This is a deeply technical book and focuses on the software engineering skills to ace your interview. The book is over 500 pages and includes 150 programming interview questions and answers, as well as other advice.The full list of topics are as follows:The Interview ProcessThis section offers an overview on questions are selected and how you will be evaluated. What happens when you get a question wrong? When should you start preparing, and how? What language should you use? All these questions and more are answered.Behind the ScenesLearn what happens behind the scenes during your interview, how decisions really get made, who you interview with, and what they ask you. Companies covered include Google, Amazon, Yahoo, Microsoft, Apple and Facebook.Special SituationsThis section explains the process for experience candidates, Program Managers, Dev Managers, Testers / SDETs, and more. Learn what your interviewers are looking for and how much code you need to know.Before the InterviewIn order to ace the interview, you first need to get an interview. This section describes what a software engineer's resume should look like and what you should be doing well before your interview.Behavioral PreparationAlthough most of a software engineering interview will be technical, behavioral questions matter too. This section covers how to prepare for behavioral questions and how to give strong, structured responses.Technical Questions (+ 5 Algorithm Approaches)This section covers how to prepare for technical questions (without wasting your time) and teaches actionable ways to solve the trickiest algorithm problems. It also teaches you what exactly "good coding" is when it comes to an interview.150 Programming Questions and AnswersThis section forms the bulk of the book. Each section opens with a discussion of the core knowledge and strategies to tackle this type of question, diving into exactly how you break down and solve it. Topics covered include• Arrays and Strings• Linked Lists• Stacks and Queues• Trees and Graphs• Bit Manipulation• Brain Teasers• Mathematics and Probability• Object-Oriented Design• Recursion and Dynamic Programming• Sorting and Searching• Scalability and Memory Limits• Testing• C and C++• Java• Databases• Threads and LocksFor the widest degree of readability, the solutions are almost entirely written with Java (with the exception of C / C++ questions). A link is provided with the book so that you can download, compile, and play with the solutions yourself.Changes from the Fourth Edition: The fifth edition includes over 200 pages of new content, bringing the book from 300 pages to over 500 pages. Major revisions were done to almost every solution, including a number of alternate solutions added. The introductory chapters were massively expanded, as were the opening of each of the chapters under Technical Questions. In addition, 24 new questions were added.Cracking the Coding Interview, Fifth Edition is the most expansive, detailed guide on how to ace your software development / programming interviews.

    The algorithms you'll use most often as a programmer have already been discovered, tested, and proven. If you want to take a hard pass on Knuth's brilliant but impenetrable theories and the dense multi-page proofs you'll find in most textbooks, this is the book for you. This fully-illustrated and engaging guide makes it easy for you to learn how to use algorithms effectively in your own programs.Grokking Algorithms is a disarming take on a core computer science topic. In it, you'll learn how to apply common algorithms to the practical problems you face in day-to-day life as a programmer. You'll start with problems like sorting and searching. As you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression or artificial intelligence. Whether you're writing business software, video games, mobile apps, or system utilities, you'll learn algorithmic techniques for solving problems that you thought were out of your grasp. For example, you'll be able to:Write a spell checker using graph algorithmsUnderstand how data compression works using Huffman codingIdentify problems that take too long to solve with naive algorithms, and attack them with algorithms that give you an approximate answer insteadEach carefully-presented example includes helpful diagrams and fully-annotated code samples in Python. By the end of this book, you will know some of the most widely applicable algorithms as well as how and when to use them.

    Significant numbers of poorly designed programs have been created by less-experienced developers, resulting in applications that are inefficient and hard to maintain and extend. Increasingly, software system professionals are discovering just how difficult it is to work with these inherited, non-optimal applications. For several years, expert-level object programmers have employed a growing collection of techniques to improve the structural integrity and performance of such existing software programs. Referred to as refactoring, these practices have remained in the domain of experts because no attempt has been made to transcribe the lore into a form that all developers could use... until now. In Refactoring: Improving the Design of Existing Software, renowned object technology mentor Martin Fowler breaks new ground, demystifying these master practices and demonstrating how software practitioners can realize the significant benefits of this new process.

    With this hands-on guide, you'll learn how to write effective, idiomatic Python code by leveraging its best and possibly most neglected features. Author Luciano Ramalho takes you through Python's core language features and libraries, and shows you how to make your code shorter, faster, and more readable at the same time.Many experienced programmers try to bend Python to fit patterns they learned from other languages, and never discover Python features outside of their experience. With this book, those Python programmers will thoroughly learn how to become proficient in Python 3.This book covers:Python data model: understand how special methods are the key to the consistent behavior of objectsData structures: take full advantage of built-in types, and understand the text vs bytes duality in the Unicode ageFunctions as objects: view Python functions as first-class objects, and understand how this affects popular design patternsObject-oriented idioms: build classes by learning about references, mutability, interfaces, operator overloading, and multiple inheritanceControl flow: leverage context managers, generators, coroutines, and concurrency with the concurrent.futures and asyncio packagesMetaprogramming: understand how properties, attribute descriptors, class decorators, and metaclasses work"

    Previously undocumented, these 23 patterns allow designers to create more flexible, elegant, and ultimately reusable designs without having to rediscover the design solutions themselves.The authors begin by describing what patterns are and how they can help you design object-oriented software. They then go on to systematically name, explain, evaluate, and catalog recurring designs in object-oriented systems. With Design Patterns as your guide, you will learn how these important patterns fit into the software development process, and how you can leverage them to solve your own design problems most efficiently. Each pattern describes the circumstances in which it is applicable, when it can be applied in view of other design constraints, and the consequences and trade-offs of using the pattern within a larger design. All patterns are compiled from real systems and are based on real-world examples. Each pattern also includes code that demonstrates how it may be implemented in object-oriented programming languages like C++ or Smalltalk.

    The principal enhancement in Java 8 was the addition of functional programming constructs to Java's object-oriented roots. Java 7, 8, and 9 also introduced language features, such as the try-with-resources statement, the diamond operator for generic types, default and static methods in interfaces, the @SafeVarargs annotation, and modules. New library features include pervasive use of functional interfaces and streams, the java.time package for manipulating dates and times, and numerous minor enhancements such as convenience factory methods for collections. In this new edition of Effective Java, Bloch updates the work to take advantage of these new language and library features, and provides specific best practices for their use. Java's increased support for multiple paradigms increases the need for best-practices advice, and this book delivers. As in previous editions, each chapter consists of several "items," each presented in the form of a short, standalone essay that provides specific advice, insight into Java platform subtleties, and updated code examples. The comprehensive descriptions and explanations for each item illuminate what to do, what not to do, and why. Coverage includes:Updated techniques and best practices on classic topics, including objects, classes, methods, libraries, and generics How to avoid the traps and pitfalls of commonly misunderstood subtleties of the platform Focus on the language and its most fundamental libraries, such as java.lang and java.util

    Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

     At any given moment, somewhere in the world someone struggles with the same software design problems you have. You know you don't want to reinvent the wheel (or worse, a flat tire), so you look to Design Patterns--the lessons learned by those who've faced the same problems. With Design Patterns, you get to take advantage of the best practices and experience of others, so that you can spend your time on...something else. Something more challenging. Something more complex. Something more fun. You want to learn about the patterns that matter--why to use them, when to use them, how to use them (and when NOT to use them). But you don't just want to see how patterns look in a book, you want to know how they look "in the wild". In their native environment. In other words, in real world applications. You also want to learn how patterns are used in the Java API, and how to exploit Java's built-in pattern support in your own code. You want to learn the real OO design principles and why everything your boss told you about inheritance might be wrong (and what to do instead). You want to learn how those principles will help the next time you're up a creek without a design pattern. Most importantly, you want to learn the "secret language" of Design Patterns so that you can hold your own with your co-worker (and impress cocktail party guests) when he casually mentions his stunningly clever use of Command, Facade, Proxy, and Factory in between sips of a martini. You'll easily counter with your deep understanding of why Singleton isn't as simple as it sounds, how the Factory is so often misunderstood, or on the real relationship between Decorator, Facade and Adapter. With Head First Design Patterns, you'll avoid the embarrassment of thinking Decorator is something from the "Trading Spaces" show. Best of all, in a way that won't put you to sleep! We think your time is too important (and too short) to spend it struggling with academic texts. If you've read a Head First book, you know what to expect--a visually rich format designed for the way your brain works. Using the latest research in neurobiology, cognitive science, and learning theory, Head First Design Patterns will load patterns into your brain in a way that sticks. In a way that lets you put them to work immediately. In a way that makes you better at solving software design problems, and better at speaking the language of patterns with others on your team.

    Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords?In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures

    The first edition of this book, Programming Perl, hit the shelves in 1990, and was quickly adopted as the undisputed bible of the language. Since then, Perl has grown with the times, and so has this book.Programming Perl is not just a book about Perl. It is also a unique introduction to the language and its culture, as one might expect only from its authors. Larry Wall is the inventor of Perl, and provides a unique perspective on the evolution of Perl and its future direction. Tom Christiansen was one of the first champions of the language, and lives and breathes the complexities of Perl internals as few other mortals do. Jon Orwant is the editor of The Perl Journal, which has brought together the Perl community as a common forum for new developments in Perl.Any Perl book can show the syntax of Perl's functions, but only this one is a comprehensive guide to all the nooks and crannies of the language. Any Perl book can explain typeglobs, pseudohashes, and closures, but only this one shows how they really work. Any Perl book can say that my is faster than local, but only this one explains why. Any Perl book can have a title, but only this book is affectionately known by all Perl programmers as "The Camel."This third edition of Programming Perl has been expanded to cover version 5.6 of this maturing language. New topics include threading, the compiler, Unicode, and other new features that have been added since the previous edition.

    … The book the National Security Agency wanted never to be published." –Wired Magazine "…monumental… fascinating… comprehensive… the definitive work on cryptography for computer programmers…" –Dr. Dobb's Journal"…easily ranks as one of the most authoritative in its field." —PC Magazine"…the bible of code hackers." –The Millennium Whole Earth CatalogThis new edition of the cryptography classic provides you with a comprehensive survey of modern cryptography. The book details how programmers and electronic communications professionals can use cryptography—the technique of enciphering and deciphering messages-to maintain the privacy of computer data. It describes dozens of cryptography algorithms, gives practical advice on how to implement them into cryptographic software, and shows how they can be used to solve security problems. Covering the latest developments in practical cryptographic techniques, this new edition shows programmers who design computer applications, networks, and storage systems how they can build security into their software and systems. What's new in the Second Edition? * New information on the Clipper Chip, including ways to defeat the key escrow mechanism * New encryption algorithms, including algorithms from the former Soviet Union and South Africa, and the RC4 stream cipher * The latest protocols for digital signatures, authentication, secure elections, digital cash, and more * More detailed information on key management and cryptographic implementations

    But what if you could have your computer do them for you?In "Automate the Boring Stuff with Python," you'll learn how to use Python to write programs that do in minutes what would take you hours to do by hand no prior programming experience required. Once you've mastered the basics of programming, you'll create Python programs that effortlessly perform useful and impressive feats of automation to: Search for text in a file or across multiple filesCreate, update, move, and rename files and foldersSearch the Web and download online contentUpdate and format data in Excel spreadsheets of any sizeSplit, merge, watermark, and encrypt PDFsSend reminder emails and text notificationsFill out online formsStep-by-step instructions walk you through each program, and practice projects at the end of each chapter challenge you to improve those programs and use your newfound skills to automate similar tasks.Don't spend your time doing work a well-trained monkey could do. Even if you've never written a line of code, you can make your computer do the grunt work. Learn how in "Automate the Boring Stuff with Python.""

    However, data structures for these languages do not always translate well to functional languages such as Standard ML, Haskell, or Scheme. This book describes data structures from the point of view of functional languages, with examples, and presents design techniques that allow programmers to develop their own functional data structures. The author includes both classical data structures, such as red-black trees and binomial queues, and a host of new data structures developed exclusively for functional languages. All source code is given in Standard ML and Haskell, and most of the programs are easily adaptable to other functional languages. This handy reference for professional programmers working with functional languages can also be used as a tutorial or for self-study.

    The study of type systems--and of programming languages from a type-theoretic perspective--has important applications in software engineering, language design, high-performance compilers, and security.This text provides a comprehensive introduction both to type systems in computer science and to the basic theory of programming languages. The approach is pragmatic and operational; each new concept is motivated by programming examples and the more theoretical sections are driven by the needs of implementations. Each chapter is accompanied by numerous exercises and solutions, as well as a running implementation, available via the Web. Dependencies between chapters are explicitly identified, allowing readers to choose a variety of paths through the material.The core topics include the untyped lambda-calculus, simple type systems, type reconstruction, universal and existential polymorphism, subtyping, bounded quantification, recursive types, kinds, and type operators. Extended case studies develop a variety of approaches to modeling the features of object-oriented languages.

    The book teaches a range of design and analysis techniques for problems that arise in computing applications. The text encourages an understanding of the algorithm design process and an appreciation of the role of algorithms in the broader field of computer science.