generate 2d barcode vb.net Part II Designing Types in Visual C#

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Part II Designing Types
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performance . Since a generic algorithm can now be created to work with a specific value type, the instances of the value type can be passed by value, and the CLR no longer has to do any boxing . In addition, since casts are not necessary (see the previous bullet), the CLR doesn t have to check the type safety of the attempted cast, and this results in faster code too . To drive home the performance benefits of generics, I wrote a program that tests the performance of the generic List algorithm against the FCL s non-generic ArrayList algorithm . In fact, I tested the performance of these two algorithms by using both value type objects and reference type objects . Here is the program itself:
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using using using using System; System.Collections; System.Collections.Generic; System.Diagnostics;
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public static class Program { public static void Main() { ValueTypePerfTest(); ReferenceTypePerfTest(); } private static void ValueTypePerfTest() { const Int32 count = 10000000; using (new OperationTimer("List<Int32>")) { List<Int32> l = new List<Int32>(count); for (Int32 n = 0; n < count; n++) { l.Add(n); Int32 x = l[n]; } l = null; // Make sure this gets GC'd } using (new OperationTimer("ArrayList of Int32")) { ArrayList a = new ArrayList(); for (Int32 n = 0; n < count; n++) { a.Add(n); Int32 x = (Int32) a[n]; } a = null; // Make sure this gets GC'd } } private static void ReferenceTypePerfTest() { const Int32 count = 10000000; using (new OperationTimer("List<String>")) { List<String> l = new List<String>(); for (Int32 n = 0; n < count; n++) { l.Add("X"); String x = l[n]; }
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l = null; } using (new OperationTimer("ArrayList of String")) { ArrayList a = new ArrayList(); for (Int32 n = 0; n < count; n++) { a.Add("X"); String x = (String) a[n]; } a = null; // Make sure this gets GC'd } } } // This class is useful for doing operation performance timing internal sealed class OperationTimer : IDisposable { private Int64 m_startTime; private String m_text; private Int32 m_collectionCount; public OperationTimer(String text) { PrepareForOperation(); m_text = text; m_collectionCount = GC.CollectionCount(0); // This should be the last statement in this // method to keep timing as accurate as possible m_startTime = Stopwatch.GetTimestamp(); } public void Dispose() { Console.WriteLine("{0,6:###.00} seconds (GCs={1,3}) {2}", (Stopwatch.GetTimestamp() - m_startTime) / (Double) Stopwatch.Frequency, GC.CollectionCount(0) - m_collectionCount, m_text); } private static void PrepareForOperation() { GC.Collect(); GC.WaitForPendingFinalizers(); GC.Collect(); } } // Make sure this gets GC'd
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When I compile and run a release build (with optimizations turned on) of this program on my computer, I get the following output:
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.10 3.02 .47 .51 seconds seconds seconds seconds (GCs= 0) List<Int32> (GCs= 45) ArrayList of Int32 (GCs= 6) List<String> (GCs= 6) ArrayList of String
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Part II Designing Types
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The output here shows that using the generic List algorithm with the Int32 type is much faster than using the non-generic ArrayList algorithm with Int32 . In fact, the difference is phenomenal: .1 second versus 3 seconds . That s 30 times faster! In addition, using a value type (Int32) with ArrayList causes a lot of boxing operations to occur, which results in 45 garbage collections . Meanwhile, the List algorithm required 0 garbage collections . The result of the test using reference types is not as momentous . Here we see that the times and number of garbage collections are about the same . So it doesn t appear that the generic List algorithm is of any benefit here . However, keep in mind that when using a generic algorithm, you also get cleaner code and compile-time type safety . So while the performance improvement is not huge, the other benefits you get when using a generic algorithm are usually an improvement . Note You do need to realize that the CLR generates native code for each method the first time
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the method is called for a particular data type . This will increase an application s working set size, which will hurt performance . I will talk about this more in the Generics Infrastructure section of this chapter .
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