c# generating barcode As usual, the results vary significantly from compiler to compiler. in Visual C#.NET

Maker GS1 - 13 in Visual C#.NET As usual, the results vary significantly from compiler to compiler.

As usual, the results vary significantly from compiler to compiler.
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Use Supplementary Indexes
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Using a supplementary index means adding related data that makes accessing a data type more efficient. You can add the related data to the main data type, or you can store it in a parallel structure.
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String-Length Index
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One example of using a supplementary index can be found in the different string-storage strategies. In C, strings are terminated by a byte that s set to 0. In Visual Basic string format, a length byte hidden at the beginning of each string indicates how long the string is. To determine the length of a string in C, a program has to start at the beginning of the string and count each byte until it
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26. Code-Tuning Techniques
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finds the byte that s set to 0. To determine the length of a Visual Basic string, the program just looks at the length byte. Visual Basic length byte is an example of augmenting a data type with an index to make certain operations like computing the length of a string faster. You can apply the idea of indexing for length to any variable-length data type. It s often more efficient to keep track of the length of the structure rather than computing the length each time you need it.
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Independent, Parallel Index Structure
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Sometimes it s more efficient to manipulate an index to a data type than it is to manipulate the data type itself. If the items in the data type are big or hard to move (on disk, perhaps), sorting and searching index references is faster than working with the data directly. If each data item is large, you can create an auxiliary structure that consists of key values and pointers to the detailed information. If the difference in size between the data-structure item and the auxiliary-structure item is great enough, sometimes you can store the key item in memory even when the data item has to be stored externally. All searching and sorting is done in memory, and you have to access the disk only once, when you know the exact location of the item you want.
Use Caching
Caching means saving a few values in such a way that you can retrieve the most commonly used values more easily than the less commonly used values. If a program randomly reads records from a disk, for example, a routine might use a cache to save the records read most frequently. When the routine receives a request for a record, it checks the cache to see whether it has the record. If it does, the record is returned directly from memory rather than from disk. In addition to caching records on disk, you can apply caching in other areas. In a Microsoft Windows font-proofing program, the performance bottleneck was in retrieving the width of each character as it was displayed. Caching the most recently used character width roughly doubled the display speed. You can cache the results of time-consuming computations too especially if the parameters to the calculation are simple. Suppose, for example, that you need to compute the length of the hypotenuse of a right triangle, given the lengths of the other two sides. The straightforward implementation of the routine would look like this:
Java Example of a Routine That s Conducive to Caching
double Hypotenuse( double sideA,
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26. Code-Tuning Techniques
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double sideB ) { return Math.sqrt( ( sideA * sideA ) + ( sideB * sideB ) ); }
If you know that the same values tend to be requested repeatedly, you can cache values this way:
Java Example of Caching to Avoid an Expensive Computation
private double cachedHypotenuse = 0; private double cachedSideA = 0; private double cachedSideB = 0; public double Hypotenuse( double sideA, double sideB ) { // check to see if the triangle is already in the cache if ( ( sideA == cachedSideA ) && ( sideB == cachedSideB ) ) { return cachedHypotenuse; } // compute new hypotenuse and cache it cachedHypotenuse = Math.sqrt( ( sideA * sideA ) + ( sideB * sideB ) ); cachedSideA = sideA; cachedSideB = sideB; return cachedHypotenuse; }
The second version of the routine is more complicated than the first and takes up more space, so speed has to be at a premium to justify it. Many caching schemes cache more than one element, so they have even more overhead. Here s the speed difference between these two versions:
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