Programming effort

Applied at each of the interior nodes, 1 < j < 7, Eq. 4.26 represents a linear system of 7 — 2 equations and 7-2 unknowns, where the unknowns are the axial velocities at the nodes. Such a system is very easily solved. The results that follow in this section were generated using a spreadsheet, which makes programming effort minimal. 

In the earlier chapters of this book, most problems can be solved with relatively little programming effort using a spreadsheet setting (Appendix D). However, we have not found a similar implementation that can handle the differential-algebraic, method-of-lines al-... 

In some cases, the major disadvantage of second-order methods may be the programming effort required to derive explicit expressions for the Hessian elements, whose number increases as the square of the number of parameters. In Sect. 3.6, a simplified form of the Hessian matrix is derived by considering the particular form of the least-squares objective functions. 

When PPG Lake Charles first initiated its prooftest program, efforts to classify which safety devices were truly critical were not defined specific enough. Hence, the original program allowed too many instruments into the test system which created a top-heavy burden. To prevent this from happening, the following information should be developed for critical loops [8]... 

The two methods that stand out in terms of efficiency and convenience are BDF and extrapolation. Both require minimal programming effort, and can be extended to higher-order spatial derivatives. However, in the case of BDF, a limit is encountered. For the most convenient start-up methods such as the simple or the rational start, the accuracy from BDF is limited to 0(8T2). This means for one thing that one need not go beyond 3-point BDF (which is 0 8T2) in itself), but that no marked improvement can be gained from higher-order spatial derivative approximations, because there will then be a mismatch between the accuracy orders with respect to the time and spatial intervals. 

This program is again a Cottrell simulation using second-order extrapolation based on the Bl (Laasonen) method and unequal intervals, but in contrast with the above program C0TT EXTRAP, this one makes use of the four-point spatial derivative approximation, and the GU-function. It performs a little better than the above program, at little extra programming effort. 

SAX parsers also never return back to already processed data or look ahead for some value needed for current processing. The computation is therefore very fast, and the best parsers can read many megabytes of data in a few seconds, but there is a price to be paid for this speed and absence of memory limits. Programmers are required to create all necessary coding structures by themselves from information sent by SAX parsers, and this often requires a nontrivial programming effort. If ultimate efficiency is not a necessity, it is usually better to let a generic piece of software create more elaborate structures in computer memory—a data model. 

The 4n + 4m + 4 conditions derived above may be used either to eliminate unknowns and thus reduce the size of the system of equations to be solved, as was done in the original paper (13), or to generate extra equations. The latter procedure is easier to apply when mixed boundary conditions are used, the resulting increase in computer time used being offset by the saving in programming effort. 

Having a few commands that do nothing but return a standard response is useful, just because you can increase the number of commands that get an interesting answer without adding much to the programming effort. For instance, the verb BREAK with any object might get the response "Vandalism won t help your situation." This will also leave the player wondering whether there s some object that could be broken for a useful result. 

Review all Joint CBD Program efforts to assess how well they will meet operational requirements in the maritime environment. 

Although it was a frustrating experience to learn how to merge STEPIT with CSMP, we are now able to use the combination routinely for parameter evaluations and with very little programming effort. Hopefully, the information provided in this section will enable the reader to also take advantage of this powerful combination. 

The core does not access source and target tools directly but uses tool wrappers. These wrappers provide a standardized graph view on the tools documents to keep the integrator code independent of the tools specific interfaces. Additionally, they provide functions for launching tools and locating specific documents. For each tool, a new wrapper has to be implemented. To minimize the required programming efforts, the model-based wrapper specification approach described in [136] and in Sect. 5.7 of this book can be used. 

Aside from this standard, guidelines and so-called style guides of software manufacturers like Microsoft or Apple exist to ensure a uniform look and feel [886, 964]. They also contribute to a standard interface design. Therefore, new applications, such as those developed in the scope of IMPROVE, try to adapt to these guidelines and to use standardized symbols and functions. In this manner, the software system should be familiar to the user. Furthermore, the programming effort can be reduced. 

Deciding the metrics with which success is measured is another challenging task. Since a general goal of a mapping tool is to reduce the required programming effort,... 

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