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The differences between these two types of statements become clearer when they are formalized in predicate logic. The statement the system contains two classes, Member and Book can be formalized as follows: Class(Member) Class(Book) where Class(x) is a predicate that asserts that an element x is a class. The formal representation of the statement there are two types of objects in the system, called Member and Book in predicate logic would be x Member(x) y Book(y) where the predicates Member(x) and Book(x) mean that element x is of type Member and Book, respectively. Obviously, the difference between these two statements lies in the domain of the predicates. These two types of statements re ect two aspects of the semantics of UML: The functional semantics de nes how an instance of a model behaves, while the descriptive semantics describes what an instance of a model looks like (i.e., it determines which system in a given subject domain is an instance of a model). As far as we know, all existing work on the formalization of UML semantics has focused on using functional statements in various formalisms to de ne the functions of modeled systems. As discussed brie y in Section 5.5, such works are interesting and important for the de nition of UML s semantics, especially since they deepen signi cantly our understanding of object-oriented concepts. However, a number of issues connected with the semantics of UML are neglected, and they are best addressed by descriptive semantics.

A garnish is an edible decorative item that is added to a salad to give eye appeal,though it often adds to the avor as well. It should not be elaborate or dominate the salad. Remember this basic rule of garnishing: Keep it simple.

The Batch Render window, shown in Figure 48-1, is accessed from the Rendering menu. Render tasks can be added to the list by clicking the Add button. Render tasks can be disabled by selecting the check box to the left of the task name.

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Ingredients Egg whites Cream of tartar Salt Sugar Vanilla Almond extract Sugar Cake our Yield: U.S. 2 lb 0.25 oz (1 tbsp) 1 tsp 1 lb 2 tsp 1 tsp 1 lb 12 oz 4 lb 12 oz Metric 1000 8 5 500 10 5 g g (15 mL) g (5 mL) g mL mL Percentage 267% 2% 1.5% 133% 2.5% 1.25% 133% 100% 640%

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H. Kobayashi. Application of the Diffusion Approximation to Queueing Networks, Part 1: Equilibrium Queue Distributions. Journal of the ACM, 21(2):316-328, April 1974. H. Kobayashi. Modeling and Analysis: An Introduction to System Performance Evaluation Methodology. Addison-Wesley, Reading, MA, 1978. H. Kobayashi. A Computational Algorithm for Queue Distributions via Polya Theory of Enumeration. In M. Arato and M. Butrimenko, editors, Proc. 4th Int. Symp. on Modelling and Performance Evaluation of Computer Systems, volume 1, pages 79-88, Vienna, Austria, February 1979. North-Holland. J. Kijllerstrijm. Heavy Traffic Theory for Queues with Several Servers. Journal of Applied Probability, 11:544-552, 1974. A. Konheim and M. Reiser. A Queueing Model with Finite Waiting Room and Blocking. Journal of the ACM, 23(2):328-341, April 1976. A. Konheim and M. Reiser. Finite Capacity Queuing Systems with Applications in Computer Modeling. SIAM Journal on Computing, 7(2):210-299, May 1978. D. Kouvatsos. Maximum Entropy Methods for General Queueing Networks. In Proc. Int. Conf. on Modelling Techniques and Tools for Performance Analysis, pages 589-608, 1985. W. Kramer and M. Langenbach-Belz. Approximate Formulae for General Single systems with Single and Bulk Arrivals. In Proc. 8th Int. Teletrafic Congress (ITC), pages 235-243, Melbourne, 1976. A. Krzesinski. Multiclass Queueing Networks with StateDependent Routing. Performance Evaluation, 7( 2) : 125-143, June 1987. A. Krzesinski, P. Teunissen, and P. Kritzinger. Mean Value Analysis for Queue Dependent Servers in Mixed Multiclass Queueing Networks. Technical report, University of Stellenbosch, South Africa, July 1981. P. Kubat. Reliability analysis for integrated networks with application to burst switching. IEEE Transactions on Communication, 34(6):564-568, 1986. Approximate Analysis of General Queuing NetP. Kuhn. works by Decomposition. IEEE Transactions on Communication, 27( 1):113-126, January 1979.

295 87 10 77 87

end STATE8: begin if (timerGreen) next_state = STATE9; else next_state = STATE8; end STATE9: begin if (timerYellow) next_state = STATE10; else next_state = STATE9; end STATE10: begin if (timerRed & (M2T | M4T)) next_state = STATE11; else if (timerRed & ~M2T & ~M4T & (M1S | M3S)) next_state = STATE2; else if (timerRed & ~M2T & ~M4T & ~M1S & ~M3S & (M1T | M3T)) next_state = STATE5; else if (timerRed & ~M2T & ~M4T & ~M1S & ~M3S & ~M1T & ~M3T & (M2S | M4S)) next_state = STATE8; else next_state = STATE10; end STATE11: begin if (timerGreen) next_state = STATE12;

Table 49-1 (continued)

gation and views of the resulting cost information. These views and aggregations are referred to as cost component splits. There are several cost component splits standard to product costing: cost of goods manufactured (COGM), cost of goods sold (COGS), sales and administration, inventory (commercial and tax-based). The cost component split merely filters costs based on the type of information desired. All examples contained within this chapter use the current cost estimate with the cost of goods manufactured cost component split.

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