Advanced Data Structures


Book Description

Advanced Data Structures presents a comprehensive look at the ideas, analysis, and implementation details of data structures as a specialized topic in applied algorithms. Data structures are how data is stored within a computer, and how one can go about searching for data within. This text examines efficient ways to search and update sets of numbers, intervals, or strings by various data structures, such as search trees, structures for sets of intervals or piece-wise constant functions, orthogonal range search structures, heaps, union-find structures, dynamization and persistence of structures, structures for strings, and hash tables. This is the first volume to show data structures as a crucial algorithmic topic, rather than relegating them as trivial material used to illustrate object-oriented programming methodology, filling a void in the ever-increasing computer science market. Numerous code examples in C and more than 500 references make Advanced Data Structures an indispensable text. topic. Numerous code examples in C and more than 500 references make Advanced Data Structures an indispensable text.




Advanced Algorithms and Data Structures


Book Description

Advanced Algorithms and Data Structures introduces a collection of algorithms for complex programming challenges in data analysis, machine learning, and graph computing. Summary As a software engineer, you’ll encounter countless programming challenges that initially seem confusing, difficult, or even impossible. Don’t despair! Many of these “new” problems already have well-established solutions. Advanced Algorithms and Data Structures teaches you powerful approaches to a wide range of tricky coding challenges that you can adapt and apply to your own applications. Providing a balanced blend of classic, advanced, and new algorithms, this practical guide upgrades your programming toolbox with new perspectives and hands-on techniques. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Can you improve the speed and efficiency of your applications without investing in new hardware? Well, yes, you can: Innovations in algorithms and data structures have led to huge advances in application performance. Pick up this book to discover a collection of advanced algorithms that will make you a more effective developer. About the book Advanced Algorithms and Data Structures introduces a collection of algorithms for complex programming challenges in data analysis, machine learning, and graph computing. You’ll discover cutting-edge approaches to a variety of tricky scenarios. You’ll even learn to design your own data structures for projects that require a custom solution. What's inside Build on basic data structures you already know Profile your algorithms to speed up application Store and query strings efficiently Distribute clustering algorithms with MapReduce Solve logistics problems using graphs and optimization algorithms About the reader For intermediate programmers. About the author Marcello La Rocca is a research scientist and a full-stack engineer. His focus is on optimization algorithms, genetic algorithms, machine learning, and quantum computing. Table of Contents 1 Introducing data structures PART 1 IMPROVING OVER BASIC DATA STRUCTURES 2 Improving priority queues: d-way heaps 3 Treaps: Using randomization to balance binary search trees 4 Bloom filters: Reducing the memory for tracking content 5 Disjoint sets: Sub-linear time processing 6 Trie, radix trie: Efficient string search 7 Use case: LRU cache PART 2 MULTIDEMENSIONAL QUERIES 8 Nearest neighbors search 9 K-d trees: Multidimensional data indexing 10 Similarity Search Trees: Approximate nearest neighbors search for image retrieval 11 Applications of nearest neighbor search 12 Clustering 13 Parallel clustering: MapReduce and canopy clustering PART 3 PLANAR GRAPHS AND MINIMUM CROSSING NUMBER 14 An introduction to graphs: Finding paths of minimum distance 15 Graph embeddings and planarity: Drawing graphs with minimal edge intersections 16 Gradient descent: Optimization problems (not just) on graphs 17 Simulated annealing: Optimization beyond local minima 18 Genetic algorithms: Biologically inspired, fast-converging optimization




Advanced Data Structures


Book Description

Advanced data structures is a core course in Computer Science which most graduate program in Computer Science, Computer Science and Engineering, and other allied engineering disciplines, offer during the first year or first semester of the curriculum. The objective of this course is to enable students to have the much-needed foundation for advanced technical skill, leading to better problem-solving in their respective disciplines. Although the course is running in almost all the technical universities for decades, major changes in the syllabus have been observed due to the recent paradigm shift of computation which is more focused on huge data and internet-based technologies. Majority of the institute has been redefined their course content of advanced data structure to fit the current need and course material heavily relies on research papers because of nonavailability of the redefined text book advanced data structure. To the best of our knowledge well-known textbook on advanced data structure provides only partial coverage of the syllabus. The book offers comprehensive coverage of the most essential topics, including: Part I details advancements on basic data structures, viz., cuckoo hashing, skip list, tango tree and Fibonacci heaps and index files. Part II details data structures of different evolving data domains like special data structures, temporal data structures, external memory data structures, distributed and streaming data structures. Part III elucidates the applications of these data structures on different areas of computer science viz, network, www, DBMS, cryptography, graphics to name a few. The concepts and techniques behind each data structure and their applications have been explained. Every chapter includes a variety of Illustrative Problems pertaining to the data structure(s) detailed, a summary of the technical content of the chapter and a list of Review Questions, to reinforce the comprehension of the concepts. The book could be used both as an introductory or an advanced-level textbook for the advanced undergraduate, graduate and research programmes which offer advanced data structures as a core or an elective course. While the book is primarily meant to serve as a course material for use in the classroom, it could be used as a starting point for the beginner researcher of a specific domain.




Advanced Data Structures


Book Description

Learn Data Structures and Algorithms! This book is a collection of lectures notes on Data Structures and Algorithms. The content found in this book supplements the free video lecture series, of the same name, "Advanced Data Structures", by the author, Dr. Daniel Page. This video lecture series is available at http://www.pagewizardgames.com/datastructures. This book: -Contains Computer Science topics and materials comparable to those found among university courses at a similar level (second-year) at top Canadian universities. -Provides an accessible written companion and supplemental notes for those that wish to learn the subject of Data Structures and Algorithms from the video lecture series, but have difficulties taking notes, or would prefer having a written alternative to follow along. This book is ideal for those with already an introductory programming background, know a little bit about computing, and wish to learn more about Data Structures and Algorithms and begin a more formal study of Computer Science. The materials here are a great place to start for supplemental/additional learning materials on the subject for self-study, university students, or those that want to learn more about Computer Science. Dr. Daniel Page places great emphasis on the introductory mathematical aspects of Computer Science, a natural transition from a basic programming background to thinking a bit more like a computer scientist about Computer Science. This book is not a textbook. The author assumes the reader is familiar with algebra, functions, common finite and infinite series such as arithmetic series and geometric series, and basic control structures in programming or logic. All the algorithms in this book are described in English, or using Java-like pseudocode. Chapters -Chapter 1 - Introduction: Data Structures, Problems, Input Size, Algorithms, The Search Problem. -Chapter 2 - Intro to Analysis of Algorithms I: Complexity Analysis, Comparing Algorithms, Growth Rate of Functions (Asymptotics), Showing f is O(g), Showing f is not O(g). -Chapter 3 - Intro to Analysis of Algorithms II: Some Properties of O, An Iterative Example, Back to our "Easy" Search Problem. -Chapter 4 - Dictionaries: The Dictionary Problem, Simple Implementations of a Dictionary. -Chapter 5 - Hashing: Hash Function, Hash Code, Separate Chaining, Open Addressing, Revisiting the Load Factor. -Chapter 6 - Trees: Tree ADT, Linked Tree Representation, Tree Property, Computing Height of a Tree, Tree Traversals -Chapter 7 - Priority Queues & Heaps: Priority Queues, Heaps, Array-Based Implementation, Building a Heap, Application: Sorting, Introduction to Amortized Analysis -Chapter 8 - Binary Search Trees: Ordered Dictionary ADT, BST Implementations, Inorder Traversal, Smallest, Get, Put, Remove, Successor. -Chapter 9 - AVL Trees: Height, AVL Trees, Re-Balancing AVL Trees, putAVL, removeAVL, AVL Tree Performance. -Chapter 10 - Graphs: Degrees and the Handshaking Lemma, Complete Graphs, Paths and Cycles, Trees, Forests, Subgraphs, and Connectivity, Graph Representations. -Chapter 11 - Graph Traversals: Depth-First Search (DFS), Path-Finding, Cycle Detection, Counting Vertices, DFS Tree, Breadth-First Search (BFS), Summary. -Chapter 12 - Minimum Spanning Trees: Weighted Graphs, Minimum Spanning Trees & Algorithms, Prim's Algorithm, Heap-Based Implementation of Prim's Algorithm and More! -Chapter 13 - Shortest Paths: Single-Source Shortest Path Problem, Dijkstra's Algorithm. -Chapter 14 - Multiway Search Trees: Beyond Binary Search Trees, Get, Put, Successor and Remove, (2,4)-Trees, B-Trees.




JavaScript Data Structures and Algorithms


Book Description

Explore data structures and algorithm concepts and their relation to everyday JavaScript development. A basic understanding of these ideas is essential to any JavaScript developer wishing to analyze and build great software solutions. You'll discover how to implement data structures such as hash tables, linked lists, stacks, queues, trees, and graphs. You'll also learn how a URL shortener, such as bit.ly, is developed and what is happening to the data as a PDF is uploaded to a webpage. This book covers the practical applications of data structures and algorithms to encryption, searching, sorting, and pattern matching. It is crucial for JavaScript developers to understand how data structures work and how to design algorithms. This book and the accompanying code provide that essential foundation for doing so. With JavaScript Data Structures and Algorithms you can start developing your knowledge and applying it to your JavaScript projects today. What You'll Learn Review core data structure fundamentals: arrays, linked-lists, trees, heaps, graphs, and hash-tableReview core algorithm fundamentals: search, sort, recursion, breadth/depth first search, dynamic programming, bitwise operators Examine how the core data structure and algorithms knowledge fits into context of JavaScript explained using prototypical inheritance and native JavaScript objects/data types Take a high-level look at commonly used design patterns in JavaScript Who This Book Is For Existing web developers and software engineers seeking to develop or revisit their fundamental data structures knowledge; beginners and students studying JavaScript independently or via a course or coding bootcamp.




Data Structures


Book Description

A modern treatment of data structures using the C programming language. Emphasizes such programming practices as dynamic memory allocation, recursion, data abstraction, and "generic" data structures. Appropriate for sophomore level data structures courses that use C, taking advantage of the flexibility that C provides. (vs. VanWyck, Korsh/Garrett)




Advanced Data Structures in C++


Book Description

After a complete review of basic class construction with which you should be familiar, Advanced Data Structures in C++ covers more advanced features of classes. Among these are forward references, class enumerated data types, friend functions, constant data members, static data members, static member functions, reference variables that are data members, methods of inlining functions and how to make a production library. Next, Advanced Data Structures in C++ covers in depth all of the various operator overloaded functions; there are a rather large number of them. Then, the principles of inheritance are fully covered. Virtual functions are presented along with the need for them. Examples clearly illustrate their usage. Abstract base classes and pure virtual functions are presented with a significant example of their usage. Advanced Data Structures in C++ discusses C++ error handling in depth along with dynamic casting and run time type identification. How "out of memory" errors are caught is discussed in depth, since Microsoft's VC 7 (and subsequent compilers) new function now no longer returns 0 when short of memory. The design of a hierarchy of exception classes is presented showing how an application can fully utilize the C++ error handling mechanism. Also, how to replace the new and delete functions, replacing the terminate and unexpected error handlers is shown. Next, Advanced Data Structures in C++ presents a full review of the four basic container classes, including the growable array, double linked list, stack and queue. C++ programming templates are covered in depth followed by an example of converting the double linked list into a template class. How client programs are written using these template classes is presented next. A thorough discussion of binary files and hashing techniques comes next. Direct file processing techniques cover the relative record number method, the remainder method and ISAM (Indexed Sequential Access Method). How to write master file update programs is discussed in depth. The impact of structure alignment is visibly shown. Then, Advanced Data Structures in C++ shows the need for hashing techniques. Hence, various methods of hashing are presented. Trees are discussed in depth next, including notation and needed functions and tree operations, such as inserting a new node and deleting a node. Advanced Data Structures in C++ shows a complete example of a binary search tree using an ISAM data base. Advanced Data Structures in C++'s chapter on sorting algorithms presents five different methods in detail. It also implements a benchmark program you can use for comparison purposes. B-trees and their variations are covered next. A complete implementation of an AVL tree is presented. Advanced Data Structures in C++ discusses graphs, priority queues and heaps in detail. Network operations are also shown. The sample program illustrates graphs in depth including showing the shortest path. The examples show how to produce useful formatted results, not just theoretical displays. Next, sets and maps are discussed. Set implementations include the set as an array and the set as a bit vector. The map structure is used to show the very beginning steps of data compression routines. The STL (Standard Template Library) is introduced. How they are created and used is discussed. Examples show how to use the basic container classes. The last chapter of Advanced Data Structures in C++ presents the theory of complex program analysis and included the big-O notation. However, I have kept the level of math low for those who are weak on higher mathematical procedures. The concepts should be easily understood and can be utilized by anyone to estimate the performance of a routing. An appendix shows in depth how to use the new Microsoft VC (.NET) compiler to build and debug C++ programs. Each chapter of Advanced Data Structures in C++ has a set of Review Questions and Programming Problems to solve.




Probabilistic Data Structures


Book Description

This book “Probabilistic Data Structures” is an Introduction to Probabilistic Data Structures and aims to introduce the readers to ideas of randomness in Data Structure design. Contents of this book: • Preface • Introduction to Probabilistic Data Structures • List of Probabilistic Data Structures • Probabilistic Algorithms and Link with Data Structures • Basic Probabilistic Data Structures • Count Min Sketch • MinHash • LogLog • Bloom Filter • Skip List • Significance in Real Life/ Conclusion It is easier to understand randomness in algorithms with examples such as randomly splitting array in Quick Sort but most programmers fail to realize that Data Structures can be probabilistic as well. In this, not only the answer is probabilistic but also the structure. In fact, Google’s Chrome browser uses a Probabilistic Data Structure within it. Read on to find out which data structure it is and how it is used. The ideas have been presented in a simple language (avoiding technical terms) with intuitive insights which will help anyone to go through this book and enjoy the knowledge. This knowledge will help you to design better systems suited for real use. --------------------------------------------------------------- Authors: Aditya Chatterjee, Ethan Z. Booker Aditya is a Founding member at OpenGenus; Ethan has been an Intern at OpenGenus and a student at University of Wisconsin, La Crosse;




Data Structures and Advanced Algorithms


Book Description

The purpose of this book is to teach you, a budding programmer, basics of Object-Oriented Programming, data structures, and advanced algorithms using Python version 3.8. Unlike many books currently on the market, a background in math is not required to read and understand this book as the data structures and concepts will be explained in simple terms.




Advanced Topics in C


Book Description

C is the most widely used programming language of all time. It has been used to create almost every category of software imaginable and the list keeps growing every day. Cutting-edge applications, such as Arduino, embeddable and wearable computing are ready-made for C. Advanced Topics In C teaches concepts that any budding programmer should know. You'll delve into topics such as sorting, searching, merging, recursion, random numbers and simulation, among others. You will increase the range of problems you can solve when you learn how to manipulate versatile and popular data structures such as binary trees and hash tables. This book assumes you have a working knowledge of basic programming concepts such as variables, constants, assignment, selection (if..else) and looping (while, for). It also assumes you are comfortable with writing functions and working with arrays. If you study this book carefully and do the exercises conscientiously, you would become a better and more agile programmer, more prepared to code today's applications (such as the Internet of Things) in C.