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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existed Ideally, Dimension should have been immutable (Item 13); alternatively, the getSize method could have been replaced by two methods returning the individual primitive components of a Dimension object In act, two such methods were added to the Component API in the 12 release for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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Page 183 fabrication components of the old organization In focusing on the new business mode, it was difficult to accept the fact that the business of the firm involved neither engineering nor fabrication, but centered instead on contracting and project management This new business model posed some obvious questions, principally, How can we do this in practice One way would be through selling project management services on an hourly basis in a consulting arrangement This approach, by itself, however, was not going to meet the criteria for the return on investment that was set by the corporate management Furthermore, it was felt that this model did not offer the kind of business volume that would have been enough for survival in the long run Simply put, working exclusively as a contracting firm using project management as its core expertise meant that it was necessary to base the business on delivery contracts in which the whole scope of work had to be out-sourced, thus putting the new firm at the mercy of the supply chain This, then, led to a reconsideration of the very basic questions regarding any business: What is the value we add to the customer What are our risks and how can we cover ourselves Even if we manage to sell something, how can we make enough money to survive in the long run The game rules concerning the contracting businesses relationship to other business groups within the Rauma Corporation were clear Rauma Offshore Contracting did not have any obligation to use its sister companies as suppliers if that did not improve its competitive position in any particular contract However, rather soon after the restructuring the three companies, Rauma Offshore Contracting, Mantyluoto Works, and PI-Rauma, found the basis for forming a well-functioning supply chain network Employees of the three new companies knew each other extremely well and were able to establish the trust level necessary to make the supplier istributor relationship run smoothly Each of the three companies focused on their own business opportunities Just knowing that corporate management was not going to step in to adjudicate disputes about money.

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Experienced designers working in a familiar domain may see the exploitable concurrency immediately and could move directly to the patterns in the Algorithm Structure design space 311 Overview Before starting to work with the patterns in this design space, the algorithm designer must first consider the problem to be solved and make sure the effort to create a parallel program will be justified: Is the problem large enough and the results significant enough to justify expending effort to solve it faster If so, the next step is to make sure the key features and data elements within the problem are well understood Finally, the designer needs to understand which parts of the problem are most computationally intensive, because the effort to parallelize the problem should be focused on those parts After this analysis is complete, the patterns in the Finding Concurrency design space can be used to start designing a parallel algorithm The patterns in this design space can be organized into three groups. Make EAN 13 In Java Using Barcode printer for Java . The task decomposition dimension views the problem as a tream of instructions that can be broken into sequences called tasks that can execute simultaneously For the computation to be efficient, the operations that make up the task should be largely independent of the operations taking place inside other tasks The data decomposition dimension focuses on the data required by the tasks and how it can be decomposed into distinct chunks The computation associated with the data chunks will only be efficient if the data chunks can be operated upon relatively independently.Related: Print ISBN .NET , Generate EAN-8 .NET , ITF-14 Generating VB.NET

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Page 184 or other operating decisions created a otally new level of appreciation among the firms It also encouraged rapid feedback mechanisms between the parties concerning the effect of costs on any planned changes in the scope of work, schedule or specifications during the project Altogether, the need to negotiate formal contracts between the sister companies, one acting as a supplier to the other, resulted in a new kind of emphasis on project planning and risk identification that eventually enhanced the quality of the whole operation The close contractor-supplier relationship that worked well with the sister companies encouraged Rauma Offshore Contracting to apply the same model to their other key suppliers The most outstanding example of this effort was shown in the relationship that the company developed with its major steel supplier The continuous improvements that the steel supplier introduced in their delivery process in the form of faster and more flexible delivery, were immediately utilized in the delivery process of Rauma Offshore Contracting Today, their major contract may involve 25,000 tons of steel plates ordered in 40 separate orders, each with specific plate sizes and qualities, the delivery time being three weeks from the order to the delivery at the yard Compared to the traditional offshore projects, this has improved the delivery time of the product and created an additional competitive advantage by offering new kind of flexibility to the customers through concurrent engineering and fabrication, at the same time maintaining a reasonable level of risk Concerning their project management processes, the old fabrication yard organization implemented a traditional model where project managers were the main interface with customers but were mostly dealing with the technical issues; that is, focusing on getting the job done Functional managers were responsible for providing the resources Toward the end of the old organization the role of project management and project managers started to change, driven by low profit levels and losses during several years.

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