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Trimester 2 - 2015 / 2016

Data Structures and Algorithms implementation in Go Data Structures and Algorithms Clean and simple implementation in Go Implementation There are several data structures and algorithms implemented in this project. The list will be replenished with time. Data structures Circular Buffer Linked List Doubly Linked List Stack Queue Binary Tree Hash Table Searching algorithms Linear Search Binary Search Jump Search Interpolation Search Exponential Search Ternary Search Sorting algorithms Selection Sort Insertion Sort Bubble Sort Comb Sort Cocktail Sort Gnome Sort Usage The library is not intended for direct use by importing. We strongly recommend copying the necessary implementations and adjusting to your case. You can download the source using go get command: go get github.com/floyernick/Data-Structures-and-Algorithms Don't forget about proverb: A little copying is better than a little dependency. Contribute We would be happy to receive your propositions of improvement ;) License This project is licensed under the MIT License . Authors Mykyta Paliienko - GitHub profile To restore the repository download the bundle wget https://archive.org/download/github.com-floyernick-Data-Structures-and-Algorithms_-_2018-04-03_09-13-13/floyernick-Data-Structures-and-Algorithms_-_2018-04-03_09-13-13.bundle and run: git clone floyernick-Data-Structures-and-Algorithms_-_2018-04-03_09-13-13.bundle Source: https://github.com/floyernick/Data-Structures-and-Algorithms Uploader: floyernick Upload date: 2018-04-03

Matroids are discrete mathematical structures that appear in a variety of applications. They are structures for which greedy algorithm gives an optimal solution, and when interested characterize such problems as minimum weight maximum cardinality bipartite matching. In this paper we study a class of combinatorial problems from a matroid point of view. Consider a matroid of rank n in which each element has a real-valued cost and one of d 1 colors. A class of matroid intersection problems is studied in which one of the matroids is a partition matroid that specifies that base have 9 sub k elements of color j, for j = 12 =1, 2, ..., d. Relationships are characterized among the solutions to the family of problems generated when the vector (q sub 1, q sub,... q sub d) is allowed to range over all values that sum to n. A fast algorithm is given for solving such matroid intersection problems when d is small. A characterization is presented for how the solution changes when one element changes in cost. Data structures are given for updating the solution on-line each time the cost of an arbitrary matroid element is modified. Efficient update algorithms are given for maintaining a color-constrained minimum spanning tree in either a general or a planar graph. An application for the techniques to finding a minimum spanning tree with several degree-constrained vertices is described.

A description of the discrete-pattern matching process is presented with the key elements described. Six data structure approaches and related search algorithms are presented. Twelve programs were coded to implement five out of the six structures/algorithms using packed and unpacked approaches on a CYBER 74. Runs were made with twelve different data files using Fortran, English, and random text. The effect of the number of patterns in the data structure and the expected incidence in the text were included. The best data structures/algorithms were a finite state automata and an alternate/successor linked list. (Author)

Trimester 1 - 2019/2020

The focus of this research is the investigation of data structures and associated search algorithms for automated fault diagnosis of complex systems such as the Hubble Space Telescope. Such data structures and algorithms will form the basis of a more sophisticated Knowledge Based Fault Diagnosis System. As a part of the research, several prototypes were written in VAXLISP and implemented on one of the VAX-11/780's at the Marshall Space Flight Center. This report describes and gives the rationale for both the data structures and algorithms selected. A brief discussion of a user interface is also included.

In this Learning Data Structures and Algorithms video training course, Rod Stephens will teach you how to analyze and implement common algorithms used in data processing. This course is designed for the absolute beginner, meaning no previous programming experience is required. You will start by learning about the complexity theory, then jump into learning about numerical algorithms, including randomizing arrays, prime factorization, and numerical integration. From there, Rod will teach you about linked lists, such as singly linked lists, sorted, and doubly linked lists. This video tutorial also covers arrays, stacks and queues, and sorting. You will also learn about searching, hash tables, recursion, and backtracking algorithms. Finally, you will cover trees, balanced trees, decision trees, and network algorithms. Once you have completed this video training course, you will be fully capable of analyzing and implementing algorithms, as well as be able to select the best algorithm for various situations. Working files are included, allowing you to follow along with the author throughout the lessons.

Inroduction to Data structures and Algorithms || Deepali Srivastava

Algorithms and Data Structures N Wirth, 1985 Contents Preface 1 Fundamental Data Structures 1.1 Introduction 1.2 The Concept of Data Type 1.3 Primitive Data Types 1.4 Standard Primitive Types 1.4.1 Integer types 1.4.2 The type REAL 1.4.3 The type BOOLEAN 1.4.4 The type CHAR 1.4.5 The type SET 1.5 The Array Structure 1.6 The Record Structure 1.7 Representation of Arrays, Records, and Sets 1.7.1 Representation of Arrays 1.7.2 Representation of Recors 1.7.3 Representation of Sets 1.8 The File (Sequence) 1.8.1 Elementary File Operators 1.8.2 Buffering Sequences 1.8.3 Buffering between Concurrent Processes 1.8.4 Textual Input and Output 1.9 Searching 1.9.1 Linear Search 1.9.2 Binary Search 1.9.3 Table Search 1.9.4 Straight String Search 1.9.5 The Knuth-Morris-Pratt String Search 1.9.6 The Boyer-Moore String Search Exercises 2 Sorting 2.1 Introduction 2.2 Sorting Arrays 2.2.1 Sorting by Straight Insertion 2.2.2 Sorting by Straight Selection 2.2.3 Sorting by Straight Exchange 2.3 Advanced Sorting Methods 2.3.1 Insertion Sort by Diminishing Increment 2.3.2 Tree Sort 2.3.3 Partition Sort 2.3.4 Finding the Median 2.3.5 A Comparison of Array Sorting Methods 2.4 Sorting Sequences 2.4.1 Straight Merging 2.4.2 Natural Merging 2.4.3 Balanced Multiway Merging 2.4.4 Polyphase Sort 2.4.5 Distribution of Initial Runs Exercises 3 Recursive Algorithms 3.1 Introduction 3.2 When Not to Use Recursion 3.3 Two Examples of Recursive Programs 3.4 Backtracking Algorithms 3.5 The Eight Queens Problem 3.6 The Stable Marriage Problem 3.7 The Optimal Selection Problem Exercises 4 Dynamic Information Structures 4.1 Recursive Data Types 4.2 Pointers 4.3 Linear Lists 4.3.1 Basic Operations 4.3.2 Ordered Lists and Reorganizing Lists 4.3.3 An Application: Topological Sorting 4.4 Tree Structures 4.4.1 Basic Concepts and Definitions 4.4.2 Basic Operations on Binary Trees 4.4.3 Tree Search and Insertion 4.4.4 Tree Deletion 4.4.5 Analysis of Tree Search and Insertion 4.5 Balanced Trees 4.5.1 Balanced Tree Insertion 4.5.2 Balanced Tree Deletion 4.6 Optimal Search Trees 4.7 B-Trees 4.7.1 Multiway B-Trees 4.7.2 Binary B-Trees 4.8 Priority Search Trees Exercises 5 Key Transformations (Hashing) 5.1 Introduction 5.2 Choice of a Hash Function 5.3 Collision handling 5.4 Analysis of Key Transformation Exercises Appendices A The ASCII Character Set B The Syntax of Oberon Index

We present DASH, a C++ template library that offers distributed data structures and parallel algorithms and implements a compiler-free PGAS (partitioned global address space) approach. DASH offers many productivity and performance features such as global-view data structures, efficient support for the owner-computes model, flexible multidimensional data distribution schemes and inter-operability with STL (standard template library) algorithms. DASH also features a flexible representation of the parallel target machine and allows the exploitation of several hierarchically organized levels of locality through a concept of Teams. We evaluate DASH on a number of benchmark applications and we port a scientific proxy application using the MPI two-sided model to DASH. We find that DASH offers excellent productivity and performance and demonstrate scalability up to 9800 cores.

Tri 2 2017/2018

Tri 2 – 2015/2016

Tri 2 – 2016/2017

poi padi da

vi, 312 pages : 28 cm

Video content can be found here: https://www.youtube.com/channel/UC0BAd8tPlDqFvDYBemHcQPQ/

RBR=DAA==17==Practice Questions of algorithms and data structures

Tri 2 – 2016/2017

data structure

data structure

xi,284p. : 25 cm

This report contains two independent papers on range searching. A range search retrieves from a file all records which conjunctively satisfy a set of range requirements for the keys; that is, each key must lie in some specified range. Range searching arises in many applications, such as data base management and statistical computing. The first paper in this report, 'A survey of algorithms and data structures for range searching' by J. L. Bentley and J. H. Friedman, describes the known 'logical structures' which can be used for range searching and then discusses the implementation of those structures in different storage media. This paper is slanted towards the practitioner. The second paper, 'Efficient worst-case data structures for range searching' by J. L. Bentley and H. A. Maurer, is more theoretical. Two new classes of data structures are proposed for range searching, establishing bounds on the asymptotic complexity of the problem. (Author)

Trimester 1 - 2017/2018

Trimester 2 - 2019/2020

Trimester 2 - 2019/2020

file

Data Structures and Algorithms

Data Structures and Algorithms

Data Structures and Algorithms

VisuAlgo: Visualising Data Structures and Algorithms through Animation http://t.co/81sfSY8x84 http://t.co/kfTWGwS5H9

Adaptive refinement and the complicated data structures required to support it are discussed. These data structures must be carefully tuned, especially in three dimensions where the time and storage requirements of algorithms are crucial. Another major issue is grid generation. The options available seem to be curvilinear fitted grids, constructed on iterative graphics systems, and unfitted Cartesian grids, which can be constructed automatically. On several grounds, including storage requirements, the second option seems preferrable for the well behaved scalar elliptic problems considered here. A variety of techniques for treatment of boundary conditions on such grids are reviewed. A new approach, which may overcome some of the difficulties encountered with previous approaches, is also presented.

Adaptive refinement and the complicated data structures required to support it are discussed. These data structures must be carefully tuned, especially in three dimensions where the time and storage requirements of algorithms are crucial. Another major issue is grid generation. The options available seem to be curvilinear fitted grids, constructed on iterative graphics systems, and unfitted Cartesian grids, which can be constructed automatically. On several grounds, including storage requirements, the second option seems preferrable for the well behaved scalar elliptic problems considered here. A variety of techniques for treatment of boundary conditions on such grids are reviewed. A new approach, which may overcome some of the difficulties encountered with previous approaches, is also presented.

Adaptive refinement and the complicated data structures required to support it are discussed. These data structures must be carefully tuned, especially in three dimensions where the time and storage requirements of algorithms are crucial. Another major issue is grid generation. The options available seem to be curvilinear fitted grids, constructed on iterative graphics systems, and unfitted Cartesian grids, which can be constructed automatically. On several grounds, including storage requirements, the second option seems preferrable for the well behaved scalar elliptic problems considered here. A variety of techniques for treatment of boundary conditions on such grids are reviewed. A new approach, which may overcome some of the difficulties encountered with previous approaches, is also presented.

Although large amounts of programming knowledge are available to human programmers in the form of books and articles, very little of this knowledge is available in a form suitable for use by a machine in performing programming tasks automatically. The principal goal of the research reported here is the explication of programming knowledge to a sufficient level of detail that it can be used effectively by a machine. The programming task considered in this experiment is that of constructing concrete implementations of abstract algorithms in the domain of symbolic programming. Knowledge about several aspects of symbolic programming has been expressed as a collection of four hundred refinement rules. The rules deal primarily with collections and mappings and ways of manipulating such structures, including several enumeration, sorting and searching techniques. The principal representation techniques covered include the representation of sets as linked lists and arrays (both ordered and unordered), and the representation of mappings as tables, sets of pairs, property list markings, and inverted mappings (indexed by range element). In addition to these general constructs, many low-level programming details are covered (such as the use of variables to store values).

Although large amounts of programming knowledge are available to human programmers in the form of books and articles, very little of this knowledge is available in a form suitable for use by a machine in performing programming tasks automatically. The principal goal of the research reported here is the explication of programming knowledge to a sufficient level of detail that it can be used effectively by a machine. The programming task considered in this experiment is that of constructing concrete implementations of abstract algorithms in the domain of symbolic programming. Knowledge about several aspects of symbolic programming has been expressed as a collection of four hundred refinement rules. The rules deal primarily with collections and mappings and ways of manipulating such structures, including several enumeration, sorting and searching techniques. The principal representation techniques covered include the representation of sets as linked lists and arrays (both ordered and unordered), and the representation of mappings as tables, sets of pairs, property list markings, and inverted mappings (indexed by range element). In addition to these general constructs, many low-level programming details are covered (such as the use of variables to store values).

Video content can be found here: https://www.youtube.com/channel/UC0BAd8tPlDqFvDYBemHcQPQ/

Learn Data Structures and Algorithms with Golang is a practical guide for developers looking to deepen their understanding of core computer science concepts using the Go programming language. Through hands-on examples and clear explanations, this book helps you implement efficient algorithms and master essential data structures to write faster, more scalable code in Go.

Algorithms and Data Structures Wiki dumped with WikiTeam tools.

Multi-adaptive Galerkin methods are extensions of the standard continuous and discontinuous Galerkin methods for the numerical solution of initial value problems for ordinary or partial differential equations. In particular, the multi-adaptive methods allow individual and adaptive time steps to be used for different components or in different regions of space. We present algorithms for efficient multi-adaptive time-stepping, including the recursive construction of time slabs and adaptive time step selection. We also present data structures for efficient storage and interpolation of the multi-adaptive solution. The efficiency of the proposed algorithms and data structures is demonstrated for a series of benchmark problems.

Trimester 1 2015 / 2016

Trimester 1 2015 / 2016

Trimester 1 2015 / 2016

DSA Course in C and C++

Data Structures

Tri 3 2021/2022

Tri 1 2022/2023 (Term Id 2210)

Dr. Dobb's Essential books on Algorithms and Data Structures is a CD-ROM from 1995 containing the following 8 books: (1985) Data Structures: From Arrays to Priority Queues by Wayne Amsbury (1935-2006) (1990) Introduction to Algorithims by Thomas H. Cormen (1956-), Charles E. Leiserson (1953-), and Ronald L. Rivest (1947-) (1992) Information Retrieval: Data Structures & Algorithms edited by William B. Frakes (1952-) and Ricardo Baeza-Yates (1961-) (1976, 1983) Fundamentals of Data Structures by Ellis Horowitz (1944-) and Sartaj Sahni (1949-) (1985) Reliable Data Structures in C by Thomas Plum (1943-2024) (1993) Data Structures and Algorithm Analysis in C by Mark Allen Weiss (19??-) (1993) Practical Data Structures in C++ by Bryan Flamig (1957-) (1988) Data Structures, Algorithms and Program Style Using C by James F. Korsh (1938-) and Leonard J. Garrett (1926-2023) The reader software will not run on a modern Windows machine, and requires 16-bit program compatibility to run.

Dr. Dobb's Essential books on Algorithms and Data Structures is a CD-ROM from 1995 containing the following 8 books: (1985) Data Structures: From Arrays to Priority Queues by Wayne Amsbury (1935-2006) (1990) Introduction to Algorithims by Thomas H. Cormen (1956-), Charles E. Leiserson (1953-), and Ronald L. Rivest (1947-) (1992) Information Retrieval: Data Structures & Algorithms edited by William B. Frakes (1952-) and Ricardo Baeza-Yates (1961-) (1976, 1983) Fundamentals of Data Structures by Ellis Horowitz (1944-) and Sartaj Sahni (1949-) (1985) Reliable Data Structures in C by Thomas Plum (1943-2024) (1993) Data Structures and Algorithm Analysis in C by Mark Allen Weiss (19??-) (1993) Practical Data Structures in C++ by Bryan Flamig (1957-) (1988) Data Structures, Algorithms and Program Style Using C by James F. Korsh (1938-) and Leonard J. Garrett (1926-2023) The reader software will not run on a modern Windows machine, and requires 16-bit program compatibility to run.

Dr. Dobb's Essential books on Algorithms and Data Structures is a CD-ROM from 1995 containing the following 8 books: (1985) Data Structures: From Arrays to Priority Queues by Wayne Amsbury (1935-2006) (1990) Introduction to Algorithims by Thomas H. Cormen (1956-), Charles E. Leiserson (1953-), and Ronald L. Rivest (1947-) (1992) Information Retrieval: Data Structures & Algorithms edited by William B. Frakes (1952-) and Ricardo Baeza-Yates (1961-) (1976, 1983) Fundamentals of Data Structures by Ellis Horowitz (1944-) and Sartaj Sahni (1949-) (1985) Reliable Data Structures in C by Thomas Plum (1943-2024) (1993) Data Structures and Algorithm Analysis in C by Mark Allen Weiss (19??-) (1993) Practical Data Structures in C++ by Bryan Flamig (1957-) (1988) Data Structures, Algorithms and Program Style Using C by James F. Korsh (1938-) and Leonard J. Garrett (1926-2023) The reader software will not run on a modern Windows machine, and requires 16-bit program compatibility to run.