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The mechanics of this refactoring apply specifically to the situation of the Transparent Fa ade AntiPattern, in which the Session fa ade component exposes the same granularity methods as the underlying components. The result should be an appropriate Session fa ade that actually does create more granular methods and subsystem layering. The different steps in this refactoring are as follows: 1. Determine the coarse-grained process(es) that the Session fa ade should implement. The first step is to decide what subsystem layering the Transparent Fa ade session should implement, that is, what it was originally intended for. Session facades are typically used to implement bulk access to Entity Beans, and/or to implement coarse-grained processes that are themselves made up of process steps and workflow. If there are existing clients that use the Transparent fa ade, they can usually be examined to decide what the usage context is, and indicate which of these was intended. Also, since the Transparent fa ade doesn t implement the coarse-grained processing that it should, this implementation usually finds its way into the clients, so this may also be helpful in deciding what implementation should be put into the Session fa ade. 2. Refactor the Session fa ade to implement the coarse-grained process. This step consists of creating the coarse-grained method(s) on the Session fa ade. As mentioned in the previous step, this will usually consist of bulk accessor and mutator methods (when providing coarser-grained access to entity beans), or process steps, workflow, and sequencing. Also, when current clients of the session have needed to implement the coarser-grained interactions to use it in context, this client implementation can be refactored down into the session. Note

At the root of the tree (the far right value) you have the organization named ExampleApp. Under the root you have a collection of organizational units in this case products. The product unit has a number of category entries, wherein the attribute name cat is a custom name that you've chosen. Finally, you have the actual entry item under the category where you use the isbn attribute name for the unique key. The LDIF file format Because the protocols are different from the tools and also from the back end database (it would be quite reasonable to implement the LDAP data structures internally as a relational database), you need some method of shuffling data back and forth, and for backing up and rebuilding databases. While no standard is defined, most LDAP databases will understand the de facto LDIF file format. The LDIF format is very straightforward basically one attribute exists per line. A blank line indicates the 163

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n=10; a=0.10;

Let s consider the use of the form element along with the method and the action attribute to specify the lines of code for logging a service request at the Headway Peripheral s site. The following is the code snippet for posting the data to hdwaysupport.jsp:

the eyes, avoiding dgeting and so on (Buller, Comstock, Aune, & Strzyzewski, 1989; Buller, Strzyzewski, & Comstock, 1991; Stiff & Miller, 1986).

A similar computation applies to all the cofactors ij , i = j . In the integral in (5.28) perform the change of variables xj =

The mean, standard deviation (SD) and maximum and minimum values are also computed for each error. A summary of the test results, calculated using the previous equations, are shown in Table 5.2. The Position Error (95%) statistics are those of the VDGPS with the largest 5% of Position errors removed (Figure 5.9). The (95%) statistics have much lower values for mean, SD and maximum error, which demonstrates that there are a few very large errors (over 50 m) in the full set of VDGPS results, this is shown in Figure 5.8. Figure 5.11 displays the length of road centre-line on which almost all of these large errors arise, i.e. between epochs 482070 and 482150. The only other time such large errors occur is at the

module SampleApp { interface Sample { string sayName(); }; };

Asset # # Profit Trades Days Max Draw MDD MCL P:L P:MD Ratio %W Time %

87 08 88 33 22 50 48 70 93 45 50 76 91 64 33 20 90 59 05 10 92 85 08 50 59 36 05 85 13 46 56 27 54 15 83 01 00 28 52 29 64 43 80 68 28 72 33 48 04 41 21 31 52 08 90 57 76 50 06 84 47 92 71 87 38 30 09 80 82 52 14 18 62 60 15 02 23 32 96 66 12 41 70 78 30 43 36 58 17 35 73 30 92 15 05 02 5l 22 23 28

[n/2]

Institute of Technology has recently launched a new educational program, its very own Masters in Finance. For those less than exaggeratedly interested in the graduate education landscape and who may doubt the relevance of such news, let me assure you that Sloan s initiative is nothing short of revolutionary. It is the rst time that a truly top U.S. business school has decided to offer a fully edged specialized nance degree, in a pioneering move that may soon be imitated by some of MIT s privileged peers (the likes of Harvard or Stanford).

In order to solve the 36 unknown coef cients, the derivatives fx, fy, fxx, fxy, fyy, fxxy, fxyy, and fxxyy and the elevations at each of the four grid vertices are required to generate a 36 36 system of equations. For the bicubic and biquintic interpolation algorithms, nite difference approximations are used for the purpose of calculating the partial derivatives [Kidner, 2003].

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