Summary

Concurrency in .NET

teaches you how to build concurrent and scalable programs in .NET using the functional paradigm. This intermediate-level guide is aimed at developers, architects, and passionate computer programmers who are interested in writing code with improved speed and effectiveness by adopting a declarative and pain-free programming style.

About the Technology

Unlock the incredible performance built into your multi-processor machines. Concurrent applications run faster because they spread work across processor cores, performing several tasks at the same time. Modern tools and techniques on the .NET platform, including parallel LINQ, functional programming, asynchronous programming, and the Task Parallel Library, offer powerful alternatives to traditional thread-based concurrency.

About the Book

Concurrency in .NET

teaches you to write code that delivers the speed you need for performance-sensitive applications. Featuring examples in both C# and F#, this book guides you through concurrent and parallel designs that emphasize functional programming in theory and practice. You'll start with the foundations of concurrency and master essential techniques and design practices to optimize code running on modern multiprocessor systems.

What's Inside

The most important concurrency abstractions

Employing the agent programming model

Implementing real-time event-stream processing

Executing unbounded asynchronous operations

Best concurrent practices and patterns that apply to all platforms

About the Reader

For readers skilled with C# or F#.

About the Book

Riccardo Terrell

is a seasoned software engineer and Microsoft MVP who is passionate about functional programming. He has over 20 years' experience delivering cost-effective technology solutions in a competitive business environment.

Table of Contents

PART 1 - Benefits of functional programming applicable to concurrent programs

Functional concurrency foundations

Functional programming techniques for concurrency

Functional data structures and immutability

PART 2 - How to approach the different parts of a concurrent program

The basics of processing big data: data parallelism, part 1

PLINQ and MapReduce: data parallelism, part 2

Real-time event streams: functional reactive programming

Task-based functional parallelism

Task asynchronicity for the win

Asynchronous functional programming in F#

Functional combinators for fluent concurrent programming

Applying reactive programming everywhere with agents

Parallel workflow and agent programming with TPL Dataflow

PART 3 - Modern patterns of concurrent programming applied

Recipes and design patterns for successful concurrent programming

Building a scalable mobile app with concurrent functional programming

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