Implement practical data structures and algorithms for text search and discover how it is used inside other larger applications. This unique in-depth guide explains string algorithms using the C programming language. String Algorithms in C teaches you the following algorithms and how to use them: classical exact search algorithms; tries and compact tries; suffix trees and arrays; approximative pattern searches; and more. In this book, author Thomas Mailund provides a library with all the algorithms and applicable source code that you can use in your own programs. There are implementations of all the algorithms presented in this book so there are plenty of examples. You’ll understand that string algorithms are used in various applications such as image processing, computer vision, text analytics processing from data science to web applications, information retrieval from databases, network security, and much more. What You Will Learn Use classical exact search algorithms including naive search, borders/border search, Knuth-Morris-Pratt, and Boyer-Moor with or without Horspool Search in trees, use tries and compact tries, and work with the Aho-Carasick algorithm Process suffix trees including the use and development of McCreight’s algorithm Work with suffix arrays including binary searches; sorting naive constructions; suffix tree construction; skew algorithms; and the Borrows-Wheeler transform (BWT) Deal with enhanced suffix arrays including longest common prefix (LCP) Carry out approximative pattern searches among suffix trees and approximative BWT searches Who This Book Is For Those with at least some prior programming experience with C or Assembly and have at least prior experience with programming algorithms.

Detailed algorithms for string processes and pattern matching have examples from natural language processing, molecular sequencing, and databases.

String algorithms are a traditional area of study in computer science. In recent years their importance has grown dramatically with the huge increase of electronically stored text and of molecular sequence data (DNA or protein sequences) produced by various genome projects. This book is a general text on computer algorithms for string processing. In addition to pure computer science, the book contains extensive discussions on biological problems that are cast as string problems, and on methods developed to solve them. It emphasises the fundamental ideas and techniques central to today's applications. New approaches to this complex material simplify methods that up to now have been for the specialist alone. With over 400 exercises to reinforce the material and develop additional topics, the book is suitable as a text for graduate or advanced undergraduate students in computer science, computational biology, or bio-informatics. Its discussion of current algorithms and techniques also makes it a reference for professionals.

String matching is a very important subject in the wider domain of text processing. It consists of finding one, or more generally, all the occurrences of a string (more generally called a pattern) in a text. The Handbook of Exact String Matching Algorithms presents 38 methods for solving this problem. For each, it gives the main features, a description, its C code, an example and references.

This much-needed book on the design of algorithms and data structures for text processing emphasizes both theoretical foundations and practical applications. It is intended to serve both as a textbook for courses on algorithm design, especially those related to text processing, and as a reference for computer science professionals. The work takes a unique approach, one that goes more deeply into its topic than other more general books. It contains both classical algorithms and recent results of research on the subject. The book is the first text to contain a collection of a wide range of text algorithms, many of them quite new and appearing here for the first time. Other algorithms, while known by reputation, have never been published in the journal literature. Two such important algorithms are those of Karp, Miller and Rosenberg, and that of Weiner. Here they are presented together for the fist time. The core of the book is the material on suffix trees and subword graphs, applications of these data structures, new approaches to time-space optimal string-matching, and text compression. Also covered are basic parallel algorithms for text problems. Applications of all these algorithms are given for problems involving data retrieval systems, treatment of natural languages, investigation of genomes, data compression software, and text processing tools. From the theoretical point of view. the book is a goldmine of paradigms for the development of efficient algorithms, providing the necessary foundation to creating practical software dealing with sequences. A crucial point in the authors' approach is the development of a methodology for presenting text algorithms so they can be fully understood. Throughout, the book emphasizes the efficiency of algorithms, holding that the essence of their usefulness depends on it. This is especially important since the algorithms described here will find application in "Big Science" areas like molecular sequence analysis where the explosive growth of data has caused problems for the current generation of software. Finally, with its development of theoretical background, the book can be considered as a mathematical foundation for the analysis and production of text processing algorithms.

In today’s fast and competitive world, a program’s performance is just as important to customers as the features it provides. This practical guide teaches developers performance-tuning principles that enable optimization in C++. You’ll learn how to make code that already embodies best practices of C++ design run faster and consume fewer resources on any computer—whether it’s a watch, phone, workstation, supercomputer, or globe-spanning network of servers. Author Kurt Guntheroth provides several running examples that demonstrate how to apply these principles incrementally to improve existing code so it meets customer requirements for responsiveness and throughput. The advice in this book will prove itself the first time you hear a colleague exclaim, “Wow, that was fast. Who fixed something?” Locate performance hot spots using the profiler and software timers Learn to perform repeatable experiments to measure performance of code changes Optimize use of dynamically allocated variables Improve performance of hot loops and functions Speed up string handling functions Recognize efficient algorithms and optimization patterns Learn the strengths—and weaknesses—of C++ container classes View searching and sorting through an optimizer’s eye Make efficient use of C++ streaming I/O functions Use C++ thread-based concurrency features effectively

"Solutions and examples for C++ programmers"--Cover.

This books reviews recent theoretical and practical advances on suffix sorting and introduces algorithmic solutions to problems of wide interest for the construction of fundamental data structures that operate efficiently on strings namely, constructing the suffix array, the longest common prefix (LCP) array, the document array and the Lyndon array. These data structures are the cornerstone of many algorithmic solutions in Bioiformatics, Information Retrieval and Data Compression. This book introduces the relevant problem areas, their importance, the notation and related algorithms and then presents the algorithmic solutions for indexing data structure constructions. This book is intended for graduate students, researchers and practitioners from Computer Science and Bioinformatics with a strong interest in algorithmic aspects.

Presents recently developed algorithms for searching for simple, multiple and extended strings, regular expressions, exact and approximate matches.

Strings are fundamental data type in real world and developing algorithms to deal with it is an important domain. In interviews, often, string algorithms are most insightful and challenging.In this guide for the day before your coding interview, we have explored some problems and demonstrated the thought process to solve it starting from the brute force solutions. In the process, we have covered all fundamental ideas along with applying Dynamic Programming to String algorithms so that you are able to solve all string-based problems. Some of the problems we have covered are: - Check substring: This is an important fundamental problem where we learn how strings can be handled just like numeric data and algorithms for numeric data can be leveraged.Some of the core concepts we explored are string hashing, rolling hash and much more.- Longest common substring: This is a core problem as this uses the concepts we gained in the previous problems and an alternative solution is to use Dynamic Programming.The core idea is to apply Dynamic Programming over two different string data.- Longest repeating substring: In line with our previous problem, we explored how to apply Dynamic Programming for this problem. The key distinction is that we are dealing with just 1 string instead of 2 strings as in the previous problem. Unlike the previous problem, the Dynamic Programming approach is the only optimal solution.With these problems and the thought process to solve them, you will be fully prepared.This book has been carefully prepared and reviewed by Top programmers and Algorithmic researchers and members of OpenGenus. We would like to thank Aditya Chatterjee and Ue Kiao for their expertise in this domain and reviews from professors at The University of Tokyo and Tokyo Institute of Technology.Read this book now and ace your upcoming coding interview. This is a must read for everyone preparing for Coding Interviews at top companies.Books in this series ("Day before coding Interview"): - Problems for the day before your coding interview- Greedy Algorithms for the day before your Coding Interview- Dynamic Programming for the day before your coding interview- String Algorithms for the day before your Coding Interview