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Now that we have agreed a precise formal specification of the precondition and postcondition, we may proceed to the development of the algorithm. oare's description of the problem involves manipulating a deck of cards. This means that his solution involves operations that are not so easy to implement in a computer program. In particular, Hoare's solution puts the 'borderline card' to one side during the process of adding cards to the bottom-left and bottom-right heaps. We will impose the restriction that all changes to the array are effected by swapping array elements. This means that the program we develop is guaranteed to permute the elements of the array (and will not, for example, introduce spurious array elements) but prohibits us from placing any cards to one side. We are seeking a so-called in situ sort of the array elements. The basic idea is to maintain invariant the property that, for some indices 5 and I, the first 5 elements of the array are known to be 'small', the next l-s elements are 'medium', and the remaining N-l elements are 'large'. Making precise what we mean by 'small', etc., a suitable invariant property is: A ( V i j : 0 ^ i < 5 A s^j <N : A ( V i j : C K i < [ A l^j<N : a [ i ] < a [ j ] } . The inequality 0 ^ 5 < K, together with the first universal quantification, defines the function of the variable 5 during the course of the computation, whilst the. Crystal matrix barcode integrating on .net generate, create matrix barcode none in .Related: 

The Tuple3f class is a generic three-element tuple represented by single-precision oating-point x, y, and z coordinates Variables The component values of a Tuple3f are directly accessible through the public variables x, y, and z To access the x component of a uple3f called upperLeftCorner, a programmer would write upperLeftCornerx The programmer would access the y and z components similarly. Version 11 Alpha 01, February 27, 1998. Encode Bar Code In Visual C# Using Barcode generation for .NET .Related: .NET Intelligent Mail Generating , ISBN Generating Word , PDF417 Generator C#

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Consider the performance consequences of your API design decisions Making a public type mutable may require a lot of needless defensive copying (Item 24) Similarly, using inheritance in a public class where composition would have been appropriate ties the class forever to its superclass, which can place artificial limits on the performance of the subclass (Item 14) As a final example, using an implementation type rather than an interface in an API ties you to a specific implementation, even though faster implementations may be written in the future (Item 34) The effects of API design on performance are very real Consider the getSize method in the javaawtComponent class The decision that this performance-critical method was to return a Dimension instance, coupled with the decision that Dimension instances are mutable, forces any implementation of this method to allocate a new Dimension instance on every invocation Even though, as of release 13, allocating small objects is relatively inexpensive, allocating millions of objects needlessly can do real harm to performance In this case, several alternatives existed Ideally, Dimension should have been immutable (Item 13); alternatively, the getSize method could have been replaced by two methods returning the individual primitive components of a Dimension object In fact, two such methods were added to the Component API in the 2 release for performance reasons Preexisting client code, however, still uses the getSize method and still suffers the performance consequences of the original API design decisions Luckily, it is generally the case that good API design is consistent with good performance It is a very bad idea to warp an API to achieve good performance The performance issue that caused you to warp the API may go away in a future release of the platform or other underlying software, but the warped API and the support headaches that it causes will be with you for life Once you've carefully designed your program and produced a clear, concise, and wellstructured implementation, then it may be time to consider optimization, assuming you're not already satisfied with the performance of the program Recall that Jackson's two rules of optimization were Don't do it, and (for experts only) Don't do it yet He could have added one more: Measure performance before and after each attempted optimization You may be surprised by what you find Often attempted optimizations have no measurable effect on performance; sometimes they make it worse The main reason is that it's difficult to guess where your program is spending its time The part of the program that you think is slow may not be at fault, in which case you'd be wasting your time trying to optimize it Common wisdom reveals that programs spend 80 percent of their time in 20 percent of their code Profiling tools can help you decide where to focus your optimization efforts Such tools give you run-time information such as roughly how much time each method is consuming and how many times it is invoked In addition to focusing your tuning efforts, this can alert you to the need for algorithmic changes If a quadratic (or worse) algorithm lurks inside your program, no amount of tuning will fix the problem You must replace the algorithm with one that's more efficient The more code in the system, the more important it is to use a profiler It's like looking for a needle in a haystack: The bigger the haystack, the more useful it is to have a metal detector The Java 2 SDK comes with a simple profiler, and several more sophisticated profiling tools are available commercially.

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