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 pattern (described in \[[Lea 00|AA. Java References#Lea 00]\]) is the simplest concurrency strategy wherein a new thread is created for each request.  This design pattern is generally recommended over sequential executions of time consuming, I/O bound, session based or isolated tasks.

However, this design pattern also has several pitfalls, including overheads of thread-creation and scheduling, task processing, resource allocation and deallocation, and frequent context switching \[[Lea 00|AA. Java References#Lea 00]\]. Furthermore, an attacker can cause a denial of service by overwhelming the system with too many requests all at once. Instead of degrading gracefully, the system becomes unresponsive, resulting in a denial of service.  From the safety point of view, one component can potentially exhaust all resources because of some intermittent error, starving all other components.

Thread pools allow a system to service as many requests as it can comfortably sustain, rather than terminating all services when presented with a deluge of requests. Thread pools overcome these issues because the maximum number of _worker threads_ that can be initialized and executed concurrently can be suitably controlled. Every object that supports thread pools accepts a {{Runnable}} or {{Callable<T>}} task and stores it in a temporary queue until resources become available.  Because the threads in a thread pool can be reused and efficiently added or removed from the pool, thread life-cycle management related overhead is minimized.  


h2. Noncompliant Code Example

This noncompliant code example demonstrates the Thread-Per-Message design pattern.  The class {{RequestHandler}} provides a public static factory method so that callers can obtain its instance. Subsequently, the {{handleRequest()}} method is used to handle each request in its own thread.

{code:bgColor=#FFCCCC}
class Helper {
  public void handle(Socket socket) {
    // ... 		
  }	
}

final class RequestHandler {
  private final Helper helper = new Helper();
  private final ServerSocket server;

  private RequestHandler(int port) throws IOException {
    server = new ServerSocket(port);
  }
  
  public static RequestHandler newInstance() throws IOException {
    return new RequestHandler(0); // Selects next available port
  }
  
  public void handleRequest() {
    new Thread(new Runnable() {
        public void run() {
          try {
            helper.handle(server.accept());
          } catch (IOException e) {
            // Forward to handler 
  
        }
        }
    }).start();
  }

  // ... other methods such as shutting down the thread pool and task cancellation ...
}
{code}

Per-Message strategy fails to provide graceful degradation of service. As the number of concurrent threads increases, processing continues normally until some resource is exhausted. The resource to be exhausted first depends on the tasks being performed, and could be available file descriptors, available threads provided by the system, available memory, or any number of other resources. When a critical resource, such as memory, gets exhausted, the system will fail hard, refusing to service any more requests.

{mc} If you want to include the above para, I suggest using a version similar to the following: ~DM
The Thread-Per-Message strategy fails to provide graceful degradation of service. As more threads are created, processing continues normally until some scarce resource is exhausted. For example, a system may only allow only a limited number of open file descriptors even though several more threads can be created to service requests. When the scarce resource is memory, the system may fail abruptly, resulting in a denial of service.
{mc}

h2. Compliant Solution

This compliant solution uses a _Fixed Thread Pool_ that places an upper bound on the number of concurrently executing threads. Tasks submitted to the pool are stored in an internal queue. This prevents the system from being overwhelmed when trying to respond to all incoming requests and allows it to degrade gracefully by serving a fixed number of clients at a particular time. \[[Tutorials 08|AA. Java References#Tutorials 08]\]

{code:bgColor=#ccccff}
// class Helper remains unchanged

final class RequestHandler {
  private final Helper helper = new Helper();
  private final ServerSocket server;
  private final ExecutorService exec;
	 
  private RequestHandler(int port, int poolSize) throws IOException {
    server = new ServerSocket(port);
    exec = Executors.newFixedThreadPool(poolSize);
  }
	  
  public static RequestHandler newInstance(int poolSize) 
                                           throws IOException {
    return new RequestHandler(0, poolSize); 
  }
	  
  public void handleRequest() {	
    Future<?> future = exec.submit(new Runnable() {
        @Override public void run() {
	          try {
  	          helper.handle(server.accept());
	          } catch (IOException e) {
            // Forward to handler						
          }
        }
    });
  }
}
{code}

According to the Java API documentation for the {{Executor}} interface \[[API 06|AA. Java References#API 06]\]:

{quote}
\[The Interface {{Executor}} is\] An object that executes submitted {{Runnable}} tasks. This interface provides a way of decoupling task submission from the mechanics of how each task will be run, including details of thread use, scheduling, etc. An {{Executor}} is normally used instead of explicitly creating threads.
{quote}

The {{ExecutorService}} interface used in this compliant solution derives from the {{  // ... Other methods such as shutting down the thread pool 
  // and task cancellation ...
}