Book Image

Clean Code in C#

By : Jason Alls

Book Image

Clean Code in C#

By: Jason Alls

Overview of this book

Traditionally associated with developing Windows desktop applications and games, C# is now used in a wide variety of domains, such as web and cloud apps, and has become increasingly popular for mobile development. Despite its extensive coding features, professionals experience problems related to efficiency, scalability, and maintainability because of bad code. Clean Code in C# will help you identify these problems and solve them using coding best practices. The book starts with a comparison of good and bad code, helping you understand the importance of coding standards, principles, and methodologies. You’ll then get to grips with code reviews and their role in improving your code while ensuring that you adhere to industry-recognized coding standards. This C# book covers unit testing, delves into test-driven development, and addresses cross-cutting concerns. You’ll explore good programming practices for objects, data structures, exception handling, and other aspects of writing C# computer programs. Once you’ve studied API design and discovered tools for improving code quality, you’ll look at examples of bad code and understand which coding practices you should avoid. By the end of this clean code book, you’ll have the developed skills you need in order to apply industry-approved coding practices to write clean, readable, extendable, and maintainable C# code.

Preface

Who this book is for

What this book covers

To get the most out of this book

Coding Standards and Principles in C#

Coding Standards and Principles in C#

Technical requirements

Good code versus bad code

The need for coding standards, principles, and methodologies

Further reading

Free Chapter

Code Review – Process and Importance

Code Review – Process and Importance

The code review process

Preparing code for review

Leading a code review

Knowing what to review

Knowing when to send code for review

Providing and responding to review feedback

Further reading

Classes, Objects, and Data Structures

Classes, Objects, and Data Structures

Technical requirements

Organizing classes

A class should have only one responsibility

Commenting for documentation generation

Cohesion and coupling

Design for change

The Law of Demeter

Immutable objects and data structures

Objects should hide data and expose methods

Data structures should expose data and have no methods

Further reading

Writing Clean Functions

Writing Clean Functions

Understanding functional programming

Keeping methods small

Avoiding duplication

Avoiding multiple parameters

Further reading

Exception Handling

Exception Handling

Checked and unchecked exceptions

Avoiding NullPointerExceptions

Business rule exceptions

Exceptions should provide meaningful information

Building your own custom exceptions

Further reading

Unit Testing

Technical Requirements

Understanding the reasons for a good test

Understanding the testing tools

TDD methodology practice – fail, pass, and refactor

Removing redundant tests, comments, and dead code

Further reading

End-to-End System Testing

End-to-End System Testing

Dependency injection

Further reading

Threading and Concurrency

Threading and Concurrency

Understanding the thread life cycle

Adding thread parameters

Using a thread pool

Using a mutex with synchronous threads

Working with parallel threads using semaphores

Limiting the number of processors and threads in the thread pool

Preventing deadlocks

Preventing race conditions

Understanding static constructors and methods

Mutability, immutability, and thread safety

Synchronized method dependencies

Using the Interlocked class

General recommendations

Further reading

Designing and Developing APIs

Designing and Developing APIs

Technical requirements

What is an API?

API design guidelines

API design using RAML

Further reading

Securing APIs with API Keys and Azure Key Vault

Securing APIs with API Keys and Azure Key Vault

Technical requirements

Undertaking the API project – dividend calendar

Accessing the Morningstar API

Creating the dividend calendar ASP.NET Core web application in Azure

Using an API key to secure our dividend calendar API

Testing our API key security

Adding the dividend calendar code

Throttling our API

Further reading

Addressing Cross-Cutting Concerns

Addressing Cross-Cutting Concerns

Technical requirements

The decorator pattern

The proxy pattern

AOP with PostSharp

Project – cross-cutting concerns reusable library

Further reading

Using Tools to Improve Code Quality

Using Tools to Improve Code Quality

Technical requirements

Defining good-quality code

Performing code cleanup and calculating code metrics

Performing code analysis

Using quick actions

Using the JetBrains dotTrace profiler

Using JetBrains ReSharper

Using Telerik JustDecompile

Further reading

Refactoring C# Code – Identifying Code Smells

Refactoring C# Code – Identifying Code Smells

Technical requirements

Application-level code smells

Class-level code smells

Method-level smells

Further reading

Refactoring C# Code – Implementing Design Patterns

Refactoring C# Code – Implementing Design Patterns

Technical requirements

Implementing creational design patterns

Implementing structural design patterns

Overview of behavioral design patterns

Further reading

Assessments

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Defining good-quality code

Good code quality is an essential software property. Financial loss, wasted time and effort, and even death can result from poor-quality code. High-standard code will have the qualities of Performance, Availability, Security, Scalability, Maintainability, Accessibility, Deployability, and Extensibility(PASSMADE).

Performant code is small, only does what it needs to do, and is very fast. Performant code will not grind a system to a halt. Things that grind a system to a halt are file input/output (I/O) operations, memory usage, and central processing unit (CPU) usage. Low-performing code is a candidate for refactoring.

Availability refers to the software being continually available at the required level of performance. Availability is the ratio between thetime the software is functional(tsf) to thetotal time it is expected to function(ttef)—for example, tsf=700; ttef =744. 700 / 744 = 0.9409 = 94.09% availability.

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