It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of "data science" for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in in a massive open online course (or MOOC) offered by the pioneering MIT--Harvard collaboration edX.Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. The book does not require knowledge of mathematics beyond high school algebra, but does assume that readers are comfortable with rigorous thinking and not intimidated by mathematical concepts. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming.Introduction to Computation and Programming Using Python can serve as a stepping-stone to more advanced computer science courses, or as a basic grounding in computational problem solving for students in other disciplines.

    The concepts and techniques described are the actual ones used by real game studios like Electronic Arts and Naughty Dog. The examples are often grounded in specific technologies, but the discussion extends way beyond any particular engine or API. The references and citations make it a great jumping off point for those who wish to dig deeper into any particular aspect of the game development process.Intended as the text for a college level series in game programming, this book can also be used by amateur software engineers, hobbyists, self-taught game programmers, and existing members of the game industry. Junior game engineers can use it to solidify their understanding of game technology and engine architecture. Even senior engineers who specialize in one particular field of game development can benefit from the bigger picture presented in these pages.

    Designed for readers who don't need the academic formality, it's a fast and easy computer science guide. It teaches essential concepts for people who want to program computers effectively. First, it introduces discrete mathematics, then it exposes the most common algorithms and data structures. It also shows the principles that make computers and programming languages work.

    Tracy Kidder got a preview of this world in the late 1970s when he observed the engineers of Data General design and build a new 32-bit minicomputer in just one year. His thoughtful, prescient book, The Soul of a New Machine, tells stories of 35-year-old "veteran" engineers hiring recent college graduates and encouraging them to work harder and faster on complex and difficult projects, exploiting the youngsters' ignorance of normal scheduling processes while engendering a new kind of work ethic.These days, we are used to the "total commitment" philosophy of managing technical creation, but Kidder was surprised and even a little alarmed at the obsessions and compulsions he found. From in-house political struggles to workers being permitted to tease management to marathon 24-hour work sessions, The Soul of a New Machine explores concepts that already seem familiar, even old-hat, less than 20 years later. Kidder plainly admires his subjects; while he admits to hopeless confusion about their work, he finds their dedication heroic. The reader wonders, though, what will become of it all, now and in the future. —Rob Lightner

    Weinberg adds new insights and highlights the similarities and differences between now and then. Using a conversational style that invites the reader to join him, Weinberg reunites with some of his most insightful writings on the human side of software engineering.Topics include egoless programming, intelligence, psychological measurement, personality factors, motivation, training, social problems on large projects, problem-solving ability, programming language design, team formation, the programming environment, and much more.Dorset House Publishing is proud to make this important text available to new generations of programmers -- and to encourage readers of the first edition to return to its valuable lessons.

    Written by three prominent members of the Perl community who each have several years of experience teaching Perl around the world, this edition has been updated to account for all the recent changes to the language up to Perl 5.8.Perl is the language for people who want to get work done. It started as a tool for Unix system administrators who needed something powerful for small tasks. Since then, Perl has blossomed into a full-featured programming language used for web programming, database manipulation, XML processing, and system administration--on practically all platforms--while remaining the favorite tool for the small daily tasks it was designed for. You might start using Perl because you need it, but you'll continue to use it because you love it.Informed by their years of success at teaching Perl as consultants, the authors have re-engineered the Llama to better match the pace and scope appropriate for readers getting started with Perl, while retaining the detailed discussion, thorough examples, and eclectic wit for which the Llama is famous.The book includes new exercises and solutions so you can practice what you've learned while it's still fresh in your mind. Here are just some of the topics covered:Perl variable typessubroutinesfile operationsregular expressionstext processingstrings and sortingprocess managementusing third party modulesIf you ask Perl programmers today what book they relied on most when they were learning Perl, you'll find that an overwhelming majority will point to the Llama. With good reason. Other books may teach you to program in Perl, but this book will turn you into a Perl programmer.

    Restructured into six parts, this new edition covers a wide spectrum of software processes from initial requirements solicitation through design and development.

    He needed a way to keep track of software development over time – whatever he was thinking about or working on. He researched subjects he found interesting, then documented his research with a public blog post, which he could easily find and refer to later. Over time, increasing numbers of blog visitors found the posts helpful, relevant and interesting. Now, approximately 100,000 readers visit the blog per day and nearly as many comment and interact on the site.Effective Programming: More Than Writing Code is your one-stop shop for all things programming. Jeff writes with humor and understanding, allowing for both seasoned programmers and newbies to appreciate the depth of his research. From such posts as“The Programmer’s Bill of Rights” and “Why Cant Programmers... Program?” to “Working With the Chaos Monkey,” this book introduces the importance of writing responsible code, the logistics involved, and how people should view it more as a lifestyle than a career.

    The book is broken into two parts, the first deals with security-related reverse engineering and the second explores the more practical aspects of reverse engineering. In addition, the author explains how to reverse engineer a third-party software library to improve interfacing and how to reverse engineer a competitor's software to build a better product. * The first popular book to show how software reverse engineering can help defend against security threats, speed up development, and unlock the secrets of competitive products * Helps developers plug security holes by demonstrating how hackers exploit reverse engineering techniques to crack copy-protection schemes and identify software targets for viruses and other malware * Offers a primer on advanced reverse-engineering, delving into disassembly-code-level reverse engineering-and explaining how to decipher assembly language

    This is one of those cases. The UNIX System Administration Handbook is one of the few books we ever measured ourselves against." -From the Foreword by Tim O'Reilly, founder of O'Reilly Media "This book is fun and functional as a desktop reference. If you use UNIX and Linux systems, you need this book in your short-reach library. It covers a bit of the systems' history but doesn't bloviate. It's just straightfoward information delivered in colorful and memorable fashion." -Jason A. Nunnelley"This is a comprehensive guide to the care and feeding of UNIX and Linux systems. The authors present the facts along with seasoned advice and real-world examples. Their perspective on the variations among systems is valuable for anyone who runs a heterogeneous computing facility." -Pat Parseghian The twentieth anniversary edition of the world's best-selling UNIX system administration book has been made even better by adding coverage of the leading Linux distributions: Ubuntu, openSUSE, and RHEL. This book approaches system administration in a practical way and is an invaluable reference for both new administrators and experienced professionals. It details best practices for every facet of system administration, including storage management, network design and administration, email, web hosting, scripting, software configuration management, performance analysis, Windows interoperability, virtualization, DNS, security, management of IT service organizations, and much more. UNIX(R) and Linux(R) System Administration Handbook, Fourth Edition, reflects the current versions of these operating systems: Ubuntu(R) LinuxopenSUSE(R) LinuxRed Hat(R) Enterprise Linux(R)Oracle America(R) Solaris(TM) (formerly Sun Solaris)HP HP-UX(R)IBM AIX(R)

    Distinct from the details of implementation, algorithm, and data representation, an architecture holds the key to achieving system quality, is a reusable asset that can be applied to subsequent systems, and is crucial to a software organization's business strategy.Drawing on their own extensive experience, the authors cover the essential technical topics for designing, specifying, and validating a system. They also emphasize the importance of the business context in which large systems are designed. Their aim is to present software architecture in a real-world setting, reflecting both the opportunities and constraints that companies encounter. To that end, case studies that describe successful architectures illustrate key points of both technical and organizational discussions.Topics new to this edition include: Architecture design and analysis, including the Architecture Tradeoff Analysis Method (ATAM) Capturing quality requirements and achieving them through quality scenarios and tactics Using architecture reconstruction to recover undocumented architectures Documenting architectures using the Unified Modeling Language (UML) New case studies, including Web-based examples and a wireless Enterprise JavaBeans™ (EJB) system designed to support wearable computers The financial aspects of architectures, including use of the Cost Benefit Analysis Method (CBAM) to make decisions If you design, develop, or manage the building of large software systems (or plan to do so), or if you are interested in acquiring such systems for your corporation or government agency, use Software Architecture in Practice, Second Edition, to get up to speed on the current state of software architecture.

    Many examples are taken from real-world projects. The book focuses on high-level design as well as the gritty details of the Python syntax. The provided exercises inspire the reader to think about his or her own code, rather than providing solved problems. If you're new to Object Oriented Programming techniques, or if you have basic Python skills and wish to learn in depth how and when to correctly apply Object Oriented Programming in Python, this is the book for you. If you are an object-oriented programmer for other languages, you too will find this book a useful introduction to Python, as it uses terminology you are already familiar with. Python 2 programmers seeking a leg up in the new world of Python 3 will also find the book beneficial, and you need not necessarily know Python 2.

    And how to move all of this data becomes nearly as important as the data itself. If you� re an application architect, developer, or production engineer new to Apache Kafka, this practical guide shows you how to use this open source streaming platform to handle real-time data feeds.Engineers from Confluent and LinkedIn who are responsible for developing Kafka explain how to deploy production Kafka clusters, write reliable event-driven microservices, and build scalable stream-processing applications with this platform. Through detailed examples, you� ll learn Kafka� s design principles, reliability guarantees, key APIs, and architecture details, including the replication protocol, the controller, and the storage layer.Understand publish-subscribe messaging and how it fits in the big data ecosystem.Explore Kafka producers and consumers for writing and reading messagesUnderstand Kafka patterns and use-case requirements to ensure reliable data deliveryGet best practices for building data pipelines and applications with KafkaManage Kafka in production, and learn to perform monitoring, tuning, and maintenance tasksLearn the most critical metrics among Kafka� s operational measurementsExplore how Kafka� s stream delivery capabilities make it a perfect source for stream processing systems

    The widespread adoption of agile methods has brought the need for effective testing into the limelight, and agile projects have transformed the role of testers. Much of a tester's function, however, remains largely misunderstood. What is the true role of a tester? Do agile teams actually need members with QA backgrounds? What does it really mean to be an "agile tester?"Two of the industry's most experienced agile testing practitioners and consultants, Lisa Crispin and Janet Gregory, have teamed up to bring you the definitive answers to these questions and many others. In Agile Testing, Crispin and Gregory define agile testing and illustrate the tester's role with examples from real agile teams. They teach you how to use the agile testing quadrants to identify what testing is needed, who should do it, and what tools might help. The book chronicles an agile software development iteration from the viewpoint of a tester and explains the seven key success factors of agile testing.Readers will come away from this book understanding- How to get testers engaged in agile development- Where testers and QA managers fit on an agile team- What to look for when hiring an agile tester- How to transition from a traditional cycle to agile development- How to complete testing activities in short iterations- How to use tests to successfully guide development- How to overcome barriers to test automationThis book is a must for agile testers, agile teams, their managers, and their customers.

    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.