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But just for a moment let s consider other possible variations Some customers may, for example, wish to get a regular report containing a graph summarizing how promptly issues are being dealt with But perhaps there are two alternative algorithms for cooking them up some customers favor one method, and others prefer the other method One way of dealing with this is a compiler switch: #if ReportType1 #else #endif (There is also of course the option of a runtime ag, which we ll discuss later in this chapter) Now suppose there are many such choices, some of them multivalued and some of them interdependent, and some of them requiring more subtle variations in the code than just including a block or not Some bright team member comes up with the idea of encoding all the choices in XML and then generating the required code from that This is where the DSL Tools come in, since they can read the XML le and use text templates to generate the code from choices encoded in the XML In this case, the DSL is just the XML, and the strength of the DSL Tools is in generating the code from this model In situations where the DSL is more sophisticated, embodying relations between entities such as work ows or complex static relationships then it is useful to think in terms of a diagrammatic DSL, and the diagram editing capabilities of the DSL Tools become useful For most of the examples in this book, we ll discuss diagrammatic DSLs, if only to show off the full feature set This DSL looks similar to the UML state diagram notation a deliberate choice that was made so that newcomers can readily understand its intention But it is without many of the UML features that are not required here, such as nested states, guards, and other decorations on transitions The semantics of this language will be expressed entirely by the code generators written for this application.

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Figure 12.27 The change in the energy of the lowest eigenstate of a 28.25 A GaAs single quantum well surrounded by Ga0.8 Al0.2 As barriers, as a function of the applied electric field

Average Cost per Item Beginning Inventory Add: Purchases from Shipment #1 Add: Purchases from Shipment #2 Total Number of Items 10 100 100 210 Average Cost $10.00 $12.00 $15.00 N/A Total Value of Inventory $100.00 $1,200.00 $1,500.00 Average Cost of Inventory per Item $10.00 $11.81 ($1,300.00/110) $13.33 ($2,800.00/210) $2,799.30 (210 $13.33)

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Top-Down and Bottom-Up Hearing of the decision to generate code from state diagrams, Annie, the chief analyst, isn t surprised She recounts that whenever she visits a new client to discuss its project management requirements, the discussion pretty soon gets around to issue tracking Having now had plenty of experience with these clients, Annie immediately asks them about the states they need in their issue logs The customers aren t always clear about this at rst, but Annie nds it helps to draw a diagram of the states and their possible transitions on the

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evidenced in the empirical pseudopotential calculation, and in fact, the energy changes are remarkably similar over the range of electric fields employed. Thus, Fig. 12.27 seems to imply, at first sight, that the computationally 'long-winded' approach of the empirical pseudopotential method is no better than much quicker methods based on the envelope function approximation. Indeed, if Stark effect energy level changes are all that is of interest, then this would be the case. However, the pseudopotential method gives much more, e.g. the same calculation can also be used to yield the in-plane dispersion curve, and the pseudopotential method can account much more fundamentally for valence band mixing and strain, at the same time as modelling the electric field.

Receipt of inventory is an important accounting event. It must be properly recorded in order to maintain accurate totals and correct valuation. Inventory receipts are accounted for in one of three ways, depending on when payment occurs in relation to receipt of the goods. In the rst accounting scenario, you receive the goods and pay for them simultaneously. In the second scenario, you receive the goods and get a bill for them at a later date. The third and nal scenario is based on your paying for goods you haven t yet received.

13.1 RECENT PROGRESS The difficulties associated with applying the techniques outlined in this work to lowerdimensional quantum wires and dots, have been hinted at already. In the work on point defects in bulk material (Section 11.13), in which a single impurity atom was placed within a larger cube of bulk material, more than 2000 plane waves were needed in the expansion set. In effect, such a system represents the ultimate quantum dot, with the confining potential existing on account of the single atom, after all, quantum dots are often referred to as artificial atoms (see, for example [265]). Single-atom quantum dots are also single-electron quantum dots [266,267]. To deal with larger quantum dots, remembering that real dots often have a base length in the range 100 400 A, requires a very large number of plane waves, and indeed the problem becomes too large to handle with present day computers. The perturbative approach, as derived for the superlatice in 12, can be extended to deal with quantum dots [268], and this appears to be a promising improvement for modest-sized unit cells. Recently, Zunger and co-workers have demonstrated a new computational technique which deals with this large-matrix problem. Instead of seeking solutions of the

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