Investigating Design Criteria for Searching Databases
This two-part tutorial will describe in detail the design complexities of selecting a particular search algorithm or technology. Part I investigates the key design considerations, including development issues and attributes that help determine which diverse memory architecture to incorporate into your design.
Algorithmic Information Theory
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Designing and Building Parallel Programs
Welcome to Designing and Building Parallel Programs ! My goal in this book is to provide a practitioner's guide for students, programmers, engineers, and scientists who wish to design and build efficient and cost-effective programs for parallel and distributed computer systems.
Algorithms and Complexity
Classic text provides the perfect introduction to the tools of algorithmic design and analysis, concentrating on basic principles and illustrating them with well-chosen paradigms.
Algorithms - Robert Sedgewick
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Handbook of Algorithms and Data Structures
Book For Algorithms and Data Structures
Algorithms and Complexity
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Data Structures and Algorithms
Complete data structures and algorithms course. This course is taught at the University Of Western Australia. The course teaches the following topics : Objects and ADTs, Constructors and destructors, Data Structure , Methods, Pre- and post-conditions C conventions, Error Handling, Arrays, Lists, Stacks, Stack Frames, Recursion, Sequential Searches, Binary Search , Trees, Complexity, Queues, Priority Queues , Heaps, Bubble , Heap Sort, Quick Sort , Bin Sort, Radix Sort, Searching Revisited, Red-Black trees, AVL trees, General n-ary trees, Hash Tables, Dynamic Algorithms, Fibonacci Numbers , Binomial Coefficients, Optimal Binary Search Trees, Matrix Chain Multiplication, Longest Common Subsequence, Optimal Triangulation , Graphs , Minimum Spanning Tree , Dijkstra's Algorithm , Huffman Encoding , FFT , Hard or Intractable Problems, Eulerian or Hamiltonian Paths , Travelling Salesman's Problem
Algorithms
This book evolved over the past ten years from a set of lecture notes developed while teaching
the undergraduate Algorithms course at Berkeley and U.C. San Diego. Our way of teaching
this course evolved tremendously over these years in a number of directions, partly to address
our students' background (undeveloped formal skills outside of programming), and partly to
reect the maturing of the eld in general, as we have come to see it. The notes increasingly
crystallized into a narrative, and we progressively structured the course to emphasize the
�story line� implicit in the progression of the material. As a result, the topics were carefully
selected and clustered. No attempt was made to be encyclopedic, and this freed us to include
topics traditionally de-emphasized or omitted from most Algorithms books.
Sorting and Searching Algorithms
A small guide on the following topics : Arrays, Linked Lists, Timing Estimates, Insertion sort, Shell sort, Quicksort, Hash Tables, Binary Search Trees, Red-Black Trees, Skip Lists, External Sorts, B-Trees.
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