Book Image

Improving your C# Skills

By : Ovais Mehboob Ahmed Khan, John Callaway, Clayton Hunt, Rod Stephens
Book Image

Improving your C# Skills

By: Ovais Mehboob Ahmed Khan, John Callaway, Clayton Hunt, Rod Stephens

Overview of this book

This Learning Path shows you how to create high performing applications and solve programming challenges using a wide range of C# features. You’ll begin by learning how to identify the bottlenecks in writing programs, highlight common performance pitfalls, and apply strategies to detect and resolve these issues early. You'll also study the importance of micro-services architecture for building fast applications and implementing resiliency and security in .NET Core. Then, you'll study the importance of defining and testing boundaries, abstracting away third-party code, and working with different types of test double, such as spies, mocks, and fakes. In addition to describing programming trade-offs, this Learning Path will also help you build a useful toolkit of techniques, including value caching, statistical analysis, and geometric algorithms. This Learning Path includes content from the following Packt products: • C# 7 and .NET Core 2.0 High Performance by Ovais Mehboob Ahmed Khan • Practical Test-Driven Development using C# 7 by John Callaway, Clayton Hunt • The Modern C# Challenge by Rod Stephens
Table of Contents (26 chapters)
Title Page
Copyright and Credits
About Packt
What to Know Before Getting Started
Files and Directories
Advanced C# and .NET Features


Use the following problems to test your geometric programming skills. Give each problem a try before you turn to the solutions and download the example programs. If you have trouble with the graphical part, try to implement the non-graphical pieces. Then, you can download the example solutions and replace the key parts of the program with your code.

1. Monte Carlo π

A Monte Carlo algorithm uses randomness to approximate the solution to a problem. Often, using more random samples gives you a more accurate approximated solution or gives a greater probability that the solution is correct.

For this problem, use a Monte Carlo algorithm to approximate π. To do that, generate random points in the square (0 ≤ X, Y ≤ 1) and then see how many fall within a circle centered in that square.

2. Newton's π

Various mathematicians have developed many different ways to approximate π over the years. Sir Isaac Newton devised the following formula to calculate π:

Use Newton's method to approximate π. Let...