Concrete Mathematics: A Foundation for Computer Science


Ronald L. Graham - 1988
    "More concretely," the authors explain, "it is the controlled manipulation of mathematical formulas, using a collection of techniques for solving problems."

Algorithm Design


Jon Kleinberg - 2005
    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.

On LISP: Advanced Techniques for Common LISP


Paul Graham - 1993
    On Lisp explains the reasons behind Lisp's growing popularity as a mainstream programming language. On Lisp is a comprehensive study of advanced Lisp techniques, with bottom-up programming as the unifying theme. It gives the first complete description of macros and macro applications. The book also covers important subjects related to bottom-up programming, including functional programming, rapid prototyping, interactive development, and embedded languages. The final chapter takes a deeper look at object-oriented programming than previous Lisp books, showing the step-by-step construction of a working model of the Common Lisp Object System (CLOS). As well as an indispensable reference, On Lisp is a source of software. Its examples form a library of functions and macros that readers will be able to use in their own Lisp programs.

Game Programming Patterns


Robert Nystrom - 2011
    Commercial game development expert Robert Nystrom presents an array of general solutions to problems encountered in game development. For example, you'll learn how double-buffering enables a player to perceive smooth and realistic motion, and how the service locator pattern can help you provide access to services such as sound without coupling your code to any particular sound driver or sound hardware. Games have much in common with other software, but also a number of unique constraints. Some of the patterns in this book are well-known in other domains of software development. Other of the patterns are unique to gaming. In either case, Robert Nystrom bridges from the ivory tower world of software architecture to the in-the-trenches reality of hardcore game programming. You'll learn the patterns and the general problems that they solve. You'll come away able to apply powerful and reusable architectural solutions that enable you to produce higher quality games with less effort than before. Applies classic design patterns to game programming. Introduces new patterns specific to game programming. Brings abstract software architecture down to Earth with approachable writing and an emphasis on simple code that shows each pattern in practice. What you'll learn Overcome architectural challenges unique to game programming Apply lessons from the larger software world to games. Tie different parts of a game (graphics, sound, AI) into a cohesive whole. Create elegant and maintainable architecture. Achieve good, low-level performance. Gain insight into professional, game development. Who this book is forGame Programming Patterns is aimed at professional game programmers who, while successful in shipping games, are frustrated at how hard it sometimes is to add and modify features when a game is under development. Game Programming Patterns shows how to apply modern software practices to the problem of game development while still maintaining the blazing-fast performance demanded by hard-core gamers. Game Programming Patterns also appeals to those learning about game programming in their spare time. Hobbyists and aspiring professionals alike will find much to learn in this book about pathfinding, collision detection, and other game-programming problem domains.

Data Science from Scratch: First Principles with Python


Joel Grus - 2015
    In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

The Implementation (TCP/IP Illustrated, Volume 2)


Gary R. Wright - 1995
    "TCP/IP Illustrated, Volume 2" contains a thorough explanation of how TCP/IP protocols are implemented. There isn't a more practical or up-to-date bookothis volume is the only one to cover the de facto standard implementation from the 4.4BSD-Lite release, the foundation for TCP/IP implementations run daily on hundreds of thousands of systems worldwide. Combining 500 illustrations with 15,000 lines of real, working code, "TCP/IP Illustrated, Volume 2" uses a teach-by-example approach to help you master TCP/IP implementation. You will learn about such topics as the relationship between the sockets API and the protocol suite, and the differences between a host implementation and a router. In addition, the book covers the newest features of the 4.4BSD-Lite release, including multicasting, long fat pipe support, window scale, timestamp options, and protection against wrapped sequence numbers, and many other topics. Comprehensive in scope, based on a working standard, and thoroughly illustrated, this book is an indispensable resource for anyone working with TCP/IP.

RESTful Web Services


Leonard Richardson - 2007
    But can you also build web sites that are usable by machines? That's where the future lies, and that's what RESTful Web Services shows you how to do. The World Wide Web is the most popular distributed application in history, and Web services and mashups have turned it into a powerful distributed computing platform. But today's web service technologies have lost sight of the simplicity that made the Web successful. They don't work like the Web, and they're missing out on its advantages. This book puts the "Web" back into web services. It shows how you can connect to the programmable web with the technologies you already use every day. The key is REST, the architectural style that drives the Web. This book:Emphasizes the power of basic Web technologies -- the HTTP application protocol, the URI naming standard, and the XML markup language Introduces the Resource-Oriented Architecture (ROA), a common-sense set of rules for designing RESTful web services Shows how a RESTful design is simpler, more versatile, and more scalable than a design based on Remote Procedure Calls (RPC) Includes real-world examples of RESTful web services, like Amazon's Simple Storage Service and the Atom Publishing Protocol Discusses web service clients for popular programming languages Shows how to implement RESTful services in three popular frameworks -- Ruby on Rails, Restlet (for Java), and Django (for Python) Focuses on practical issues: how to design and implement RESTful web services and clients This is the first book that applies the REST design philosophy to real web services. It sets down the best practices you need to make your design a success, and the techniques you need to turn your design into working code. You can harness the power of the Web for programmable applications: you just have to work with the Web instead of against it. This book shows you how.

Terraform: Up & Running: Writing Infrastructure as Code


Yevgeniy Brikman - 2019
    This hands-on second edition, expanded and thoroughly updated for Terraform version 0.12 and beyond, shows you the fastest way to get up and running.Gruntwork cofounder Yevgeniy (Jim) Brikman walks you through code examples that demonstrate Terraform's simple, declarative programming language for deploying and managing infrastructure with a few commands. Veteran sysadmins, DevOps engineers, and novice developers will quickly go from Terraform basics to running a full stack that can support a massive amount of traffic and a large team of developers.Explore changes from Terraform 0.9 through 0.12, including backends, workspaces, and first-class expressionsLearn how to write production-grade Terraform modulesDive into manual and automated testing for Terraform codeCompare Terraform to Chef, Puppet, Ansible, CloudFormation, and Salt StackDeploy server clusters, load balancers, and databasesUse Terraform to manage the state of your infrastructureCreate reusable infrastructure with Terraform modulesUse advanced Terraform syntax to achieve zero-downtime deployment

Lean from the Trenches


Henrik Kniberg - 2011
    Find out how the Swedish police combined XP, Scrum, and Kanban in a 60-person project. From start to finish, you'll see how to deliver a successful product using Lean principles. We start with an organization in desperate need of a new way of doing things and finish with a group of sixty, all working in sync to develop a scalable, complex system. You'll walk through the project step by step, from customer engagement, to the daily "cocktail party," version control, bug tracking, and release. In this honest look at what works--and what doesn't--you'll find out how to: Make quality everyone's business, not just the testers. Keep everyone moving in the same direction without micromanagement. Use simple and powerful metrics to aid in planning and process improvement. Balance between low-level feature focus and high-level system focus. You'll be ready to jump into the trenches and streamline your own development process.ContentsForewordPrefacePART I: HOW WE WORK1. About the Project1.1 Timeline 51.2 How We Sliced the Elephant 61.3 How We Involved the Customer 72. Structuring the Teams3. Attending the Daily Cocktail Party3.1 First Tier: Feature Team Daily Stand-up3.2 Second Tier: Sync Meetings per Specialty3.3 Third Tier: Project Sync Meeting4. The Project Board4.1 Our Cadences4.2 How We Handle Urgent Issues and Impediments5. Scaling the Kanban Boards6. Tracking the High-Level Goal7. Defining Ready and Done7.1 Ready for Development7.2 Ready for System Test7.3 How This Improved Collaboration 8. Handling Tech Stories8.1 Example 1: System Test Bottleneck8.2 Example 2: Day Before the Release8.3 Example 3: The 7-Meter Class9. Handling Bugs9.1 Continuous System Test9.2 Fix the Bugs Immediately9.3 Why We Limit the Number of Bugs in the Bug Tracker9.4 Visualizing Bugs9.5 Preventing Recurring Bugs10. Continuously Improving the Process10.1 Team Retrospectives10.2 Process Improvement Workshops10.3 Managing the Rate of Change11. Managing Work in Progress11.1 Using WIP Limits11.2 Why WIP Limits Apply Only to Features12. Capturing and Using Process Metrics12.1 Velocity (Features per Week)12.2 Why We Don’t Use Story Points12.3 Cycle Time (Weeks per Feature)12.4 Cumulative Flow12.5 Process Cycle Efficiency13. Planning the Sprint and Release13.1 Backlog Grooming13.2 Selecting the Top Ten Features13.3 Why We Moved Backlog Grooming Out of the Sprint Planning Meeting13.4 Planning the Release14. How We Do Version Control14.1 No Junk on the Trunk14.2 Team Branches14.3 System Test Branch15. Why We Use Only Physical Kanban Boards16. What We Learned16.1 Know Your Goal16.2 Experiment16.3 Embrace Failure16.4 Solve Real Problems16.5 Have Dedicated Change Agents16.6 Involve PeoplePART II: A CLOSER LOOK AT THE TECHNIQUES 17. Agile and Lean in a Nutshell17.1 Agile in a Nutshell17.2 Lean in a Nutshell17.3 Scrum in a Nutshell17.4 XP in a Nutshell17.5 Kanban in a Nutshell18. Reducing the Test Automation Backlog18.1 What to Do About It18.2 How to Improve Test Coverage a Little Bit Each Iteration18.3 Step 1: List Your Test Cases18.4 Step 2: Classify Each Test18.5 Step 3: Sort the List in Priority Order18.6 Step 4: Automate a Few Tests Each Iteration18.7 Does This Solve the Problem?19. Sizing the Backlog with Planning Poker19.1 Estimating Without Planning Poker19.2 Estimating with Planning Poker19.3 Special Cards20. Cause-Effect Diagrams20.1 Solve Problems, Not Symptoms20.2 The Lean Problem-Solving Approach: A3 Thinking20.3 How to Use Cause-Effect Diagrams20.4 Example 1: Long Release Cycle20.5 Example 2: Defects Released to Production20.6 Example 3: Lack of Pair Programming20.7 Example 4: Lots of Problems20.8 Practical Issues: How to Create and Maintain the Diagrams20.9 Pitfalls20.10 Why Use Cause-Effect Diagrams?21. Final WordsA1. Glossary: How We Avoid Buzzword BingoIndex