Building on two widely acclaimed previous editions, Craig Larman has updated this book to fully reflect the new UML 2 standard, to help you master the art of object design, and to promote high-impact, iterative, and skillful agile modeling practices.Developers and students will learn object-oriented analysis and design (OOA/D) through three iterations of two cohesive, start-to-finish case studies. These case studies incrementally introduce key skills, essential OO principles and patterns, UML notation, and best practices. You won’t just learn UML diagrams - you’ll learn how to apply UML in the context of OO software development.Drawing on his unsurpassed experience as a mentor and consultant, Larman helps you understand evolutionary requirements and use cases, domain object modeling, responsibility-driven design, essential OO design, layered architectures, “Gang of Four” design patterns, GRASP, iterative methods, an agile approach to the Unified Process (UP), and much more. This edition’s extensive improvements include:- A stronger focus on helping you master OOA/D through case studies that demonstrate key OO principles and patterns, while also applying the UML- New coverage of UML 2, Agile Modeling, Test-Driven Development, and refactoring- Many new tips on combining iterative and evolutionary development with OOA/D- Updates for easier study, including new learning aids and graphics- New college educator teaching resources- Guidance on applying the UP in a light, agile spirit, complementary with other iterative methods such as XP and Scrum- Techniques for applying the UML to documenting architectures- A new chapter on evolutionary requirements, and much moreApplying UML and Patterns, Third Edition, is a lucid and practical introduction to thinking and designing with objects - and creating systems that are well crafted, robust, and maintainable.

    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.

    As a modern application developer you need to understand the emerging field of data management, both RDBMS and NoSQL. Seven Databases in Seven Weeks takes you on a tour of some of the hottest open source databases today. In the tradition of Bruce A. Tate's Seven Languages in Seven Weeks, this book goes beyond your basic tutorial to explore the essential concepts at the core each technology. Redis, Neo4J, CouchDB, MongoDB, HBase, Riak and Postgres. With each database, you'll tackle a real-world data problem that highlights the concepts and features that make it shine. You'll explore the five data models employed by these databases-relational, key/value, columnar, document and graph-and which kinds of problems are best suited to each. You'll learn how MongoDB and CouchDB are strikingly different, and discover the Dynamo heritage at the heart of Riak. Make your applications faster with Redis and more connected with Neo4J. Use MapReduce to solve Big Data problems. Build clusters of servers using scalable services like Amazon's Elastic Compute Cloud (EC2). Discover the CAP theorem and its implications for your distributed data. Understand the tradeoffs between consistency and availability, and when you can use them to your advantage. Use multiple databases in concert to create a platform that's more than the sum of its parts, or find one that meets all your needs at once.Seven Databases in Seven Weeks will take you on a deep dive into each of the databases, their strengths and weaknesses, and how to choose the ones that fit your needs.What You Need: To get the most of of this book you'll have to follow along, and that means you'll need a *nix shell (Mac OSX or Linux preferred, Windows users will need Cygwin), and Java 6 (or greater) and Ruby 1.8.7 (or greater). Each chapter will list the downloads required for that database.

    This book contains the fundamental laws of software development, the primary pieces of understanding that make the difference between a mid-level/junior programmer and the high-level senior software engineer. The book exists to help all programmers understand the process of writing software, on a very fundamental level that can be applied to any programming language or project, from here into eternity. Code Simplicity is also written in such a way that even non-technical managers of software teams can gain an understanding of what the “right way” and the “wrong way” is (and why they are right and wrong) when it comes to software design. The focus of the book is primarily on “software design,” the process of creating a plan for a software project and making technical decisions about the pattern and structure of a system.

    Joining the professional web designers and programmers are new audiences who need to know a little bit of code at work (update a content management system or e-commerce store) and those who want to make their personal blogs more attractive. Many books teaching HTML and CSS are dry and only written for those who want to become programmers, which is why this book takes an entirely new approach. • Introduces HTML and CSS in a way that makes them accessible to everyone—hobbyists, students, and professionals—and it’s full-color throughout • Utilizes information graphics and lifestyle photography to explain the topics in a simple way that is engaging • Boasts a unique structure that allows you to progress through the chapters from beginning to end or just dip into topics of particular interest at your leisureThis educational book is one that you will enjoy picking up, reading, then referring back to. It will make you wish other technical topics were presented in such a simple, attractive and engaging way!

    The authors' enthusiasm for their subject is compelling as they present abstract concepts in a humorous and easy-to-grasp fashion. Together, these books will open new doors of thought to anyone who wants to find out what computing is really about. The Little Schemer introduces computing as an extension of arithmetic and algebra; things that everyone studies in grade school and high school. It introduces programs as recursive functions and briefly discusses the limits of what computers can do. The authors use the programming language Scheme, and interesting foods to illustrate these abstract ideas. The Seasoned Schemer informs the reader about additional dimensions of computing: functions as values, change of state, and exceptional cases. The Little LISPer has been a popular introduction to LISP for many years. It had appeared in French and Japanese. The Little Schemer and The Seasoned Schemer are worthy successors and will prove equally popular as textbooks for Scheme courses as well as companion texts for any complete introductory course in Computer Science.

    Available here:readmeaway.com/download?i=1593279523The Linux Command Line, 2nd Edition: A Complete Introduction PDF by William ShottsRead The Linux Command Line, 2nd Edition: A Complete Introduction PDF from No Starch Press,William ShottsDownload William Shotts’s PDF E-book The Linux Command Line, 2nd Edition: A Complete Introduction

    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.

    Domain-driven design (DDD) combined with functional programming is the innovative combo that will get you there. In this pragmatic, down-to-earth guide, you'll see how applying the core principles of functional programming can result in software designs that model real-world requirements both elegantly and concisely - often more so than an object-oriented approach. Practical examples in the open-source F# functional language, and examples from familiar business domains, show you how to apply these techniques to build software that is business-focused, flexible, and high quality.Domain-driven design is a well-established approach to designing software that ensures that domain experts and developers work together effectively to create high-quality software. This book is the first to combine DDD with techniques from statically typed functional programming. This book is perfect for newcomers to DDD or functional programming - all the techniques you need will be introduced and explained.Model a complex domain accurately using the F# type system, creating compilable code that is also readable documentation---ensuring that the code and design never get out of sync. Encode business rules in the design so that you have "compile-time unit tests," and eliminate many potential bugs by making illegal states unrepresentable. Assemble a series of small, testable functions into a complete use case, and compose these individual scenarios into a large-scale design. Discover why the combination of functional programming and DDD leads naturally to service-oriented and hexagonal architectures. Finally, create a functional domain model that works with traditional databases, NoSQL, and event stores, and safely expose your domain via a website or API.Solve real problems by focusing on real-world requirements for your software.What You Need: The code in this book is designed to be run interactively on Windows, Mac and Linux.You will need a recent version of F# (4.0 or greater), and the appropriate .NET runtime for your platform.Full installation instructions for all platforms at fsharp.org.

    I'm going to share that mindset with you — along with hundreds of actionable techniques and proven habits — so you can shortcut those years.Introducing The Effective Engineer — the only book designed specifically for today's software engineers, based on extensive interviews with engineering leaders at top tech companies, and packed with hundreds of techniques to accelerate your career.For two years, I embarked on a quest seeking an answer to one question:How do the most effective engineers make their efforts, their teams, and their careers more successful?I interviewed and collected stories from engineering VPs, directors, managers, and other leaders at today's top software companies: established, household names like Google, Facebook, Twitter, and LinkedIn; rapidly growing mid-sized companies like Dropbox, Square, Box, Airbnb, and Etsy; and startups like Reddit, Stripe, Instagram, and Lyft.These leaders shared stories about the most valuable insights they've learned and the most common and costly mistakes that they've seen engineers — sometimes themselves — make.This is just a small sampling of the hard questions I posed to them:- What engineering qualities correlate with future success?- What have you done that has paid off the highest returns?- What separates the most effective engineers you've worked with from everyone else?- What's the most valuable lesson your team has learned in the past year?- What advice do you give to new engineers on your team? Everyone's story is different, but many of the lessons share common themes.You'll get to hear stories like:- How did Instagram's team of 5 engineers build and support a service that grew to over 40 million users by the time the company was acquired?- How and why did Quora deploy code to production 40 to 50 times per day?- How did the team behind Google Docs become the fastest acquisition to rewrite its software to run on Google's infrastructure?- How does Etsy use continuous experimentation to design features that are guaranteed to increase revenue at launch?- How did Facebook's small infrastructure team effectively operate thousands of database servers?- How did Dropbox go from barely hiring any new engineers to nearly tripling its team size year-over-year? What's more, I've distilled their stories into actionable habits and lessons that you can follow step-by-step to make your career and your team more successful.The skills used by effective engineers are all learnable.And I'll teach them to you. With The Effective Engineer, I'll teach you a unifying framework called leverage — the value produced per unit of time invested — that you can use to identify the activities that produce disproportionate results.Here's a sneak peek at some of the lessons you'll learn. You'll learn how to:- Prioritize the right projects and tasks to increase your impact.- Earn more leeway from your peers and managers on your projects.- Spend less time maintaining and fixing software and more time building and shipping new features.- Produce more accurate software estimates.- Validate your ideas cheaply to reduce wasted work.- Navigate organizational and people-related bottlenecks.- Find the appropriate level of code reviews, testing, abstraction, and technical debt to balance speed and quality.- Shorten your debugging workflow to increase your iteration speed.

    This book explains the technical aspects of hacking, including stack based overflows, heap based overflows, string exploits, return-into-libc, shellcode, and cryptographic attacks on 802.11b.

    The author's take on the essence of Java as a new programming language and the thorough introduction to Java's features make this a worthwhile tutorial. Thinking in Java begins a little esoterically, with the author's reflections on why Java is new and better. (This book's choice of font for chapter headings is remarkably hard on the eyes.) The author outlines his thoughts on why Java will make you a better programmer, without all the complexity. The book is better when he presents actual language features. There's a tutorial to basic Java types, keywords, and operators. The guide includes extensive source code that is sometimes daunting (as with the author's sample code for all the Java operators in one listing.) As such, this text will be most useful for the experienced developer. The text then moves on to class design issues, when to use inheritance and composition, and related topics of information hiding and polymorphism. (The treatment of inner classes and scoping will likely seem a bit overdone for most readers.) The chapter on Java collection classes for both Java Developer's Kit (JDK) 1.1 and the new classes, such as sets, lists, and maps, are much better. There's material in this chapter that you are unlikely to find anywhere else. Chapters on exception handling and programming with type information are also worthwhile, as are the chapters on the new Swing interface classes and network programming. Although it adopts somewhat of a mixed-bag approach, Thinking in Java contains some excellent material for the object-oriented developer who wants to see what all the fuss is about with Java.

    With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it.Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains:Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details."-- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths."-- Tim Wolters, CTO, Collective Intellect

    An effective testing strategy will deliver new functionality more aggressively, accelerate user feedback, and improve quality. However, for many developers, creating effective automated tests is a unique and unfamiliar challenge. xUnit Test Patterns is the definitive guide to writing automated tests using xUnit, the most popular unit testing framework in use today. Agile coach and test automation expert Gerard Meszaros describes 68 proven patterns for making tests easier to write, understand, and maintain. He then shows you how to make them more robust and repeatable--and far more cost-effective. Loaded with information, this book feels like three books in one. The first part is a detailed tutorial on test automation that covers everything from test strategy to in-depth test coding. The second part, a catalog of 18 frequently encountered "test smells," provides trouble-shooting guidelines to help you determine the root cause of problems and the most applicable patterns. The third part contains detailed descriptions of each pattern, including refactoring instructions illustrated by extensive code samples in multiple programming languages. Topics covered includeWriting better tests--and writing them faster The four phases of automated tests: fixture setup, exercising the system under test, result verification, and fixture teardown Improving test coverage by isolating software from its environment using Test Stubs and Mock Objects Designing software for greater testability Using test "smells" (including code smells, behavior smells, and project smells) to spot problems and know when and how to eliminate them Refactoring tests for greater simplicity, robustness, and execution speed This book will benefit developers, managers, and testers working with any agile or conventional development process, whether doing test-driven development or writing the tests last. While the patterns and smells are especially applicable to all members of the xUnit family, they also apply to next-generation behavior-driven development frameworks such as RSpec and JBehave and to other kinds of test automation tools, including recorded test tools and data-driven test tools such as Fit and FitNesse.Visual Summary of the Pattern Language Foreword Preface Acknowledgments Introduction Refactoring a Test PART I: The Narratives Chapter 1 A Brief Tour Chapter 2 Test Smells Chapter 3 Goals of Test Automation Chapter 4 Philosophy of Test Automation Chapter 5 Principles of Test Automation Chapter 6 Test Automation Strategy Chapter 7 xUnit Basics Chapter 8 Transient Fixture Management Chapter 9 Persistent Fixture Management Chapter 10 Result Verification Chapter 11 Using Test Doubles Chapter 12 Organizing Our Tests Chapter 13 Testing with Databases Chapter 14 A Roadmap to Effective Test Automation PART II: The Test Smells Chapter 15 Code Smells Chapter 16 Behavior Smells Chapter 17 Project Smells PART III: The Patterns Chapter 18 Test Strategy Patterns Chapter 19 xUnit Basics Patterns Chapter 20 Fixture Setup Patterns Chapter 21 Result Verification Patterns Chapter 22 Fixture Teardown Patterns Chapter 23 Test Double Patterns Chapter 24 Test Organization Patterns Chapter 25 Database Patterns Chapter 26 Design-for-Testability Patterns Chapter 27 Value Patterns PART IV: Appendixes Appendix A Test Refactorings Appendix B xUnit Terminology Appendix C xUnit Family Members Appendix D Tools Appendix E Goals and Principles Appendix F Smells, Aliases, and Causes Appendix G Patterns, Aliases, and Variations Glossary References Index "

    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.""