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This is a quick assessment book / quiz book. It has a vast collection of over 1,100 questions, with answers on Data Structures. Questions have a wide range of difficulty levels and are designed to test a thorough understanding of the topical material. The coverage includes elementary and advanced data structures – Arrays (single/multidimensional); Linked lists (singly–linked, doubly–linked, circular); Stacks; Queues; Heaps; Hash tables; Binary trees; Binary search trees; Balanced trees (AVL trees, Red–Black trees, B–trees/B+ trees); Graphs.
This is a quick assessment book / quiz book. It has a wide variety of over 1,600 questions, with answers on Operating Systems. The questions have a wide range of difficulty levels and are designed to test a thorough understanding of the topical material. The book covers questions on the operating systems structures, fundamentals of processes and threads, CPU scheduling, process synchronization, deadlocks, memory management, I/O subsystem, and mass storage (disk) structures.
This text is intended for a 1-semester CS1 course sequence. The Brief Version contains the first 18 chapters of the Comprehensive Version. The first 13 chapters are appropriate for preparing the AP Computer Science exam. For courses in Java Programming. A fundamentals-first introduction to basic programming concepts and techniques Designed to support an introductory programming course, Introduction to Java Programming and Data Structures teaches concepts of problem-solving and object-orientated programming using a fundamentals-first approach. Beginner programmers learn critical problem-solving techniques then move on to grasp the key concepts of object-oriented, GUI programming, advanced GUI and Web programming using JavaFX. This course approaches Java GUI programming using JavaFX, which has replaced Swing as the new GUI tool for developing cross-platform-rich Internet applications and is simpler to learn and use. The 11th edition has been completely revised to enhance clarity and presentation, and includes new and expanded content, examples, and exercises.
The design and analysis of efficient data structures has long been recognized as a key component of the Computer Science curriculum. Goodrich, Tomassia and Goldwasser's approach to this classic topic is based on the object-oriented paradigm as the framework of choice for the design of data structures. For each ADT presented in the text, the authors provide an associated Java interface. Concrete data structures realizing the ADTs are provided as Java classes implementing the interfaces. The Java code implementing fundamental data structures in this book is organized in a single Java package, net.datastructures. This package forms a coherent library of data structures and algorithms in Java specifically designed for educational purposes in a way that is complimentary with the Java Collections Framework.
Algorithms are a dominant force in modern culture, and every indication is that they will become more pervasive, not less. The best algorithms are undergirded by beautiful mathematics. This text cuts across discipline boundaries to highlight some of the most famous and successful algorithms. Readers are exposed to the principles behind these examples and guided in assembling complex algorithms from simpler building blocks. Written in clear, instructive language within the constraints of mathematical rigor, Algorithms from THE BOOK includes a large number of classroom-tested exercises at the end of each chapter. The appendices cover background material often omitted from undergraduate courses. Most of the algorithm descriptions are accompanied by Julia code, an ideal language for scientific computing. This code is immediately available for experimentation. Algorithms from THE BOOK is aimed at first-year graduate and advanced undergraduate students. It will also serve as a convenient reference for professionals throughout the mathematical sciences, physical sciences, engineering, and the quantitative sectors of the biological and social sciences.
An Essential Reference for Intermediate and Advanced R Programmers Advanced R presents useful tools and techniques for attacking many types of R programming problems, helping you avoid mistakes and dead ends. With more than ten years of experience programming in R, the author illustrates the elegance, beauty, and flexibility at the heart of R. The book develops the necessary skills to produce quality code that can be used in a variety of circumstances. You will learn: The fundamentals of R, including standard data types and functions Functional programming as a useful framework for solving wide classes of problems The positives and negatives of metaprogramming How to write fast, memory-efficient code This book not only helps current R users become R programmers but also shows existing programmers what’s special about R. Intermediate R programmers can dive deeper into R and learn new strategies for solving diverse problems while programmers from other languages can learn the details of R and understand why R works the way it does.
This is a quiz /exercise / self–assessment book. It has a vast collection of questions in Discrete Mathematics. The topical coverage includes: Logic and Proof methods, Sets, Functions, Relations, Properties of integers, Sequences, Induction and Recursion, Basic and advanced counting methods, Discrete probability, Graph theory, Modeling computation, and Boolean algebra.
This book is a self–assessment book / quiz book. It has a vast collection of over 2,500 questions, along with answers. The questions have a wide range of difficulty levels. They have been designed to test a good understanding of the fundamental aspects of the major core areas of Computer Science. The topical coverage includes data representation, digital design, computer organization, software, operating systems, data structures, algorithms, programming languages and compilers, automata, languages, and computation, database systems, computer networks, and computer security.
Now in the 5th edition, Cracking the Coding Interview gives you the interview preparation you need to get the top software developer jobs. This book provides: 150 Programming Interview Questions and Solutions: From binary trees to binary search, this list of 150 questions includes the most common and most useful questions in data structures, algorithms, and knowledge based questions. 5 Algorithm Approaches: Stop being blind-sided by tough algorithm questions, and learn these five approaches to tackle the trickiest problems. Behind the Scenes of the interview processes at Google, Amazon, Microsoft, Facebook, Yahoo, and Apple: Learn what really goes on during your interview day and how decisions get made. Ten Mistakes Candidates Make -- And How to Avoid Them: Don't lose your dream job by making these common mistakes. Learn what many candidates do wrong, and how to avoid these issues. Steps to Prepare for Behavioral and Technical Questions: Stop meandering through an endless set of questions, while missing some of the most important preparation techniques. Follow these steps to more thoroughly prepare in less time.
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