.NET | Exercises in .NET with Andras Nemes

Web farms in .NET and IIS part 3: Application Request Routing ARR

June 24, 2013 17 Comments

Introduction

In this post we’ll look at the basics of Application Request Routing. The target audience is beginners who have not worked with ARR before and want to get going with it.

As mentioned in the first post of this series ARR is an extension that can be added to IIS 7.0 and above.

ARR has a lot more available functions than Network Load Balancing (NLB) making it the better load balancing option. However, ARR doesn’t have its own solution for high availability so it cannot handle failures to the server hosting ARR – the result is that the ARR server becomes a single point of failure. This is where NLB enters the scene as it provides high availability – ARR and NLB together make up a very good team.

ARR comes with the following advantages compared to full-blown hardware based load balancers:

Cost: if you have IIS7.0 or above you can install ARR free of charge
Ease of use: this is of course relative, but if you have some basic knowledge of IIS then the learning curve will be minimal
Performance: ARR can handle very large sites with ease – the first resource limit that ARR runs into is network. Most networks support 1 Gbps or more, so this is usually not an issue
Flexibility: ARR offers load balancing based on any server variable, URL, cookie etc.

ARR has some disadvantages:

As mentioned above ARR doesn’t have its own built-in solution for high availability
It does not offer the same range of features as more complete hardware based products. E.g. it lacks SEO treatment and DDoS handling. Some of these shortcomings can be solved with other products, such as NLB or Request Filtering

You can get pretty far with NLB and ARR unless you have some very specialised needs that only expensive commercial products can provide.

ARR is a software based reverse proxy solution – for an explanation of these terms check out the first post in this series. It supports all common load-balancing algorithms, such as server weighting, round-robin etc. The following general list shows the features available in ARR:

Health checking
Caching
Can work as a Content Delivery Network (CDN)
SSL offloading
HTTP compression
URL rewrite
Usage reporting
Sticky sessions
Programming and automation support

ARR only handles HTTP traffic, so it cannot work in conjunction with FTP, RDP etc.

Routing

ARR routing goes through three touchpoints:

IIS site binding: your website will of course need to have a valid URL which we can call the ARR base. It is a site that appears below the Sites node in the IIS manager
URL rewrite rule: this happens at the IIS level
The server farm

When a web request hits the ARR server it is first caught by the IIS binding. A standard binding needs to exist on a website. This is the same process as setting up a new website in IIS under the Sites node. It can be a generic website with no real content – it is only used for the HTTP and HTTPS bindings. Also, it is here where SSL offloading occurs.

The request is then caught by URL Rewrite as long as an appropriate rule exists. This happens at the PreBeginRequest step in the IIS pipeline so it is performed before any other site functionality. URL Rewrite rules can edit server variables as well.

In the last step the server farm gets the request from URL Rewrite. It determines which server to send the request to based on the load balancing algorithm and client affinity settings.

How-to

You can download ARR on your designated routing server using the web platform installer available here. Search for Application Request Routing in the search window of the installer and select the below version:

By the time you read this post there may of course be a new version of the extension.

Click Add and Install in the installer window. The installer will fetch all the dependencies as well.

As in the case of Network Load Balancer I don’t have a private network of Windows servers. Therefore I can show you the steps you need to take in order to create a web farm but will not actually create one in the process.

As soon as you install ARR you will see a new node called Server Farms in the IIS manager:

Right click on that node and select Create Server Farm. The Create Server Farm window will appear where you can add the Server farm name:

You can provide any name here, like in the case of the, but give it some URL-type of name, such as arr.mysite.com. It’s a good idea to provide the same name as the URL for the ARR version of your website. Example: if your website is http://www.fantasticsite.com then the ARR version may well be arr.fantasticsite.com. Click Next to go to the Add Server window:

Here you can add the servers that are the members of the farm. Add the server address one by one in the Server Address textbox and click Add after each entry. The servers you will appear in the list box. Click Finish when you’re done with this step. ARR will then ask you if you want to create any URL rewrite rules:

Click yes. You’ll see that the server farm will appear in the Server Farms list of the IIS manager. Open the Server Farms node, select the name of the farm you’ve just created and you will see some additional setup options:

The default options are sufficient to test the network. Open a web browser and navigate to the ARR name of your website such as arr.mysite.com. The request should be routed to one of the web farm members you specified during the setup.

Let’s look at some of the options in the IIS manager. Clicking on Caching will open the following window:

The default setting is that anything that goes through ARR will be cached for 60 seconds and disk cache is enabled. So if 2 web requests ask for the same resource within a minute ARR will hand back the cached version to the second request without consulting the web tier. You can even set whether the caching mechanism should cache the results by the query string or not. Example: arr.mysite.com?arg=1 and arr.mysite.com?arg=2 will probably return different results from your backend database so it’s a good idea to cache by the query string.

So what is cached? ARR follows the caching rules set out in RFC2616. By default all static content such as css, js etc. is cached.

If your site streams media then checking the Enable request consolidation checkbox can be a good idea. It will consolidate all the streaming requests to reduce the number of requests.

Also, it is recommended to turn off the idle time setting of the application pool:

By default this value is set to 20 minutes. This means that the application pool will enter “sleep” mode if it sits idle, i.e. receives no web request for 20 minutes. Set that value to 0 to turn off this feature, which is recommended anyway, so not only in web farm scenarios. This keeps your site actively running while maintaining the health checking even during quiet times.

ARR can even function as a Content Delivery Network to front entire web farms. Check out the resources on this page for a video user guide.

The Health Test window looks as follows:

Here you can schedule explicit health checks and/or rely on live traffic tests. Live traffic testing watches for errors with the live traffic. If it sees what you define as a failure it marks that server as unhealthy. The main advantage of this method is that is watches for errors with any type of page request not just a single testing URL. The main disadvantage is that if the developers release a bad, untested version of the website then eventually all web farm machines may be turned off as all of them may eventually produce the same error if the same page is requested by the clients. This makes a DoS attack a breeze and even completely innocent clients can break down your site if they hit F5 often enough. Also, if a live traffic test shuts off a web server then that server is not brought back online automatically. Therefore it’s very important that you set up explicit URL testing as well and don’t rely on live tests exclusively.

You can configure live traffic tests as follows:

A comma separated list of failure codes that will cause the web server to be marked as unhealthy. You can even define a range with a hyphen, e.g. 400-500, or mix the styles such as 500, 510-599
The number of maximum failures that must occur during the failover period before the server is marked unhealthy
The failover period in seconds is used along with the maximum failures to determine if there are too many failures during the failover period. If this value is set to 0 then live traffic testing is disabled.

With explicit URL testing you ask ARR to send a request to the web farm members with specific time intervals and inspect the response. You can provide the URL in the URL text box. The test request will be sent to each machine in the farm. It’s highly recommended that you set up explicit URL checks so that unhealthy servers are not allocated any web requests. You can enable explicit URL tests by providing a URL in the appropriate text box. We’ll come back to this type of test a little later, but here are the parameters you can set:

The test URL whose response is inspected by ARR
The time between tests in seconds – if the test fails ARR will continue to send the same request and bring the server back online if the test passes
The timeout in seconds before the health test gives up on a page that takes too long. If ARR receives no response before the timeout then the server is marked as unhealthy.
The Acceptable status codes field works the same way as failure codes in the case of live traffic tests
You can also perform a content match to ensure that a certain word or phrase can be found on the page.

Bear in mind that ARR will mark the server as unhealthy after the very first bad response. Therefore make sure that the testing interval is not too long as even fully functioning and healthy servers may produce bad responses from time to time.

In the bottom of the same window you’ll see another text box where you can define the number of minimum servers. The idea here is that if you know that you need a certain number of healthy servers to reasonably handle the load then the health test shouldn’t allow the server farm to drop below that level. Example: your web farm has 10 machines and you need a minimum of 6 to handle the load on an average day. If the number of healthy servers drops to 5 then it may be a better idea to bring all machines back online again: 5 out of 10 users will receive good experience, so not all visitors will be impacted. The quality level is difficult to predict: your users may see intermittent errors that only occur if their request is directed to one of the bad servers. This is a tradeoff: the web farm will not be rendered completely useless due to overloading but the user experience may not be top class either. If this limit is reached then ARR will ignore all scheduled tests and bring back all servers online again.

The test URL should be a very simple self-contained page: it should not access the database or your application logic. If your database or application layer fails then all the web farm machines will be taken out of action. The ideal test page contains only some static HTML. Make sure that the test page only fails if there’s a problem with the specific server the page is employed on. Otherwise, if the test page fails on every server then the entire web farm will be useless as all servers are brought offline.

You can pick the load balance algorithm in the Load Balance window, meaning how would like to set the rules for web request routing:

The default option is Least current request which is probably the most logical choice. This option means that the web request will be routed to the web farm member that has the least amount of request. Weighted round robin tells ARR to route the requests to each web farm member in turn: first to server 1, then 2 then 3, back to 1, then 2, then 3 etc. regardless of the current load each machine. You can find the explanation of each algorithm in the first post of this series.

If you change the default options you’ll need to select Apply to the right:

The Monitoring and Management window will show you the web request statistics and current health state of each member of the web farm:

You can even get some real time disk cache statistics in the bottom of this window:

Proxy allows us to configure how the packets are forwarded:

Preserving the X-Forwarded-For header can be useful if you want to see which IP the client’s request originated from.

In the Routing Rules window we can set various advanced features.

You can e.g. let the ARR server take care of SSL encryption and decryption by selecting the Enable SSL offloading option which is set by default. Keep in mind that ARR is a reverse proxy load balancer meaning that the web farm servers will see the http request coming from ARR and not from the client. If ARR is responsible to encrypt and decrypt SSL then the web farm will get HTTP requests from ARR even if the original request was sent through HTTPS. If it is critical in your environment that the web farm receives HTTPS requests then a tool called ARR Helper can be something to consider: it digs out the details of the original HTTPS message from the ARR server and writes them back to the original locations thereby fooling the web servers into thinking that the request came from the client in the form of HTTPS. The tool can be downloaded from this link. It comes in two versions: 32bit and 64bit. The tool must be installed on the web servers, not on the ARR machine.

In the Server Affinity window you can set whether you want sticky sessions or not.

The default setting is that there are no sticky sessions. Selecting Client affinity means that the same user will be directed to the same machine during the web session. Session stickiness will be cookie based, you can even set the name of the cookie in the Cookie name text box.

With the web farm and the load balancer in place you can test how ARR behaves if one of the web farm servers is taken out of action. Go to the IIS manager of a server and stop the application pool of the website deployed there:

If you selected the round robin routing algorithm then you will see the following: a normal 200 response from the web server still up and running followed by a 503 from the one you’ve just shut down, then back to healthy server, then again to the inactive one etc. We can set up a status check to avoid this behaviour so that ARR can determine if a web server is healthy before routing any web requests to it.

Go back to ARR and select the Health checks option. Enter a URL which ARR can send requests to. It can be a page dedicated to the health checks, a very simple page with no value to a “real” visitor. Its only reason to exist is to check the state of the web server. How you implement such a logic is up to you, e.g. check if the page can connect to a web service. The outcome of that logic should be a simple boolean value: is this web server in a healthy state or not.

Then you can set the interval for the health checks in seconds:

Note that these checks are real web requests so it creates some additional load on your web site. Therefore make the status URL as lightweight as possible.

Then you can set the upper limit of the response timeout and the acceptable status codes as well. The response match text box has the following purpose: say that your status page writes a specific string in the response if the status is fine, such as “True” or “Success”. You can put that string in this text box. If the response from the status page is different from this string then the machine is deemed unhealthy.

You can test the status response by pressing the Verify URL test button:

If you again turn off the application pool of one of the farm members then you should see that ARR does not route any traffic to that server. Also, the Monitoring and Management window should tell you that the server is not healthy:

High availability for ARR

As mentioned before ARR doesn’t have any built-in high availability feature. If the ARR server is down then the web farm will be unavailable. This doesn’t sound too convincing as one of the reasons we set up web farms is to ensure high availability, right? One solution is to go for a full-blown hardware based commercial load balancer but those typically cost a lot of money. If you are looking for a cheaper alternative then Network Load Balancing (NLB) can be useful. NLB is a load balancer with limited capabilities but can be used together with ARR. NLB must be installed and configured on the web servers of the farm. See the previous post on NLB.

This concludes our discussion on the basics of ARR.

Filed under .NET, Web optimisation Tagged with .net, application request routing, arr, iis, web farm

Web farms in .NET and IIS part 2: Network Load Balancer

June 20, 2013 3 Comments

This post is direct continuation of the post on the general introduction into web farms. We briefly mentioned NLB in the previous post: it performs load balancing by manipulating the MAC address of the network adapters.

This product is in fact not the primary choice for load balancing nowadays. It is very easy to use but it lacks many features that a full blown load balancer has but it has its place, especially in conjunction with Application Request Routing ARR – more on that in the next post.

Web traffic is routed to all servers in the web farm but only one of them will actually respond while the others simply ignore the request. Therefore NLB doesn’t have any load balancing device in front of the web farm – the farm machines work together to “solve an issue”.

Network load balancer

You first need to activate NLB on each machine in the web farm. If you have Windows Server 2008 R2 then in the Start menu select Administrative Tools and then Server Manager. In the Server Manager window select the Features node and click the Add Features menu point in the Action menu. Select NLB in the list that appears:

Click Install and if the installation was successful then you’ll be greeted with the following message:

The NLB manager will then be available through a simple search:

I don’t actually have access to 2 or more private machines with Windows Server installed and I don’t want to misuse my company’s network either for my private blogging purposes so it’s probably best to point you to a video showing how to set up NLB. I’d suggest you to watch the video to get a general idea but make sure you read my comments below before you actually set up the NLB cluster:

How to set up NLB – a Youtube video

Let’s add some information to the setup process:

In the New Cluster: Host Parameters window you can choose the default state of the host when it comes online: started, stopped or suspended. Started is a good option of course. The ‘Retain suspended state after computer restarts’ checkbox is asking you if the host should be put into a suspended state in case it is rebooted. This is an interesting feature: say that you need to update one of the hosts and the updates require a machine restart. You may not want the host to jump back online again as the changes you made may be breaking ones that need to be tested first.

In the same window you can set the priority of the cluster member. Normally the first one you create will have priority 1, the next one will be priority 2 and so on. Keep in mind that the servers normally function as peers to each other so the default 1,2…n increments are fine.

In the New Cluster: Cluster Parameters window you need to select the Cluster operation mode: unicast, multicast or IGMP multicast. Normally it’s going to be unicast but in a virtual environment you’ll probably need to select multicast. If your network supports multicast then either of the multicast types will be the best solution. Make sure to ask your network engineers in the office if you’re not sure which option is applicable to you.

In the same window you can add a Full internet name. This is optional, you can even leave it blank. It gives you an administrative name for the NLB cluster.

In the New Cluster: Port Rules window you can define which ports will be balanced:

Click ‘Edit’ and the Add/Edit Port Rule window will open:

As this is a web farm you may as well choose to load balance port 80 only so set 80 in the From and To port range option:

We are dealing with TCP so you may as well select TCP from the Protocols options:

In the same window you select affinity under the Filtering mode options – this becomes available because we select the Multiple host option as we have 2 hosts as opposed to the Single host option. The choices for affinity are none, single or network. Normally the default choice is None. This means that when a request comes from the certain IP address and we get a new request from the IP address then we don’t care which web server the client is routed to.

This is what you should aim for: no sticky sessions. You can store the session state on a different machine – this is a topic I’ll take up in this series on web farms. Avoiding sticky sessions makes load balancing more effective. With sticky sessions the load balancer is constrained to direct the same user to the same web server even if that server is under heavy load so we lose some of the efficiency of load balancing. The option ‘Single’ means that the user with the same IP address should always be directed to the same machine. The ‘Network’ option is the same as ‘Single’ but for a subgroup of users. This last option is very rarely used.

You can add another Port Rule for SSL: the From and To Port Range options will be set to 443.

All requests coming to a port not defined in this window will be ignored because NLB will not know how to load balance it.

Now you can press finish and the NLB manager will start creating our cluster. You’ll see that the status is Pending at first:

Eventually the status will change to Converged which means we can add a new web server: right click the cluster name, which should be the name you provided in the Full internet name text box, and choose Add Host to Cluster which will lead you through the same windows as when you set up the first node above. Many values such as the port rules will already be populated based on your previous entries. The NLB manager will add this node to the cluster when you’re finished setting it up.

At the end of this process you should see two Converged web farm members in the NLB manager window. You can verify the setup by pinging the name of the cluster you chose in the Full internet name text box. Enter the following in the command prompt: ping
You should see that it answers with the IP of the cluster that you see in the NLB manager, e.g. nlb.mysite.com (123.456.789.10). You can now also navigate to nlb.mysite.com in a web browser and it will probably take you to the first priority web farm member, but this is not for certain: NLB can of course route the request to whichever member in the cluster. In case you set up the system with affinity then you should see that you get to the same cluster member upon subsequent requests.

Keep in mind that NLB has no concept of health checks so it will route to any member of the web farm regardless of the state of the members. Even if a bad server responds with a 503 NLB will not take any note of that and will happily route the request to that machine. This is especially harmful if you’ve set up affinity and the user is always directed to the same machine in the immediate future.

You can easily temporarily remove a cluster member, e.g. if you want to perform some patch on it. Right-click the cluster member node in the NLB manager, click Control Host and select Stop or Drainstop. Stopping means that the node will not accept any connections. Drainstop means that the node will not accept any new connections.

In the above scenario with 2 web farm members stopping one of the two nodes will make NLB route all the web traffic to the one available machine. That’s basically a very simple solution for high availability. NLB handles server failures automatically – when one fails then it does not take part in the decision process on which server should handle the request.

This concludes the introduction to NLB. In the next post we’ll look at ARR.

Filed under .NET, Web optimisation Tagged with .net, iis, network load balancer, nlb, web farm

Design patterns and practices in .NET: the Facade pattern

June 13, 2013 6 Comments

Introduction

Even if you’ve just started learning about patterns chances are the you used the Facade pattern before. You just didn’t know that it had a name.

The main intention of the pattern is to hide a large, complex and possibly poorly written body of code behind a purpose-built interface. The poorly written code obviously wasn’t written by you but by those other baaaad programmers you inherited the code from.

The pattern is often used in conjunction with legacy code – if you want to shield the consumers from the complexities of some old-style spaghetti code you will want to hide its methods behind a simplified interface with a couple of methods. In other words you put a facade in front of the complex code. The interface doesn’t necessary cover all the functionality of the complex code, only the parts that are the most interesting and useful for a consumer. Thus the client code doesn’t need to contact the complex code directly, it will communicate with it through the facade interface.

Another typical scenario is when you reference a large external library with hundreds of methods of which you only need a handful. Instead of making the other developers go through the entire library you can extract the most important functions into an interface that all calling code can use. The fact that a lot larger library sits behind the interface is not important to the caller.

It is perfectly fine to create multiple facades to factor out different chunks of functionality from a large API. The facade will also need to be extended and updated if you wish to expose more of the underlying API.

Demo

We’ll simulate an application which looks up the temperature of our current location using several services. We want to show the temperature in Fahrenheit and Celsius as well.

Start Visual Studio and create a new Console application. We start with the simplest service which is the one that converts Fahrenheit to Celsius. Call this class MetricConverterService:

public class MetricConverterService
{
	public double FarenheitToCelcius(double degrees)
	{
		return ((degrees - 32) / 9.0) * 5.0;
	}
}

Next we’ll need a service that looks up our location based on a zip code:

public class GeoLocService
{
	public Coordinates GetCoordinatesForZipCode(string zipCode)
	{
		return new Coordinates()
		{
			Latitude = 10,
			Longitude = 20
		};
	}

	public string GetCityForZipCode(string zipCode)
	{
		return "Seattle";
	}

	public string GetStateForZipCode(string zipCode)
	{
		return "Washington";
	}
}

I don’t actually know the coordinates of Seattle, but building a true geoloc service is way beyond the scope and true purpose of this post.

The Coordinates class is very simple:

public class Coordinates
{
	public double Latitude { get; set; }
	public double Longitude { get; set; }
}

The WeatherService is also very basic:

public class WeatherService
{
	public double GetTempFarenheit(double latitude, double longitude)
	{
		return 86.5;
	}
}

We return the temperature in F based on the coordinates of the location. We of course ignore the true implementation of such a service.

The first implementation of the calling code in the Main method may look as follows:

static void Main(string[] args)
{
	const string zipCode = "SeattleZipCode";

	GeoLocService geoLookupService = new GeoLocService();

	string city = geoLookupService.GetCityForZipCode(zipCode);
	string state = geoLookupService.GetStateForZipCode(zipCode);
	Coordinates coords = geoLookupService.GetCoordinatesForZipCode(zipCode);

	WeatherService weatherService = new WeatherService();
	double farenheit = weatherService.GetTempFarenheit(coords.Latitude, coords.Longitude);

	MetricConverterService metricConverter = new MetricConverterService();
	double celcius = metricConverter.FarenheitToCelcius(farenheit);

	Console.WriteLine("The current temperature is {0}F/{1}C. in {2}, {3}",
		farenheit.ToString("F1"),
		celcius.ToString("F1"),
		city,
        	state);
        Console.ReadKey();
}

The Main method will use the 3 services we created before to perform its work. We first get back some information from the geoloc service based on the zip code. Then we ask the weather service and the metric converter service to get the temperature at that zip code in both F and C.

Run the application and you’ll see some temperature info in the console.

The Main method has to do a lot of things. Getting the zip code in the beginning and writing out the information at the end are trivial tasks, we don’t need to worry about them. However, the method talks to 3 potentially complicated API:s in between. The services may be dlls we downloaded from NuGet or external web services. The Main method will need to know about all three of these services/libraries to carry out its work. It will also need to know how they work, what parameters they need, in what order they must be called etc. Whereas all we really want is to take a ZIP code and get the temperature with the city and state information. It would be beneficial to hide this complexity behind an easy-to-use class or interface.

Let’s insert a new interface:

public interface ITemperatureService
{
	LocalTemperature GetTemperature(string zipCode);
}

…where the LocalTemperature class looks as follows:

public class LocalTemperature
{
	public double Celcius { get; set; }
	public double Farenheit { get; set; }
	public string City { get; set; }
	public string State { get; set; }
}

The interface represents the ideal way to get all information needed by the Main method. LocalTemperature encapsulates the individual bits of information.

Let’s implement the interface as follows:

public class TemperatureService : ITemperatureService
{
	readonly WeatherService _weatherService;
	readonly GeoLocService _geoLocService;
	readonly MetricConverterService _converter;

        public TemperatureService() : this(new WeatherService(), new GeoLocService(), new MetricConverterService())
	{}

	public TemperatureService(WeatherService weatherService, GeoLocService geoLocService, MetricConverterService converter)
	{
		_weatherService = weatherService;
		_converter = converter;
		_geoLocService = geoLocService;
	}

	public LocalTemperature GetTemperature(string zipCode)
	{
		Coordinates coords = _geoLocService.GetCoordinatesForZipCode(zipCode);
		string city = _geoLocService.GetCityForZipCode(zipCode);
		string state = _geoLocService.GetStateForZipCode(zipCode);

		double farenheit = _weatherService.GetTempFarenheit(coords.Latitude, coords.Longitude);
		double celcius = _converter.FarenheitToCelcius(farenheit);

		LocalTemperature localTemperature = new LocalTemperature()
		{
			Farenheit = farenheit,
			Celcius = celcius,
			City = city,
			State = state
		};

		return localTemperature;
	}
}

This is really nothing else than a refactored version of the API calls in the Main method. The dependencies on the external services have been moved to this temperature service implementation. In a more advanced solution those dependencies would be hidden behind interfaces to avoid the tight coupling between them and the Temperature Service and injected via constructor injection. Note that this class structure is not specific to the Facade pattern, so don’t feel obliged to introduce an empty constructor and an overloaded one etc. The goal is to simplify the usage of those external components from the caller’s point of view.

The revised Main method looks as follows:

static void Main(string[] args)
{
	const string zipCode = "SeattleZipCode";

	ITemperatureService temperatureService = new TemperatureService();
	LocalTemperature localTemp = temperatureService.GetTemperature(zipCode);

	Console.WriteLine("The current temperature is {0}F/{1}C. in {2}, {3}",
						localTemp.Farenheit.ToString("F1"),
						localTemp.Celcius.ToString("F1"),
						localTemp.City,
						localTemp.State);

	Console.ReadKey();
}

I think you agree that this is a lot more streamlined solution. So as you see the facade pattern in this case is equal to some sound refactoring of code. Run the application and you’ll see the same output as before we had the facade in place.

Examples from .NET include File I/O operations such as File.ReadAllText(string filename) and the data access types such as Linq to SQL and the Entity Framework. The tedious operations of opening and closing files and database connections are hidden behind simple methods.

View the list of posts on Architecture and Patterns here.

Filed under .NET, Design patterns Tagged with .net, c#, design pattern, facade

Design patterns and practices in .NET: the Flyweight pattern

June 10, 2013 6 Comments

Introduction

The main intent of the Flyweight pattern is to structure objects so that they can be shared among multiple contexts. It is often mistaken for factories that are responsible for object creation. The structure of the pattern involves a flyweight factory to create the correct implementation of the flyweight interface but they are certainly not the same patterns.

Object oriented programming is considered a blessing by many .NET and Java programmers and by all others that write code in other object oriented languages. However, it has a couple of challenges. Consider a large object domain where you try to model every component as an object. Example: an Excel document has a large amount of cells. Imagine creating a new Cell object when Excel opens – that would create a large amount of identical objects. Another example is a skyscraper with loads of windows. The windows are potentially identical but there may be some variations to them. As soon as you create a skyscraper object your application may need thousands of window objects as well. If you then create a couple more skyscraper objects your application may eat up all the available memory of your machine.

The flyweight pattern can come to the rescue as it helps reduce the storage cost of a large number of objects. It also allows us to share objects across multiple contexts simultaneously.

The pattern lets us achieve these goals by retaining object oriented granularity and flexibility at the same time.

An anti-pattern solution to the skyscraper-window problem would be to build a superobject that incorporates all window types. You may think that the number of objects may be reduced if you create one type of object instead of 2 or more. However, why should that number decrease??? You still have to new up the window objects, right? In addition, such superobjects can quickly become difficult to maintain as you need to accommodate several different types of objects within it and you’ll end up with lots of if statements, possibly nested ones.

The ideal solution in this situation is to create shared objects. Why build 1000 window objects if 1 suffices or at least as few as possible?

The key to creating shared objects is to distinguish between the intrinsic and extrinsic state of an object. The shared objects in the pattern are called Flyweights.

Extrinsic state is supplied to the flyweight from the outside as a parameter when some operation is called on it. This state is not stored inside the flyweight. Example: a Window object may have a Draw operation where the object draws itself. The initial implementation of the Window object may have X and Y co-ordinates plus Width and Height. Those states are contextual can be externalised as parameters to the Draw method: Draw(int x, int y, int width, int height).

Intrinsic state on the other hand is stored inside the flyweight. It does not depend on the context hence it is shareable. The Window object may have a Brush object that is used to draw it. The Brush used to draw the window is the same irrespective of the co-ordinates and size of the window. Thus a single brush can be shared across window objects to draw the windows of the same size.

We still need to make sure that the clients do not end up creating their own flyweights. Even if we implement the extrinsic and intrinsic states everyone is free to create their own copies of the object, right? The answer to that challenge is to use a Flyweight factory. This factory creates and manages flyweights. The client will communicate with the factory if it needs a flyweight. The factory will either provide an existing one or create a new one depending on inputs coming from the client. The client doesn’t care which.

Also, we can have distinct Window objects that are somehow unique among all window objects. There may only be a handful of those on a skyscraper. These may not be shared and they store all their state. These objects are unshared flyweights.

Note however that if the objects must be identified by an ID then this pattern will not be applicable. In other words if you need to distinguish between the second window from the right on the third floor and the sixth window from the left on the fifth floor then you cannot possibly share the objects. In Domain Driven Design such id-less objects are called Value Objects as opposed to Entities that have a unique ID. Value Objects have no ID so it doesn’t make any difference which specific window object you put in which position. If you have such objects in your domain model then they are a good candidate for flyweights.

Demo

In the demo we’ll demonstrate sharing Window objects. Fire up Visual Studio and create a new blank solution. Insert a class library called Domain. Every Window will need to implement the IWindow interface:

public interface IWindow
{
	void Draw(Graphics g, int x, int y, int width, int height);
}

You’ll need to add a reference to the System.Drawing library. Note that we pass in parameters that you may first introduce as object properties: x, y, width, height. These are the parameters that represent the extrinsic state mentioned before. They are computed and supplied by the consumer of the object. They can even be stored in a database table if the Window objects have pre-set sizes which is very likely.

We have the following concrete window types:

public class RedWindow : IWindow
	{
		public static int ObjectCounter = 0;
		Brush paintBrush;

		public RedWindow()
		{
			paintBrush = Brushes.Red;
			ObjectCounter++;
		}

		public void Draw(Graphics g, int x, int y, int width, int height)
		{
			g.FillRectangle(paintBrush, x, y, width, height);
		}
	}

public class BlueWindow : IWindow
	{
		public static int ObjectCounter = 0;

		Brush paintBrush;

		public BlueWindow()
		{
			paintBrush = Brushes.Blue;
			ObjectCounter++;
		}

		public void Draw(Graphics g, int x, int y, int width, int height)
		{
			g.FillRectangle(paintBrush, x, y, width, height);
		}
	}

You’ll see that we have a static object counter. This will help us verify how many objects were really created by the client. The Brush object represents an intrinsic state as mentioned above. It is stored within the object.

The Window objects are built by the WindowFactory:

public class WindowFactory
	{
		static Dictionary<string, IWindow> windows = new Dictionary<string, IWindow>();

		public static IWindow GetWindow(string windowType)
		{
			switch (windowType)
			{
				case "Red":
					if (!windows.ContainsKey("Red"))
						windows["Red"] = new RedWindow();
					return windows["Red"];
				case "Blue":
					if (!windows.ContainsKey("Blue"))
						windows["Blue"] = new BlueWindow();
					return windows["Blue"];
				default:
					break;
			}
			return null;
		}
	}

The client will contact the factory to get hold of a Window object. It will send in a string parameter which describes the type of the window. You’ll note that the factory has a dictionary where it stores the available Window types. This is a tool for the factory to manage the pool of shared tiles. Look at the switch statement: the factory checks if the requested window type is already available in the dictionary using the window type description as the key. If not then it creates a new concrete window and adds it to the dictionary. Finally it returns the correct window object. Note that the factory only creates a new window the first time it is contacted. It returns the existing object on all subsequent requests.

How would a client use this code? Add a new Windows Forms Application called SkyScraper to the solution. Rename Form1 to WindowDemo. Put a label control on the form and name it lblObjectCounter. Put it as far to one of the edges of the form as possible.

We’ll use a random number generator to generate the size parameters of the window objects. We will paint 40 windows on the form: 20 red and 20 blue ones. The total number of objects created should however be 2: one blue and one red. The WindowDemo code behind looks as follows:

public partial class WindowDemo : Form
	{
		Random random = new Random();

		public WindowDemo()
		{
			InitializeComponent();
		}

		protected override void OnPaint(PaintEventArgs e)
		{
			base.OnPaint(e);

			for (int i = 0; i < 20; i++)
			{
				IWindow redWindow = WindowFactory.GetWindow("Red");
				redWindow.Draw(e.Graphics, GetRandomNumber(),
					GetRandomNumber(), GetRandomNumber(), GetRandomNumber());
			}

			for (int i = 0; i < 20; i++)
			{
				IWindow stoneTile = WindowFactory.GetWindow("Blue");
				stoneTile.Draw(e.Graphics, GetRandomNumber(),
					GetRandomNumber(), GetRandomNumber(), GetRandomNumber());
			}

			this.lblObjectCounter.Text = "Total Objects Created : " +
				Convert.ToString(RedWindow.ObjectCounter
				+ BlueWindow.ObjectCounter);
		}

		private int GetRandomNumber()
		{
			return (int)(random.Next(100));
		}       
	}

You’ll need to add a reference to the Domain project.

We’ll paint the Window objects in the overridden OnPaint method. Otherwise the code should be pretty easy to follow. Compile and run the application. You should see red and blue squares painted on the form. The object counter label should say 2 verifying that our flyweight implementation was correct.

Before I close this post try the following bit of code:

string s1 = "flyweight";
string s2 = "flyweight";
bool areEqual = ReferenceEquals(s1, s2);

Can you guess what value areEqual will have? You may think it’s false as s1 and s2 are two different objects and strings are reference types. However, .NET maintains a string pool to manage space and replaces the individual strings to a shared instance.

View the list of posts on Architecture and Patterns here.

Filed under .NET, Design patterns Tagged with .net, c#, design pattern, flyweight

Design patterns and practices in .NET: the Mediator pattern

June 6, 2013 13 Comments

Introduction

The Mediator pattern can be applicable when several objects of a related type need to communicate with each other and this communication is complex. Consider a scenario where incoming aircraft need to carefully communicate with each other for safety reasons. They constantly need to know the position of all other planes, meaning that each aircraft needs to communicate with all other aircraft.

Think of a first naive solution in this case. You have 3 types of aircraft in your domain model: Boeing, Airbus and Fokker. Consider that each type needs to communicate with the other two types. The first approach would be to check the type of the other aircraft directly in code such as this in the Airbus class:

if (otherAircraft is Boeing)
{
    //do something
}
else if (otherAircraft is Fokker)
{
    //do something else
}

You would have similar if-else statements in the other two classes. You can imagine how this gets out of control as we add new types of aircraft. You’ll need to revisit the code of all other types and extend the if-else statements to accommodate the new type thereby violating the open-close design principle. Also, it’s bad practice to let one class intimately know about the inner workings of another class, which is the case here.

We need to decouple the related objects from each other. This is where a Mediator enters the scene. A mediator encapsulates the interaction logic among related objects. The pattern allows loose coupling between objects by keeping them from directly referring to each other explicitly. The interaction logic is centralised in one place only.

The above problem has been solved through air traffic controllers in the real world. It is those professionals that will monitor the position of each aircraft in their zone and communicate with them directly. I don’t know if pilots of different commercial planes directly contact each other but I can imagine that it occurs very rarely. If we applied the same solution in this case then the pilots would need to know if every type of aircraft they may encounter during their flight.

There are a couple of formal elements to the Mediator pattern:

Colleagues: components that need to communicate with each other, very often of the same base type. These objects will have no knowledge of each other but will know about the Mediator component
Mediator: a centralised component that manages communication between the colleagues. The colleagues will have a dependency on this object through an abstraction

Demo

We’ll build on the idea mentioned above: the colleague elements are the incoming aircraft and the mediator is represented by an air traffic controller.

Start up Visual Studio and create a new Console application. Insert a base class for all colleagues called Aircraft:

public abstract class Aircraft
	{
		private readonly IAirTrafficControl _atc;
		private int _currentAltitude;

		protected Aircraft(string callSign, IAirTrafficControl atc)
		{
			_atc = atc;
			CallSign = callSign;
			_atc.RegisterAircraftUnderGuidance(this);
		}

		public abstract int Ceiling { get; }

		public string CallSign { get; private set; }

		public int Altitude
		{
			get { return _currentAltitude; }
			set
			{
				_currentAltitude = value;
				_atc.ReceiveAircraftLocation(this);
			}
		}

		public void Climb(int heightToClimb)
		{
			Altitude += heightToClimb;
		}

		public override bool Equals(object obj)
		{
			if (obj.GetType() != this.GetType()) return false;

			var incoming = (Aircraft)obj;
			return this.CallSign.Equals(incoming.CallSign);
		}

		public override int GetHashCode()
		{
			return CallSign.GetHashCode();
		}

		public void WarnOfAirspaceIntrusionBy(Aircraft reportingAircraft)
		{
			//do something in response to the warning
		}
	}

Every aircraft will have a call sign and a dependency on an air flight controller in the form of the IAirTrafficController interface. We’ll take a look at that interface shortly but you’ll see that we put the aircraft under the responsibility of that air traffic control. We tell the mediator that there’s a new object that it needs to communicate with.

You can imagine that as commercial aircraft fly to their destinations they enter and leave the zones of various air traffic controls on their way. So in a more complete interface would have a de-register method as well but we can omit that to keep the demo simple.

Then comes an abstract property called Ceiling that shows the maximum flying altitude of the aircraft. Each concrete type will need to communicate this property about itself. This is followed by the current Altitude of the aircraft. You’ll see that in the property setter we send the current location to the air traffic controller.

The rest of the class is pretty simple: we let the aircraft climb, we make them comparable and we let them receive a warning signal if there is another aircraft too close.

The IAirTrafficControl interface looks as follows:

public interface IAirTrafficControl
	{
		void ReceiveAircraftLocation(Aircraft location);
		void RegisterAircraftUnderGuidance(Aircraft aircraft);
	}

The type that implements the IAirTrafficControl interface will be responsible to implement these methods. The Aircraft object doesn’t care how its position is registered at the control.

We have the following concrete types of aircraft:

public class Boeing : Aircraft
	{
		public Boeing(string callSign, IAirTrafficControl atc)
			: base(callSign, atc)
		{
		}

		public override int Ceiling
		{
			get { return 33000; }
		}
	}

public class Fokker : Aircraft
	{
		public Fokker(string callSign, IAirTrafficControl atc) : base(callSign, atc)
        {
        }

		public override int Ceiling
		{
			get { return 40000; }
		}
	}

public class Airbus : Aircraft
	{
		public Airbus(string callSign, IAirTrafficControl atc)
			: base(callSign, atc)
		{
		}

		public override int Ceiling
		{
			get { return 40000; }
		}
	}

These should be fairly easy to follow. If you later want to introduce a new type of aircraft just derive from the Aircraft base class and then it will automatically become a colleague component to the existing types. The important thing to note is that in any concrete type there is no reference to any other type. The colleagues are completely independent. That dependency is replaced by the IAirTrafficControl abstraction which is the definition of the mediator. You can imagine that we can pass in different types of air traffic control as the plane flies towards its destination: Stockholm, Copenhagen, Hamburg etc. They may all treat the aircraft in their zones little differently.

Let’s take a look at the concrete mediator:

public class Tower : IAirTrafficControl
	{
		private readonly IList<Aircraft> _aircraftUnderGuidance = new List<Aircraft>();

		public void ReceiveAircraftLocation(Aircraft reportingAircraft)
		{
			foreach (Aircraft currentAircraftUnderGuidance in _aircraftUnderGuidance.
				Where(x => x != reportingAircraft))
			{
				if (Math.Abs(currentAircraftUnderGuidance.Altitude - reportingAircraft.Altitude) < 1000)
				{
					reportingAircraft.Climb(1000);
					//communicate to the class
					currentAircraftUnderGuidance.WarnOfAirspaceIntrusionBy(reportingAircraft);
				}
			}
		}

		public void RegisterAircraftUnderGuidance(Aircraft aircraft)
		{
			if (!_aircraftUnderGuidance.Contains(aircraft))
			{
				_aircraftUnderGuidance.Add(aircraft);
			}
		}
	}

The Tower maintains a list of Aircraft that belong under its control. The list is augmented using the implemented RegisterAircraftUnderGuidance method.

The ReceiveAircraftLocation method includes a bit of logic. When an aircraft reports its position then the Tower loops through the list of aircraft currently under its control – except for the one reporting its position – and if any other plane is within 1000 feet then the reporting aircraft needs to climb 1000 feet and the current aircraft in the loop is warned of another aircraft flying too close. This emergency call is a form of indirect communication between two colleagues: the reporting aircraft communicates tells the other aircraft of the violation of the flying distance. The communication is mediated using the Tower class, the two concrete aircraft still have no knowledge about each other, all communication is handled through abstractions.

Let’s look at the Main method:

static void Main(string[] args)
{
	IAirTrafficControl tower = new Tower();

	Aircraft flight1 = new Airbus("AC159", tower);
	Aircraft flight2 = new Boeing("WS203", tower);
	Aircraft flight3 = new Fokker("AC602", tower);

	flight1.Altitude += 1000;
}

We create a mediator and the aircraft currently flying. That’s all we need to introduce a new aircraft: tell it about the mediator it can use for its communication purposes through its constructor.

The last row says that the Airbus will increase its altitude by 1000 feet. If you recall then the Altitude property setter will initiate a communication with the air traffic control. The aircraft indicates its new altitude and the Tower will loop through the list of aircraft currently under its control and see of any other aircraft object is too close to the reporting one.

The main advantage of the mediator pattern is abstraction: we hide the communicating colleagues from each other and let them talk to each other through another abstraction, i.e. the mediator. An aircraft can only belong to a single mediator and a mediator can have many colleagues under its control, i.e. this is a one-to-many relationship. If we remove the mediator then we’re immediately dealing with a many-to-many relationship among colleagues. If you’re like me then you probably prefer the former type of relationship to the latter.

The disadvantage of the mediator lies in its possible complexity. Our example is still very simple but in real life examples the communication can become very messy with if statements checking the type of the colleague. The mediator can grow very large as more and more communication logic enters the picture. The problem can be mitigated by breaking down the mediator to smaller chunks adhering to the single responsibility principle.

View the list of posts on Architecture and Patterns here.

Filed under .NET, Design patterns Tagged with .net, c#, design pattern, mediator

Design patterns and practices in .NET: the Interpreter pattern

June 3, 2013 5 Comments

Introduction

The Interpreter pattern is somewhat different from the other design patterns. It’s easily overlooked and many find it difficult to understand and apply. Formally the pattern is about handling languages based on a set of rules. So we have a language – any language – and its rules, i.e. the grammar. We also have an interpreter that takes the set of rules to interpret the sentences of the language. You will probably not use this pattern in your everyday programming work – except maybe if you work with robots that need to read some formal representation of an object.

Barcodes are real life examples of the pattern. Barcodes are usually not readable by humans because we don’t know the rules of the barcode language. However, we can take an interpreter, i.e. a barcode reader which will use the barcode rules stored within it to tell us what kind of product we have just bought. The language is represented by the bars of the barcode. The grammar is represented by the numerical values of the bars.

What does all that have to do with programming??? We’ll try to find out.

Demo

Open Visual Studio and create a new Console application. In our demo we’ll simulate a sandwich builder. We’ll create a sandwich language and we want to print the instructions for building the sandwich.

We want to represent a sandwich as follows. We have the top bread and the bottom bread with as many ingredients in between as you like. The ingredients can be condiments such as ketchup or mayo and other ingredients such as ham or vegetables. An additional rule is that the ingredients cannot be applied in any order. We first have one or more condiments, then some ‘normal’ ingredients such as chicken, followed by some more condiments.

We will have the following spices: mayo, mustard and ketchup. Ingredients include lettuce, tomato and chicken. Bread can be either white bread or wheat bread. The ingredients are grouped into a condiment list and an ingredient list. Each list can contain 0 or more elements. In an extreme case we can have a very plain sandwich with only the top and bottom bread.

The goal is to give instructions to a machine which will build sandwiches for us. We won’t go overboard with our notations so that the result can be understood by a human, but you can replace the ingredients and bread types with any symbol you like.

The ingredients of our sandwich – bread, condiment, etc. – and the sandwich itself are the sentences or expressions in our sandwich language. This will be the first element in our programme, the IExpression interface:

public interface IExpression
	{
		void Interpret(Context context);
	}

Each expression has a meaning so it can be interpreted, hence the Interpret method. The sandwich means something. The list of condiments and ingredients mean something, they are all expressions. In order to understand the meaning of a sandwich we need to know the meaning of each ingredient and condiment. The Context class represents the context within which the Expression is interpreted. In this case it’s a very simple class:

public class Context
	{
		public string Output { get; set; }
	}

We only use the context for our output.

Each condiment implements the ICondiment interface which is extremely simple:

public interface ICondiment : IExpression { }

Each ingredient implements the IIngredient interface which again is very simple:

public interface IIngredient : IExpression{}

Here come the condiment types, they should be easy to follow. The Interpret method appends the name of the condiment to the string output in each case. This is possible as a single condiment doesn’t have any children so it can interpret itself:

public class KetchupCondiment : ICondiment
	{
		public void Interpret(Context context)
		{
			context.Output += string.Format(" {0} ", "Ketchup");
		}
	}

public class MayoCondiment : ICondiment
	{
		public void Interpret(Context context)
		{
			context.Output += string.Format(" {0} ", "Mayo");
		}
	}

public class MustardCondiment : ICondiment
	{
		public void Interpret(Context context)
		{
			context.Output += string.Format(" {0} ", "Mustard");
		}
	}

The condiments are grouped in a Condiment list:

public class CondimentList : IExpression
	{
		private readonly List<ICondiment> condiments;

		public CondimentList(List<ICondiment> condiments)
		{
			this.condiments = condiments;
		}

		public void Interpret(Context context)
		{
			foreach (ICondiment condiment in condiments)
				condiment.Interpret(context);
		}
	}

The Interpret method simply iterates through the members of the Condiment list and calls the interpret method on each.

Here come the ingredients which implement the Interpret method the same way:

public class LettuceIngredient : IIngredient
	{
		public void Interpret(Context context)
		{
			context.Output += string.Format(" {0} ", "Lettuce");
		}
	}

public class ChickenIngredient : IIngredient
	{
		public void Interpret(Context context)
		{
			context.Output += string.Format(" {0} ", "Chicken");
		}
	}

The ingredients are also grouped into an ingredient list:

public class IngredientList : IExpression
	{
		private readonly List<IIngredient> ingredients;

		public IngredientList(List<IIngredient> ingredients)
		{
			this.ingredients = ingredients;
		}

		public void Interpret(Context context)
		{
			foreach (IIngredient ingredient in ingredients)
				ingredient.Interpret(context);
		}
	}

Now all we need is to represent the bread somehow:

public interface IBread : IExpression{}

Here come the bread types:

public class WheatBread : IBread
	{
		public void Interpret(Context context)
		{
			context.Output += string.Format(" {0} ", "Wheat-Bread");
		}
	}

public class WhiteBread : IBread
	{
		public void Interpret(Context context)
		{
			context.Output += string.Format(" {0} ", "White-Bread");
		}
	}

Now we have all the elements ready to build our Sandwich class:

public class Sandwhich : IExpression
	{
		private readonly IBread topBread;
		private readonly CondimentList topCondiments;
		private readonly IngredientList ingredients;
		private readonly CondimentList bottomCondiments;
		private readonly IBread bottomBread;

		public Sandwhich(IBread topBread, CondimentList topCondiments, IngredientList ingredients, CondimentList bottomCondiments, IBread bottomBread)
		{
			this.topBread = topBread;
			this.topCondiments = topCondiments;
			this.ingredients = ingredients;
			this.bottomCondiments = bottomCondiments;
			this.bottomBread = bottomBread;
		}

		public void Interpret(Context context)
		{
			context.Output += "|";
			topBread.Interpret(context);
			context.Output += "|";
			context.Output += "<--";
			topCondiments.Interpret(context);
			context.Output += "-";
			ingredients.Interpret(context);
			context.Output += "-";
			bottomCondiments.Interpret(context);
			context.Output += "-->";
			context.Output += "|";
			bottomBread.Interpret(context);
			context.Output += "|";
			Console.WriteLine(context.Output);
		}
	}

We build the sandwich using the 5 objects in the constructor: the top bread, top condiments, ingredients in the middle, bottom condiments and finally the bottom bread. The Interpret method builds our sandwich machine language:

We start with a delimiter ‘|’
Followed by the top bread interpretation
Then comes the bread delimiter again ‘|’
“<–"; indicates the start of the things in the sandwich
Then come the top condiments interpretation
Followed by a ‘-‘ delimiter
Ingredients
Againt followed by the ‘-‘ delimiter
Bottom condiments
The sandwich filling is then closed with “–>”
The bottom bread is surrounded by pipe characters like the top bread

Note that every element in the sandwich, including the sandwich itself, can interpret itself. This is of course due to the fact that every element here is an expression, a sentence that has a meaning and can be interpreted.

The Interpret method in each implementation builds up the grammar of our sandwich language. The ultimate Interpret method in the Sandwich class builds up the sentences in sandwich language according to the rules of that grammar. We let each expression interpret itself – it is a lot easier to let each element do it instead of going through some complicated string operation and if-else statements trying build up our sentences. Not just that – we built our object model with our domain knowledge in mind so the solution is a lot more object oriented and reflects our business logic.

Let’s see how this can be used by a client. Let’s insert the following in the Main method:

class Program
	{
		static void Main(string[] args)
		{
			Sandwhich sandwhich = new Sandwhich(
				new WheatBread(),
				new CondimentList(
					new List<ICondiment> { new MayoCondiment(), new MustardCondiment() }),
				new IngredientList(
					new List<IIngredient> { new LettuceIngredient(), new ChickenIngredient() }),
				new CondimentList(new List<ICondiment> { new KetchupCondiment() }),
				new WheatBread());

			sandwhich.Interpret(new Context());


			Console.ReadKey();
		}
	}

We build a sandwich using the Sandwich constructor where we pass in each element of the sandwich. As the sandwich itself is also an expression we can call its interpret method to output the representation of the sandwich.

Run the application and you’ll see our beautiful instructions to build a sandwich. Feel free to change the ingredients and check the output in the console.

View the list of posts on Architecture and Patterns here.

Filed under .NET, Design patterns Tagged with .net, c#, design pattern, interpreter

Design patterns and practices in .NET: the Composite pattern

May 30, 2013 3 Comments

Introduction

The Composite pattern deals with putting individual objects together to form a whole. In mathematics the relationship between the objects and the composite object they build can be described by a part-whole hierarchy. The ingredient objects are the parts and the composite is the whole.

In essence we build up a tree – a composite – that consists of one or more children – the leaves. The client calling upon the composite should be able to treat the individual parts of the whole in a uniform way.

A real life example is sending emails. If you want to send an email to all developers in your organisation one option is that you type in the names of each developer in the ‘to’ field. This is of course not efficient. Fortunately we can construct recipient groups, such as Developers. If you then also want to send the email to another person outside the Developers group you can simply put their name in the ‘to’ box along with Developers. We treat both the group and the individual emails in a uniform way. We can insert both groups and individual emails in the ‘to’ box. We rely on the email engine to take the group apart and send the email to each recipient in that group. We don’t really care how it’s done – apart from a couple network geeks I guess.

Demo

We will first build a demo application that does not use the pattern and then we’ll refactor it. We’ll simulate a game where play money is split among the players in a group if they manage to kill a monster.

Start up Visual Studio and create a new console application. Insert a new class called Player:

public class Player
	{
		public string Name { get; set; }
		public int Gold { get; set; }

		public void Stats()
		{
			Console.WriteLine("{0} has {1} coins.", Name, Gold);
		}
	}

This is easy to follow I believe. A group of players is represented by the Group class:

public class Group
	{
		public string Name { get; set; }
		public List<Player> Members { get; set; }

		public Group()
		{
			Members = new List<Player>();
		}
	}

The money splitting mechanism is run in the Main method as follows:

static void Main(string[] args)
{
	int goldForKill = 1023;
	Console.WriteLine("You have killed the Monster and gained {0} coins!", goldForKill);

	Player andy = new Player { Name = "Andy" };
	Player jane = new Player { Name = "Jane" };
	Player eve = new Player { Name = "Eve" };
	Player ann = new Player { Name = "Ann" };
	Player edith = new Player { Name = "Edith" };
	Group developers = new Group { Name = "Developers", Members = { andy, jane, eve } };

	List<Player> individuals = new List<Player> { ann, edith };
	List<Group> groups = new List<Group> { developers };

	double totalToSplitBy = individuals.Count + groups.Count;
	double amountForEach = goldForKill / totalToSplitBy;
	int leftOver = goldForKill % totalToSplitBy;

	foreach (Player individual in individuals)
	{
		individual.Gold += amountForEach + leftOver;
		leftOver = 0;
		individual.Stats();
	}

	foreach (Group group in groups)
	{
		double amountForEachGroupMember = amountForEach / group.Members.Count;
		int leftOverForGroup = amountForEachGroupMember % group.Members.Count;
		foreach (Player member in group.Members)
		{
			member.Gold += amountForEachGroupMember + leftOverForGroup;
			leftOverForGroup = 0;
			member.Stats();
		}
	}

	Console.ReadKey();
}

So our brilliant game starts off where the monster was killed and we’re ready to hand out the reward among the players. We have 5 players. Three of them make up a group and the other two make up a list of individual players. We’re then ready to split the gold among the participants where the group is counted as one unit i.e. we have 3 elements: the two individual players and the Developer group. Then we go through each individual and give them their share. We do the same to each group as well where we also divide the group’s share among the individuals within that group.

Build and run the application and you’ll see in the console that the 1023 pieces of gold was divided up. The code works but it’s definitely quite messy. Keep in mind that our tree hierarchy is very simple: we can have individuals and groups. Think of a more complicated scenario: within the Developers group we can have subgroups, such as .NET developers, Java developers who are further subdivided into web and desktop developers and even individuals that do not fit into any group. In the code we iterate through the individuals and the groups manually. We also iterate the players in the group. Imagine that we’d have to iterate through the subgroups of the subgroups of the group if we are facing a deeper hierarchy. The foreach loop would keep growing and the splitting logic would become very challenging to maintain.

So let’s refactor the code. The composite pattern states that the client should be able to treat the individual part and the whole in a uniform way. Thus the first step is to make the Person and the Group class uniform in some way. As it turns out the logical way to do this is that both classes implement an interface that the client can communicate with. So the client won’t deal with groups and individuals but with a uniform object, such as Participant.

Insert an interface called IParticipant:

public interface IParticipant
{
	int Gold { get; set; }
	void Stats();
}

Every participant of the game will have some gold and will be able to write out the current statistics regardless of them being individuals or groups. We let Player and Group implement the interface:

public class Player : IParticipant
	{
		public string Name { get; set; }
		public int Gold { get; set; }

		public void Stats()
		{
			Console.WriteLine("{0} has {1} coins.", Name, Gold);
		}
	}

The Player class implements the interface without changes in its body.

The Group class will encapsulate the gold sharing logic we saw in the Main method above:

public class Group : IParticipant
	{
		public string Name { get; set; }
		public List<IParticipant> Members { get; set; }

		public Group()
		{
			Members = new List<IParticipant>();
		}

		public int Gold
		{
			get
			{
				int totalGold = 0;
				foreach (IParticipant member in Members)
				{
					totalGold += member.Gold;
				}

				return totalGold;
			}
			set
			{
				double eachSplit = value / Members.Count;
				int leftOver = value % Members.Count;
				foreach (IParticipant member in Members)
				{
					member.Gold += eachSplit + leftOver;
					leftOver = 0;
				}
			}
		}

		public void Stats()
		{
			foreach (IParticipant member in Members)
			{
				member.Stats();
			}
		}
	}

In the Gold property getter we simply loop through the group members and add up their amount of gold. In the setter we split up the total amount of gold among the group members. Note also that Group can have a list of IParticipant objects representing either individual players or subgroups. You can imagine that those subgroups in turn can also have subgroups so the setters and getters will automatically collect the information from the nested members as well. The leftover variable is set to 0 as the first member will be given all the left over, we don’t care about such details.

In the Stats method we simply call the statistics of each group member – again group members can be individuals and subgroups. If it’s a subgroup then the Stats method of the members of the subgroup will automatically be called.

The modified Main method looks as follows:

static void Main(string[] args)
{
	int goldForKill = 1023;
	Console.WriteLine("You have killed the Monster and gained {0} coins!", goldForKill);

	IParticipant andy = new Player { Name = "Andy" };
	IParticipant jane = new Player { Name = "Jane" };
	IParticipant eve = new Player { Name = "Eve" };
	IParticipant ann = new Player { Name = "Ann" };
	IParticipant edith = new Player { Name = "Edith" };
	IParticipant oldBob = new Player { Name = "Old Bob" };
	IParticipant newBob = new Player { Name = "New Bob" };
	IParticipant bobs = new Group { Members = { oldBob, newBob } };
	IParticipant developers = new Group { Name = "Developers", Members = { andy, jane, eve, bobs } };

	IParticipant participants = new Group { Members = { developers, ann, edith } };
	participants.Gold += goldForKill;
	participants.Stats();

	Console.ReadKey();
}

You can see that the client, i.e. the Main method calls the methods of IParticipant where IParticipant can be an individual, a group or a group within a group. When we set the level gold through the Gold property the gold distribution logic of each concrete type is called which even takes care of sharing the gold among the groups within a group. The participants variable includes all members of the game.

The main advantage of this pattern is that now the tree structure can be as deep as you can imagine and you don’t have to change the logic within the Player and Group classes. Also, we contain the differences between a leaf and a group in the Player and Group classes separately. In addition, they can also tested independently.

Build and run the project and you should see the amount of gold split among all participants of the game.

View the list of posts on Architecture and Patterns here.

Filed under .NET, Design patterns Tagged with .net, c#, composite, design pattern

Design patterns and practices in .NET: the Chain of Responsibility pattern

May 23, 2013 11 Comments

Introduction

The Chain of Responsibility is an ordered chain of message handlers that can process a specific type of message or pass the message to the next handler in the chain. This pattern revolves around messaging between a sender and one more receivers. This probably sounds very cryptic – just like the basic description of design patterns in general – so let’s see a quick example in words.

Suppose we have a Sender that knows the first receiver in the messaging chain, call it Receiver A. Receiver A is in turn aware of Receiver B and so on. When a message comes in to a sender we can only perform one thing: pass it along to the first receiver. Receiver A inspects the message and decides whether it can process it or not. If not then it passes the message along to Receiver B and Receiver B will perform the same message inspection as Receiver A. It then decides to either process the Message or send it further down the messaging chain. If it processes the message then it will send a Response back to the Sender.

In this example the Sender sent a message to the first Receiver and received a Response from a different one. However, the Sender is not aware of Receiver B. If the messaging stops at Receiver B then Receiver C remained completely inactive: it has no knowledge of the Message and that the messaging actually occurred.

The example also showcases the traits of the pattern:

The Sender is only aware of the first receiver
Each receiver only knows of the next receiver down the messaging chain
Receivers can process the Message or send it down the chain
The Sender will have no knowledge about which Receiver received the message
The first receiver that was able to process the message terminates the chain
The order of the receiver list matters

Demo

In the demo we’ll simulate the hierarchy of a company: an employee would like to make a large expenditure so he asks his manager. The manager is not entitled to approve the large sum and sends the request forward to the VP. The VP is not entitled either to approve the request so sends it to the President. The President is the highest authority in the hierarchy who will either approve or disapprove the request and sends the response back to the original employee.

Open Visual Studio and create a blank solution. Insert a class library called Domain. You can remove Class1.cs. We’ll build up the components one by one. We’ll start with the abstraction for an expense report, IExpenseReport:

public interface IExpenseReport
    {
        Decimal Total { get; }
    }

An expense report can thus have a total sum.

The IExpenseApprover interface represents any object that is entitled to approve expense reports:

public interface IExpenseApprover
	{
		ApprovalResponse ApproveExpense(IExpenseReport expenseReport);
	}

…where ApprovalResponse is an enumeration:

public enum ApprovalResponse
	{
		Denied,
		Approved,
		BeyondApprovalLimit,
	}

The concrete implementation of the IExpenseReport is very straightforward:

public class ExpenseReport : IExpenseReport
	{
		public ExpenseReport(Decimal total)
		{
			Total = total;
		}

		public decimal Total
		{
			get;
			private set;
		}
	}

The Employee class implements the IExpenseApprover interface:

public class Employee : IExpenseApprover
	{
		public Employee(string name, Decimal approvalLimit)
		{
			Name = name;
			_approvalLimit = approvalLimit;
		}

		public string Name { get; private set; }

		public ApprovalResponse ApproveExpense(IExpenseReport expenseReport)
		{
			return expenseReport.Total > _approvalLimit
					? ApprovalResponse.BeyondApprovalLimit
					: ApprovalResponse.Approved;
		}

		private readonly Decimal _approvalLimit;
	}

As you see the constructor needs a name and an approval limit. The implemented ApproveExpense method simply checks if the total value of the expense report is above or below the approval limit. If total is lower than the limit, then the expense is approved, otherwise the method indicates that the total is too much for the employee to approve.

Add a Console application called Approval to the solution and add a reference to the Domain library. We’ll first check how the approval process may look like without the pattern applied:

static void Main(string[] args)
		{
			List<Employee> managers = new List<Employee>
                                          {
                                              new Employee("William Worker", Decimal.Zero),
                                              new Employee("Mary Manager", new Decimal(1000)),
                                              new Employee("Victor Vicepres", new Decimal(5000)),
                                              new Employee("Paula President", new Decimal(20000)),
                                          };

			Decimal expenseReportAmount;
			while (ConsoleInput.TryReadDecimal("Expense report amount:", out expenseReportAmount))
			{
				IExpenseReport expense = new ExpenseReport(expenseReportAmount);

				bool expenseProcessed = false;

				foreach (Employee approver in managers)
				{
					ApprovalResponse response = approver.ApproveExpense(expense);

					if (response != ApprovalResponse.BeyondApprovalLimit)
					{
						Console.WriteLine("The request was {0}.", response);
						expenseProcessed = true;
						break;
					}
				}

				if (!expenseProcessed)
				{
					Console.WriteLine("No one was able to approve your expense.");
				}
			}
		}

…where ConsoleInput is a helper class that looks as follows:

public static class ConsoleInput
	{
		public static bool TryReadDecimal(string prompt, out Decimal value)
		{
			value = default(Decimal);

			while (true)
			{
				Console.WriteLine(prompt);
				string input = Console.ReadLine();

				if (string.IsNullOrEmpty(input))
				{
					return false;
				}

				try
				{
					value = Convert.ToDecimal(input);
					return true;
				}
				catch (FormatException)
				{
					Console.WriteLine("The input is not a valid decimal.");
				}
				catch (OverflowException)
				{
					Console.WriteLine("The input is not a valid decimal.");
				}
			}
		}
	}

What can we say about the Main method? We first set up our employees with the approval limits in increasing order. The next step is to read an expense report from the command line. Using that sum we construct an expense report which is given to every employee in the list. Each employee is asked to approve the limit and we check the outcome. If the expense is approved then we break the foreach loop.

Build and run the application. Enter 5000 in the console and you’ll see that the expense was approved. You’ll recall that the VP had an approval limit of 5000 so it was that employee in the chain to approve. Enter 50000 and you’ll see that nobody was able to approve the expense because it exceeds the limit of every one of them.

What is wrong with this implementation? After all we iterate through the employee list to see if anyone is able to approve the expense. We get our response and we get to know the outcome.

The problem is that the caller is responsible for iterating through the list. This means that the logic of handling expense reports is encapsulated at the wrong level. Imagine that you as an employee should not ask each one of the managers above you for a yes or no answer. You should only have to turn to your boss who in turn will ask his or her boss etc. Our code should reflect this.

In order to achieve that we need to insert a new interface:

public interface IExpenseHandler
	{
		ApprovalResponse Approve(IExpenseReport expenseReport);
		void RegisterNext(IExpenseHandler next);
	}

The Approve method should look familiar from the previous descriptions. The RegisterNext method registers the next approver in the chain. It means that if I cannot approve the expense then I should go and ask the next person in line.

This interface represents a single link in the chain of responsibility.

The IExpenseHandler interface is implemented by the ExpenseHandler class:

public class ExpenseHandler : IExpenseHandler
	{
		private readonly IExpenseApprover _approver;
		private IExpenseHandler _next;

		public ExpenseHandler(IExpenseApprover expenseApprover)
		{
			_approver = expenseApprover;
			_next = EndOfChainExpenseHandler.Instance;
		}

		public ApprovalResponse Approve(IExpenseReport expenseReport)
		{
			ApprovalResponse response = _approver.ApproveExpense(expenseReport);

			if (response == ApprovalResponse.BeyondApprovalLimit)
			{
				return _next.Approve(expenseReport);
			}

			return response;
		}

		public void RegisterNext(IExpenseHandler next)
		{
			_next = next;
		}
	}

This class will need an IExpenseApprover in its constructor. This approver is an Employee just like before. The constructor makes sure that there is always a special end of chain Employee in the approval chain through the EndOfChainExpenseHandler class. The Approve method receives an expense report. We ask the approver if they are able to approver the expense. If not, then we go to the next person in the hierarchy, i.e. to the “next” variable.

The implementation of the EndOfChainExpenseHandler class follows below. It also implements the IExpenseHandler method and it represents – as the name implies – the last member in the approval hierarchy. Its Instance property returns this special member of the chain according to the singleton pattern – more on that here.

public class EndOfChainExpenseHandler : IExpenseHandler
	{
		private EndOfChainExpenseHandler() { }

		public static EndOfChainExpenseHandler Instance
		{
			get { return _instance; }
		}

		public ApprovalResponse Approve(IExpenseReport expenseReport)
		{
			return ApprovalResponse.Denied;
		}

		public void RegisterNext(IExpenseHandler next)
		{
			throw new InvalidOperationException("End of chain handler must be the end of the chain!");
		}

		private static readonly EndOfChainExpenseHandler _instance = new EndOfChainExpenseHandler();
	}

The purpose of this class is to make sure that if the last person in the hierarchy, i.e. the President, is unable to approve the report then it is not passed on to a null reference – as there’s nobody above the President – but that there’s an automatic message handler that gives some default answer. Here we follow the null object pattern. In this case we reject the expense in the Approve method. If we made it this far in the approval chain then the expense must be rejected.

The revised Main method looks as follows:

static void Main(string[] args)
{
	ExpenseHandler william = new ExpenseHandler(new Employee("William Worker", Decimal.Zero));
	ExpenseHandler mary = new ExpenseHandler(new Employee("Mary Manager", new Decimal(1000)));
	ExpenseHandler victor = new ExpenseHandler(new Employee("Victor Vicepres", new Decimal(5000)));
	ExpenseHandler paula = new ExpenseHandler(new Employee("Paula President", new Decimal(20000)));

	william.RegisterNext(mary);
	mary.RegisterNext(victor);
	victor.RegisterNext(paula);

	Decimal expenseReportAmount;
	if (ConsoleInput.TryReadDecimal("Expense report amount:", out expenseReportAmount))
	{
		IExpenseReport expense = new ExpenseReport(expenseReportAmount);
		ApprovalResponse response = william.Approve(expense);
		Console.WriteLine("The request was {0}.", response);
	}
        Console.ReadKey();
}

You’ll see that we have not registered anyone for the President. This is where it becomes important that we set up a default end of chain approver in the ExpenseHandler constructor.

This is a significantly smaller amount of code than before. We start off by wrapping our employees into expense handlers, so each employee becomes an expense handler. Instead of putting them in a list we register the next employee in the hierarchy for each of them. Then as before we read the user’s input from the console, create an expense report and then we go to the first approver in the chain – william. The response from william will be abstracted away in the management chain we set up through the RegisterNext method.

Build and run the application. Enter 1000 and you’ll see that it is approved. Enter 30000 and you’ll see that it is rejected and the caller is oblivious of who and why rejected the request.

So this is the Chain of Responsibility pattern for you!

View the list of posts on Architecture and Patterns here.

Filed under .NET, Design patterns Tagged with .net, c#, chain of responsibility, design pattern

Design patterns and practices in .NET: the Template Method design pattern

May 20, 2013 6 Comments

Introduction

The Template Method pattern is best used when you have an algorithm consisting of certain steps and you want to allow for different implementations of these steps. The implementation details of each step can vary but the structure and order of the steps are enforced.

A good example is games:

Set up the game
Take turns
Game is over
Display the winner

A large number of games can implement this algorithm, such as Monopoly, Chess, card games etc. Each game is set up and played in a different way but they follow the same order.

The Template pattern is very much based around inheritance. The algorithm represents an abstraction and the concrete game types are the implementations, i.e. the subclasses of that abstraction. It is of course plausible that some steps in the algorithm will be implemented in the abstraction while the others will be overridden in the implementing classes.

Note that a prerequisite for this pattern to be applied properly is the rigidness of the algorithm steps. The steps must be known and well defined. The pattern relies on inheritance, rather than composition, and merging two child algorithms into one can prove difficult. If you find that the Template pattern is too limiting in your application then consider the Strategy or the Decorator patterns.

This pattern helps to implement the so-called Hollywood principle: Don’t call us, we’ll call you. It means that high level components, i.e. the superclasses, should not depend on low-level ones, i.e. the implementing subclasses. A base class with a template method is a high level component and clients should depend on this class. The base class will include one or more template method that the subclasses implement, i.e. it is the base class calling the implementation and not vice versa. In other words, the Hollywood principle is applied from the point of view of the base classes: dear implementing classes, don’t call us, we’ll call you.

Demo

Open Visual Studio and create a new blank solution. We’ll simulate a simple dispatch service where shipping an item must go through specific steps regardless of which specific service completes the shipment. Insert a new Console application to the solution.

We’ll start with the most important component of the pattern: the base class that must be respected by each implementation. Add a class called OrderShipment:

public abstract class OrderShipment
    {
        public string ShippingAddress { get; set; }
        public string Label { get; set; }
        public void Ship(TextWriter writer)
        {
            VerifyShippingData();
            GetShippingLabelFromCarrier();
            PrintLabel(writer);
        }

        public virtual void VerifyShippingData()
        {
            if (String.IsNullOrEmpty(ShippingAddress))
            {
                throw new ApplicationException("Invalid address.");
            }
        }
        public abstract void GetShippingLabelFromCarrier();
        public virtual void PrintLabel(TextWriter writer)
        {
            writer.Write(Label);
        }
    }

The template method that implements the order of the steps is Ship. It calls three methods in a specific order. Two of them – VerifyShippingData and PrintLabel are virtual and have a default implementation. They can of course be overridden. The third method, i.e. GetShippingLabelFromCarrier is the abstract method that the base class cannot implement. The superclass has no way of knowing what a service-specific shipping label looks like – it is delegated to the implementations. We’ll simulate two services, UPS and FedEx:

public class FedExOrderShipment : OrderShipment
	{
		public override void GetShippingLabelFromCarrier()
		{
			// Call FedEx Web Service
			Label = String.Format("FedEx:[{0}]", ShippingAddress);
		}
	}

public class UpsOrderShipment : OrderShipment
	{
		public override void GetShippingLabelFromCarrier()
		{
			// Call UPS Web Service
			Label = String.Format("UPS:[{0}]", ShippingAddress);
		}
	}

The implementations should be quite straighforward: they create service-specific shipping labels and set those values to the Label property. There’s of course nothing stopping the concrete classes from overriding any other step in the algorithm. Adding new shipping services is very easy: just create a new implementation. Let’s see how a client would communicate with the services:

static void Main(string[] args)
{
	OrderShipment service = new UpsOrderShipment();
	service.ShippingAddress = "New York";
	service.Ship(Console.Out);

	OrderShipment serviceTwo = new FedExOrderShipment();
	serviceTwo.ShippingAddress = "Los Angeles";
	serviceTwo.Ship(Console.Out);
        
        Console.ReadKey();
}

Run the programme and you’ll see the service-specific labels in the Console. The client calls the Template method Ship which ensures that the steps in the shipping algorithm are carried out in a certain order.

It is of course not optimal to create the specific OrderShipment classes like that, i.e. directly with the new keyword as it introduces tight coupling. Consider using a factory for building the correct implementation. However, this solution is satisfactory for demo purposes.

View the list of posts on Architecture and Patterns here.

Filed under .NET, Design patterns Tagged with .net, c#, design pattern, template

Design patterns and practices in .NET: the State pattern

May 16, 2013 12 Comments

Introduction

The State design pattern allows to change the behaviour of a method through the state of an object. A typical scenario where the state pattern is used when an object goes through different phases. An issue in a bug tracking application can have the following states: inserted, reviewed, rejected, processing, resolved and possibly many others. Depending on the state of the bug the behaviour of the underlying system may also change: some methods will become (un)available and some of them will change their behaviour. You may have seen or even produced code similar to this:

public void ProcessBug()
{
	switch (state)
	{
		case "Inserted":
			//call another method based on the current state
			break;
		case "Reviewed":
			//call another method based on the current state
			break;
		case "Rejected":
			//call another method based on the current state
			break;
		case "Resolved":
			//call another method based on the current state
			break;
	}
}

Here we change the behaviour of the ProcessBug() method based on the state of the “state” parameter, which represents the state of the bug. You can imagine that once a bug has reached the Rejected status then it cannot be Reviewed any more. Also, once it has been reviewed, it cannot be deleted. There are other similar scenarios like that where the available actions and paths depend on the actual state of an object.

Suppose you have public methods to perform certain operations on an object: Insert, Delete, Edit, Resolve, Reject. If you follow the above solution then you will have to insert a switch statement in each and check the actual state of the object and act accordingly. This is clearly not maintainable; it’s easy to get lost in the chain of the logic, it gets difficult to update the code if the rules change and the class code grows unreasonably large compared to the amount of logic carried out.

There are other issues with the naive switch-statement approach:

The states are hard coded which offers no or little extensibility
If we introduce a new state we have to extend every single switch statement to account for it
All actions for a particular state are spread around the actions: a change in one state action may have an effect on the other states
Difficult to unit test: each method can have a switch statement creating many permutations of the inputs and the corresponding outputs

In the switch statement solution the states are relegated to simple string properties. In reality they are more likely to be more important objects that are part of the core Domain. Hence that logic should be encapsulated into separate objects that can be tested independently of the other concrete state types.

Demo

We’ll simulate an e-commerce application where an order can go through the following states: New, Shipped, Cancelled. The rules are simple: a new order can be shipped or cancelled. Shipped and cancelled orders cannot be shipped or cancelled again.

Fire up Visual Studio and create a blank solution. Insert a Windows class library called Domains. You can delete Class1.cs. The first item we’ll insert is a simple enumeration:

public enum OrderStatus
	{
		New
		, Shipped
		, Cancelled
	}

Next we’ll insert the interface that each State will need to implement, IOrderState:

public interface IOrderState
	{
		bool CanShip(Order order);
		void Ship(Order order);
		bool CanCancel(Order order);
		void Cancel(Order order);
                OrderStatus Status {get;}
	}

Each concrete state will need to handle these methods independently of the other state types. The Order domain looks like this:

public class Order
	{
		private IOrderState _orderState;

		public Order(IOrderState orderState)
		{
			_orderState = orderState;
		}

		public int Id { get; set; }
		public string Customer { get; set; }
		public DateTime OrderDate { get; set; }
		public OrderStatus Status
		{
			get
			{
				return _orderState.Status;
			}
		}
		public bool CanCancel()
		{
			return _orderState.CanCancel(this);
		}
		public void Cancel()
		{
			if (CanCancel())
				_orderState.Cancel(this);
		}
		public bool CanShip()
		{
			return _orderState.CanShip(this);
		}
		public void Ship()
		{
			if (CanShip())
				_orderState.Ship(this);
		}

		void Change(IOrderState orderState)
		{
			_orderState = orderState;
		}
	}

As you can see each Order related action is delegated to the OrderState object where the Order object is completely oblivious of the actual state. It only sees the interface, i.e. an abstraction, which facilitates loose coupling and enhanced testability.

Let’s implement the Cancelled state first:

public class CancelledState : IOrderState
	{
		public bool CanShip(Order order)
		{
			return false;
		}

		public void Ship(Order order)
		{
			throw new NotImplementedException("Cannot ship, already cancelled.");
		}

		public bool CanCancel(Order order)
		{
			return false;
		}

		public void Cancel(Order order)
		{
			throw new NotImplementedException("Already cancelled.");
		}

		public OrderStatus Status
		{
			get
			{
				return OrderStatus.Cancelled;
			}
		}
	}

This should be easy to follow: we incorporate the cancellation and shipping rules within this concrete state.

ShippedState.cs is also straighyforward:

 
public class ShippedState : IOrderState
	{
		public bool CanShip(Order order)
		{
			return false;
		}

		public void Ship(Order order)
		{
			throw new NotImplementedException("Already shipped.");
		}

		public bool CanCancel(Order order)
		{
			return false;
		}

		public void Cancel(Order order)
		{
			throw new NotImplementedException("Already shipped, cannot cancel.");
		}

		public OrderStatus Status
		{
			get { return OrderStatus.Shipped; }
		}
	}

NewState.cs is somewhat more exciting as we change the state of the order after it has been shipped or cancelled:

 
public class NewState : IOrderState
	{
		public bool CanShip(Order order)
		{
			return true;
		}

		public void Ship(Order order)
		{
			//actual shipping logic ignored, only changing the status
			order.Change(new ShippedState());
		}

		public bool CanCancel(Order order)
		{
			return true;
		}

		public void Cancel(Order order)
		{
			//actual cancellation logic ignored, only changing the status;
			order.Change(new CancelledState());
		}

		public OrderStatus Status
		{
			get { return OrderStatus.New; }
		}
	}

That’s it really, the state pattern is not more complicated than this.

We separated out the state-dependent logic to standalone classes that can be tested independently. It’s now easy to introduce new states later. We won’t have to extend dozens of switch statements – the new state object will handle that logic internally. The Order object is no longer concerned with the concrete state objects – it delegates the cancellation and shipping actions to the states.

View the list of posts on Architecture and Patterns here.

Filed under .NET, Design patterns Tagged with .net, c#, design pattern, state

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Design patterns and practices in .NET: the State pattern

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