You know how to code..but is it enough? Do you feel left out when other programmers talk about asymptotic bounds? Have you failed a job interview because you don't know computer science? The author, a senior developer at a major software company with a PhD in computer science, takes you through what you would have learned while earning a four-year computer science degree. Volume one covers the most frequently referenced topics, including algorithms and data structures, graphs, problem-solving techniques, and complexity theory. When you finish this book, you'll have the tools you need to hold your own with people who have - or expect you to have - a computer science degree.

You know how to code... ...but is it enough?Do you feel left out when other programmers talk about asymptotic bounds?Have you failed a job interview because you don't know computer science?Volume two picks up where volume one left off, covering proofs, security, hardware and software, and various advanced topics.You've learned the basics. Are you ready for what comes next?

Understand essential computer science concepts and skills. This book focuses on the foundational and fundamental concepts upon which expertise in specific areas can be developed, including computer architecture, programming language, algorithm and data structure, operating systems, computer networks, distributed systems, security, and more. According to code.org, there are 500,000 open programming positions available in the US— compared to an annual crop of just 50,000 graduating computer science majors. The US Department of Labor predicted that there will be almost a million and a half computer science jobs in the very near future, but only enough programmers to fill roughly one third of these jobs. To bridge the gap, many people not formally trained in computer science are employed in programming jobs. Although they are able to start programming and coding quickly, it often takes them time to acquire the necessary understanding to gain the requisite skills to become an efficient computer engineer or advanced developer. What You Will Learn The fundamentals of how a computer works The basics of computer programming and programming paradigms How to write efficient programs How the hardware and software work together to provide a good user experience and enhance the usability of the system How computers can talk to each other How to ensure the security of the system The fundamentals of cloud offerings, implications/trade-offs, and deployment/adoption configurations The fundamentals of machine learning Who This Book Is For Computer programmers lacking a formal education in computer science, and anyone with a formal education in computer science, looking to develop a general understanding of computer science fundamentals

This invaluable textbook presents a comprehensive introduction to modern competitive programming. The text highlights how competitive programming has proven to be an excellent way to learn algorithms, by encouraging the design of algorithms that actually work, stimulating the improvement of programming and debugging skills, and reinforcing the type of thinking required to solve problems in a competitive setting. The book contains many “folklore” algorithm design tricks that are known by experienced competitive programmers, yet which have previously only been formally discussed in online forums and blog posts. Topics and features: reviews the features of the C++ programming language, and describes how to create efficient algorithms that can quickly process large data sets; discusses sorting algorithms and binary search, and examines a selection of data structures of the C++ standard library; introduces the algorithm design technique of dynamic programming, and investigates elementary graph algorithms; covers such advanced algorithm design topics as bit-parallelism and amortized analysis, and presents a focus on efficiently processing array range queries; surveys specialized algorithms for trees, and discusses the mathematical topics that are relevant in competitive programming; examines advanced graph techniques, geometric algorithms, and string techniques; describes a selection of more advanced topics, including square root algorithms and dynamic programming optimization. This easy-to-follow guide is an ideal reference for all students wishing to learn algorithms, and practice for programming contests. Knowledge of the basics of programming is assumed, but previous background in algorithm design or programming contests is not necessary. Due to the broad range of topics covered at various levels of difficulty, this book is suitable for both beginners and more experienced readers.

There are many distinct pleasures associated with computer programming. Craftsmanship has its quiet rewards, the satisfaction that comes from building a useful object and making it work. Excitement arrives with the flash of insight that cracks a previously intractable problem. The spiritual quest for elegance can turn the hacker into an artist. There are pleasures in parsimony, in squeezing the last drop of performance out of clever algorithms and tight coding. The games, puzzles, and challenges of problems from international programming competitions are a great way to experience these pleasures while improving your algorithmic and coding skills. This book contains over 100 problems that have appeared in previous programming contests, along with discussions of the theory and ideas necessary to attack them. Instant online grading for all of these problems is available from two WWW robot judging sites. Combining this book with a judge gives an exciting new way to challenge and improve your programming skills. This book can be used for self-study, for teaching innovative courses in algorithms and programming, and in training for international competition. The problems in this book have been selected from over 1,000 programming problems at the Universidad de Valladolid online judge. The judge has ruled on well over one million submissions from 27,000 registered users around the world to date. We have taken only the best of the best, the most fun, exciting, and interesting problems available.

Despite growing interest, basic information on methods and models for mathematically analyzing algorithms has rarely been directly accessible to practitioners, researchers, or students. An Introduction to the Analysis of Algorithms, Second Edition, organizes and presents that knowledge, fully introducing primary techniques and results in the field. Robert Sedgewick and the late Philippe Flajolet have drawn from both classical mathematics and computer science, integrating discrete mathematics, elementary real analysis, combinatorics, algorithms, and data structures. They emphasize the mathematics needed to support scientific studies that can serve as the basis for predicting algorithm performance and for comparing different algorithms on the basis of performance. Techniques covered in the first half of the book include recurrences, generating functions, asymptotics, and analytic combinatorics. Structures studied in the second half of the book include permutations, trees, strings, tries, and mappings. Numerous examples are included throughout to illustrate applications to the analysis of algorithms that are playing a critical role in the evolution of our modern computational infrastructure. Improvements and additions in this new edition include Upgraded figures and code An all-new chapter introducing analytic combinatorics Simplified derivations via analytic combinatorics throughout The book’s thorough, self-contained coverage will help readers appreciate the field’s challenges, prepare them for advanced results—covered in their monograph Analytic Combinatorics and in Donald Knuth’s The Art of Computer Programming books—and provide the background they need to keep abreast of new research. "[Sedgewick and Flajolet] are not only worldwide leaders of the field, they also are masters of exposition. I am sure that every serious computer scientist will find this book rewarding in many ways." —From the Foreword by Donald E. Knuth