Unless you are careful, a software application quickly becomes difficult to change. We all have had the experience of inheriting an application that someone else has written and being asked to modify it. Think of the fear that strikes your heart just before you make your first change.

In the game of Pick-Up Sticks, you must remove stick after stick from a pile of sticks without disturbing the other sticks. The slightest mistake and the whole pile of sticks might scatter.

Modifying an existing software application is similar to the game of Pick-Up Sticks. You bump the wrong piece of code and you introduce a bug.

Bad software is software that is difficult to change. Robert and Micah Martin describe the markers of bad software as code smells. The following code smells indicate that software is badly written:

Notice that these code smells are all related to change. Each of these code smells is a barrier to change.

Software does not need to be badly written. A software application can be designed from the beginning to survive change.

The best strategy for making software easy to change is to make the components of the application loosely coupled. In a loosely coupled application, you can make a change to one component of an application without making changes to other parts.

Over the years, several principles have emerged for writing good software. These principles enable you to reduce the dependencies between different parts of an application. These software principles have been collected together in the work of Robert Martin (AKA Uncle Bob).

Robert Martin did not invent all the principles; however, he was the first one to gather the principles into a single list. Here is his list of software design principles:

This collection of principles is collectively known by the acronym SOLID. (Yes, SOLID is an acronym of acronyms.)

For example, according to the Single Responsibility Principle, a class should have one, and only one, reason to change. Here’s a concrete example of how this principle is applied: If you know that you might need to modify your application’s validation logic separately from its data access logic, then you should not mix validation and data access logic in the same class.

Software design patterns represent strategies for applying software design principles. In other words, a software design principle is a good idea and a software design pattern is the tool that you use to implement the good idea. (It’s the hammer.)

The idea behind software design patterns was originally promoted by the book Design Patterns: Elements of Reusable Object-Oriented Software. (This book is known as the Gang of Four book.) This book has inspired many other books that describe software design patterns.

The Head First Design Pattern book provides a more user-friendly introduction to the design patterns from the Gang of Four book. The Head First Design book devotes chapters to 14 patterns with names like Observer, Façade, Singleton, and Adaptor.

Another influential book on software design patterns is Martin Fowler’s book Patterns of Enterprise Application Architecture. This book has a companion website that lists the patterns from the book: www.martinfowler.com/eaaCatalog.

Software design patterns provide you with patterns for making your code more resilient to change. For example, in many places in this book, we take advantage of a software design pattern named the Repository pattern. Eric Evans, in his book Domain-Driven Design, describes the Repository pattern like this:

“A REPOSITORY represents all objects of a certain type as a conceptual set (usually emulated). It acts like a collection, except with more elaborate querying capability. Objects of the appropriate type are added and removed, and the machinery behind the REPOSITORY inserts them or deletes them from the database” (see page 151).

According to Evans, one of the major benefits of the Repository pattern is that it enables you to “decouple application and domain design from persistence technology, multiple database strategies, or even multiple data sources.” In other words, the Repository pattern enables you to shield your application from changes in how you perform database access.

For example, when we write our blog application at the end of this book, we take advantage of the Repository pattern to isolate our blog application from a particular persistence technology. The blog application will be designed in such a way that we could switch between different data access technologies such as LINQ to SQL, the Entity Framework, or even NHibernate.

By taking advantage of software design principles and patterns, you can build software that is more resilient to change. Software design patterns are architectural patterns. They focus on the gross architecture of your application.

If you want to make your applications more change proof on a more granular level, then you can build unit tests for your application. A unit test enables you to verify whether a particular method in your application works as you intend it to work.

There are many benefits that result from writing unit tests for your code:

1. Building tests for your code provides you with a safety net for change.
2. Building tests for your code forces you to write loosely coupled code.
3. Building tests for your code forces you to take a user perspective on the code.

First, unit tests provide you with a safety net for change. This is a point that Michael Feathers emphasizes again and again in his book Working Effectively with Legacy Code. In fact, he defines legacy code as “simply code without tests” (see xvi).

When your application code is covered by unit tests, you can modify the code without the fear that the modifications will break the functionality of your code. Unit tests make your code safe to refactor. If you can refactor, then you can modify your code using software design patterns and thus produce better code that is more resilient to change.

Second, writing unit tests for your code forces you to write code in a particular way. Testable code tends to be loosely coupled code. A unit test performs a test on a unit of code in isolation. To build your application so that it is testable, you need to build the application in such a way that it has isolatable components.

One class is loosely coupled to a second class when you can change the first class without changing the second class. Test-driven development often forces you to write loosely coupled code. Loosely coupled code is resistant to change.

Finally, writing unit tests forces you to take a user’s perspective on the code. When writing a unit test, you take on the same perspective as a developer who will use your code in the future. Because writing tests forces you to think about how a developer (perhaps, your future self) will use your code, the code tends to be better designed.

In the previous section, we discussed the importance of building unit tests for your code. Test-driven development is a software design methodology that makes unit tests central to the process of writing software applications. When you practice test-driven development, you write tests first and then write code against the tests.

More precisely, when practicing test-driven development, you complete three steps when creating code (Red/Green/Refactor):

1. Write a unit test that fails (Red).
2. Write code that passes the unit test (Green).
3. Refactor your code (Refactor).

First, you write the unit test. The unit test should express your intention for how you expect your code to behave. When you first create the unit test, the unit test should fail. The test should fail because you have not yet written any application code that satisfies the test.

Next, you write just enough code for the unit test to pass. The goal is to write the code in the laziest, sloppiest, and fastest possible way. You should not waste time thinking about the architecture of your application. Instead, you should focus on writing the minimal amount of code necessary to satisfy the intention expressed by the unit test.

Finally, after you write enough code, you can step back and consider the overall architecture of your application. In this step, you rewrite (refactor) your code by taking advantage of software design patterns—such as the Repository pattern—so that your code is more maintainable. You can fearlessly rewrite your code in this step because your code is covered by unit tests.

There are many benefits that result from practicing test-driven development. First, test-driven development forces you to focus on code that actually needs to be written. Because you are constantly focused on just writing enough code to pass a particular test, you are prevented from wandering into the weeds and writing massive amounts of code that you will never use.

Second, a “test first” design methodology forces you to write code from the perspective of how your code will be used. In other words, when practicing test-driven development, you constant write your tests from a user perspective. Therefore, test-driven development can result in cleaner and more understandable APIs.

Finally, test-driven development forces you to write unit tests as part of the normal process of writing an application. As a project deadline approaches, testing is typically the first thing that goes out the window. When practicing test-driven development, on the other hand, you are more likely to be virtuous about writing unit tests because test-driven development makes unit tests central to the process of building an application.

Building software designed for change requires more upfront effort. Implementing software design principles and patterns takes thought and effort. Writing tests takes time. However, the idea is that the initial effort required to build software the right way will pay huge dividends in the future.

There are two ways to be a developer. You can be a cowboy or you can be a craftsman. A cowboy jumps right in and starts coding. A cowboy can build a software application quickly. The problem with being a cowboy is that software must be maintained over time.

A craftsman is patient. A craftsman builds software carefully by hand. A craftsman is careful to build unit tests that cover all the code in an application. It takes longer for a craftsman to create an application. However, after the application is created, it is easier to fix bugs in the application and add new features to the application.

Most software developers start their programming careers as cowboys. At some point, however, you must hang up your saddle and start building software that can stand the test of time.

Microsoft’s framework for building software applications—any type of application including desktop, web, and console applications—is called the .NET framework. The .NET framework consists of a vast set of classes, tens of thousands of classes, which you can use when building any type of software application. For example, the .NET framework includes classes for working with the file system, accessing a database, using regular expressions, and generating images.

The ASP.NET framework is one part of the .NET framework. The ASP.NET framework is Microsoft’s framework for building web applications. It contains a set of classes that were created specifically to support building web applications. For example, the ASP.NET framework includes classes for implementing web page caching, authentication, and authorization.

Microsoft has two frameworks for building web applications built on top of the ASP.NET framework: ASP.NET Web Forms and ASP.NET MVC (see Figure 1.1).

Figure 1.1. The ASP.NET frameworks

ASP.NET MVC is an alternative to, but not a replacement for, ASP.NET Web Forms. Some developers find the style of programming represented by ASP.NET Web Forms more compelling, and some developers find ASP.NET MVC more compelling. Microsoft continues to make heavy investments in both technologies.

The ASP.NET MVC framework is new; however, the MVC software design pattern itself has a long history. The MVC pattern was invented by Trygve Reenskaug while he was a visiting scientist at the Smalltalk group at the famed Xerox Palo Alto Research Center. He wrote his first paper on MVC in 1978. He originally called it the Thing Model View Editor pattern, but he quickly changed the name of the pattern to the Model View Controller pattern.

The MVC pattern was first implemented as part of the Smalltalk-80 class library. It was originally used as an architectural pattern for creating graphical user interfaces (GUIs).

The meaning of MVC shifted radically when the pattern was adapted to work with web applications. In the context of web applications, the MVC pattern is sometimes referred to as the Model 2 MVC pattern.

The MVC pattern has proven to be very successful. Today, the MVC pattern is used by several popular web application frameworks including Ruby on Rails, Merb, and Django. The MVC pattern is also popular in the Java world. In the Java world, MVC is used in the Struts, Spring, and Tapestry frameworks.

The first major MVC framework for ASP.NET was the open source MonoRail project (see CastleProject.org). There continues to be an active developer community around this project.

The Microsoft ASP.NET MVC framework was originally created by Scott Guthrie on an airplane trip to Austin, Texas, to speak at the first Alt.NET conference in October 2007. (Scott Guthrie was one of the creators of ASP.NET.) Scott Guthrie’s talk generated so much excitement that the ASP.NET MVC framework became an official Microsoft product. ASP.NET MVC 1.0 was released in the first part of 2009.

The ASP.NET MVC framework emphasizes convention over configuration. There are standard locations for each type of file in an ASP.NET MVC project. The ASP.NET MVC application project contains the following folders:

When building an ASP.NET MVC application, you should place controllers only in the Controllers folder, JavaScript scripts only in the Scripts folder, ASP.NET MVC views only in the Views folder, and so on. By following these conventions, your application is more easily maintained, and it can be more easily understood by others.

When you create a new ASP.NET MVC application, you get a simple sample application. You can run this sample application by selecting the menu option Debug, Start Debugging (or press the F5 key).

The first time that you run a new ASP.NET MVC application in Visual Studio, you receive a dialog asking if you want to enable debugging. Simply click the OK button.

When you run the application, your browser opens with the page in Figure 1.5.

Figure 1.5. The sample application

You can use the tabs that appear at the top of the page to navigate to either the Home or the About page. You also can click the Login link to register or log in to the application. And, that is all you can do with the application.

This sample application is implemented with one ASP.NET MVC controller and two ASP.NET MVC views. The sample application does not contain any business or data access logic, so it does not contain any ASP.NET MVC model classes.

The controller is located in the Controllers folder:

(C#)

ControllersHomeController.cs

(VB)

ControllersHomeController.vb

If you open the HomeController in the Code Editor window, you see the file in Listing 1.1.

The file in Listing 1.1 contains a class with two methods named Index() and About(). Methods exposed by a controller are called actions. Both the Index() and About() actions return a view.

When you first run the sample application, the Index() action is invoked and this action returns the Index view. If you click the About tab, the About() action is invoked and this action returns the About view.

The two views can be found in the Views folder at the following location:

ViewsHomeAbout.aspx

ViewsHomeIndex.aspx

The content of the Index view is contained in Listing 1.2.

Notice that a view consists mostly of standard HTML content. For example, the view contains standard <h2> and <p> tags. A view generates a page that is sent to the browser.