ASP.NET PDF Viewer using C#, VB/NET

The Qt class QSemaphore implements the semaphore feature. You can acquire a value from a semaphore object by using the acquire method, or use the tryAcquire method if you don t want to block when the requested value is not available. The tryAcquire method returns true if the acquisition was successful and false if the requested amount was not available. You release a value back to a semaphore object using the release method. If you want to know the value of a semaphore object without affecting the semaphore, you can use the available method. This can be handy if the semaphore represents the availability of a shared resource and you want to show the user how much of the resource is being used. In Listing 12-17, you can see how the available value changes as a semaphore object is used. The semaphore is initialized to have a value of 10 before a series of acquire and release calls are made. The highlighted line shows a method call to tryAcquire that fails because the call attempts to acquire more than is available. Because the call fails, the available value of the semaphore is left unchanged. Listing 12-17. The available value of a semaphore is changed because the object is used. QSemaphore s( 10 ); s.acquire(); s.acquire(5); s.release(2); s.release(); s.release(5); s.tryAcquire(15); // // // // // // s.available() s.available() s.available() s.available() s.available() s.available() = = = = = = 9 4 6 7 12 12

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With CanChange as a value type, it takes about 150 ms on my machine to populate the list, and then about 40 ms to run through all the numbers, adding them together. But if I change CanChange from a struct to a class (i.e., make it a reference type) the numbers become more like 600 ms and 50 ms, respectively. So that s about 25 percent longer to perform the calculations but a staggering four times longer to create the collection in the first place. And that s because with CanChange as a reference type, we now need to ask the .NET Framework to create half a million objects for us instead of just one object when we initialize the list. From the perspective of an end user, this is the difference between a tiny hiatus and an annoyingly long delay when an application freezes for more than half a second, users begin to wonder if it has hung, which is very disruptive.

Please don t take away the message that value types are four times faster than reference types they aren t. A micro benchmark like this should always be taken with a very strong pinch of salt. All we ve really measured here is how long it takes to do something contrived in an isolated and artificial experiment. This example is illuminating only insofar as it demonstrates that the choice between value types and reference types can sometimes have a profound effect. It would be a mistake to draw a generalized conclusion from this. Notice that even in this example we see significant variation: the first part of the code slowed down by a factor of four, but in the second part, the impact was much smaller. In some scenarios, there will be no measurable difference, and as it happens there are situations in which value types can be shown to be slower than reference types. The bottom line is this: the only important performance measurements are ones you make yourself on the system you are building. If you think your code might get a useful speedup by using a value type instead of a reference type in a large collection, measure the effect of that change, rather than doing it just because some book said it would be faster.

Since the use of value types in a collection can sometimes offer very useful performance benefits, the rule of thumb we suggested earlier always use reference types looks too restrictive in practice. So this is where immutability comes into play. As we saw earlier in this section, the fact that a get accessor can only return a copy of a value type causes problems if you ever need to modify a value already in a collection. But if your value types are immutable, you will never hit this problem. And as we ll see in 16, there are other benefits to immutable types. So we now know how List<T> is able to make itself resemble an array. Having understood some of the subtle differences between array element access and custom indexers, let s get back to some of the other functionality of List<T>.

As well as joining text up, we can also split it up into smaller pieces at a particular breaking string or character. For example, we could split the final concatenated string back up at whitespace or punctuation as in Example 10-59.

One of the biggest risks when implementing threaded systems is the deadlock, which occurs when two threads block each other so that both block. Because both are blocked, neither can release the resource that the other thread is blocking on. The result is that the system freezes.

string[] strings = Soliloquize(); string output = String.Join(Environment.NewLine, strings); string[] splitStrings = output.Split( new char[] { ' ', '\t', '\r', '\n', ',', '-', ':' }); bool first = true;

foreach (string splitBit in splitStrings) { if( first ) { first = false; } else { Console.Write(", "); } Console.Write(splitBit); }

addCssClass(String className)

If we run again, we see the following output:

Note A deadlock can occur even with a single thread. Imagine a thread trying to acquire a value that is

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