Tree Implementation
... already extensively studied by Munro, Raman, and Rao [22]. In addition to these navigational operations, suffix trees have several other useful operations such as suffix links, constant time lowest common ancestor (lca) queries, and pattern search capabilities. Sadakane developed a fully functional ...
... already extensively studied by Munro, Raman, and Rao [22]. In addition to these navigational operations, suffix trees have several other useful operations such as suffix links, constant time lowest common ancestor (lca) queries, and pattern search capabilities. Sadakane developed a fully functional ...
Online-Autotuning of Parallel SAH kD-Trees - IPD Tichy
... exploiting the benefits of parallelism brought by ubiquitous parallel multicore processors. Prominent examples are Shevtsov et al. [1] and Choi et al. [2], who combine parallel precomputation of the upper tree levels with subsequent parallel processing of the lower levels via space subdivision. Foll ...
... exploiting the benefits of parallelism brought by ubiquitous parallel multicore processors. Prominent examples are Shevtsov et al. [1] and Choi et al. [2], who combine parallel precomputation of the upper tree levels with subsequent parallel processing of the lower levels via space subdivision. Foll ...
Lab Manual Data Structures (P) COT-213 and IT-215
... VIII.(a) WAP to implement 2 overlapping queues in an Array of size ‘N’. There are facing in opposite direction to eachother. Give IsEmpty(i), Insert(i), Delete(i) and IsFull(i) routines for ith queue. WAP to implement Dequeue using Arrays with all the basic operations. ...
... VIII.(a) WAP to implement 2 overlapping queues in an Array of size ‘N’. There are facing in opposite direction to eachother. Give IsEmpty(i), Insert(i), Delete(i) and IsFull(i) routines for ith queue. WAP to implement Dequeue using Arrays with all the basic operations. ...
CS 171: Introduction to Computer Science II Linked List
... • Example: remove “be” from the linked list • Search the item, then remove it • Need to keep the reference to the previous element as well as current element. • Need to consider the case when current is first Node current = first; Node previous = first; while (current != null && !current.item.equals ...
... • Example: remove “be” from the linked list • Search the item, then remove it • Need to keep the reference to the previous element as well as current element. • Need to consider the case when current is first Node current = first; Node previous = first; while (current != null && !current.item.equals ...
Introduction to Algorithms, Data Structures and Formal Languages
... education of every computer scientist. The textbook is closely based on the syllabus of the course COMPSCI220, which the authors and their colleagues have taught at the University of Auckland for several years. The book could also be used for self-study. Many exercises are provided, a substantial pr ...
... education of every computer scientist. The textbook is closely based on the syllabus of the course COMPSCI220, which the authors and their colleagues have taught at the University of Auckland for several years. The book could also be used for self-study. Many exercises are provided, a substantial pr ...
Authenticated Data Structures for Graph and Geometric Searching
... same connected component and a path query returns a path, if it exists, between two given vertices. We could also define update operations of S that add and/or remove vertices and edges. As a second example, S could be a collection of line segments in the plane forming a polygonal chain, where an in ...
... same connected component and a path query returns a path, if it exists, between two given vertices. We could also define update operations of S that add and/or remove vertices and edges. As a second example, S could be a collection of line segments in the plane forming a polygonal chain, where an in ...
Chapter26
... 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 ...
9 Data Structures for Disjoint Sets (October 10 and 15)
... The cost of Find(x0 ) is proportional to the number of nodes on the find path from x 0 up to its leader (before path compression). To count up the total cost of all Finds, we use an accounting method—each object x0 , x1 , x2 , . . . , xl on the find path pays a $1 tax into one of several different b ...
... The cost of Find(x0 ) is proportional to the number of nodes on the find path from x 0 up to its leader (before path compression). To count up the total cost of all Finds, we use an accounting method—each object x0 , x1 , x2 , . . . , xl on the find path pays a $1 tax into one of several different b ...
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.