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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.
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 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
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.
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.
In this second edition of his successful book, experienced teacher and author Mark Allen Weiss continues to refine and enhance his innovative approach to algorithms and data structures. Written for the advanced data structures course, this text highlights theoretical topics such as abstract data types and the efficiency of algorithms, as well as performance and running time. Before covering algorithms and data structures, the author provides a brief introduction to C++ for programmers unfamiliar with the language. Dr Weiss's clear writing style, logical organization of topics, and extensive use of figures and examples to demonstrate the successive stages of an algorithm make this an accessible, valuable text. New to this Edition *An appendix on the Standard Template Library (STL) *C++ code, tested on multiple platforms, that conforms to the ANSI ISO final draft standard 0201361221B04062001
This book starts with the fundamentals of data structures and finally lead to the muchdetailed discussion on the subject. The very first chapter introduces the readers with elementary concepts of C as type conversions, structures, pointers, dynamic memory management, functions, flow-chart, algorithm and fundamental of data structures. This textbook covers the syllabus of Semester College course on data structures. It provides both a strong theoretical base in data structures and an advanced approach to their representation in C. The text is useful to C professionals and programmers, as well as students of any branch of Engineering of graduate and postgraduate courses. The data structures are presented with in the context of complete working programs that have been tested both on a UNIX system and a personal computer using Turbo-C++, Compiler. The code is developed in a top-down fashion, typically with the low-level data structures implementation following the high-level application code. This approach foster good programming habits and makes subject matter more interesting. The book has three goals- to develop a consistent programming methodology, to develop data structures access techniques and to introduce algorithms. The bulk of the text is developed to make a strong hold on data structures. Programming style and development methodology are introduced and its applications are presented. This has the advantage of allowing the reader to concentrate on the data structures, while illustrating how good practices make programming easier.
This second edition of Data Structures Using C has been developed to provide a comprehensive and consistent coverage of both the abstract concepts of data structures as well as the implementation of these concepts using C language. It begins with a thorough overview of the concepts of C programming followed by introduction of different data structures and methods to analyse the complexity of different algorithms. It then connects these concepts and applies them to the study of various data structures such as arrays, strings, linked lists, stacks, queues, trees, heaps, and graphs. The book utilizes a systematic approach wherein the design of each of the data structures is followed by algorithms of different operations that can be performed on them, and the analysis of these algorithms in terms of their running times. Each chapter includes a variety of end-chapter exercises in the form of MCQs with answers, review questions, and programming exercises to help readers test their knowledge.
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.
Implementations, as well as interesting, real-world examples of each data structure and algorithm, are shown in the text. Full source code appears on the accompanying disk.