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Business rules are policies enforced by a company for its various business processes For example, the company might require that each purchase be approved by three people holding specific titles (purchasing agent, manager of accounts payable, project manager) Business rules may or may not be implemented in your model, but they need to be documented because eventually you need to implement them somewhere Whether you implement them as a relationship in the model, use a trigger in SQL Server, or even implement them through an application, it is important to understand them early, because the model design will be driven by the business rules that it needs to support In 6 we also look at the iterative process of working with stakeholders in the company They not only have to sign off on the initial model, but both you (as the designer) and they (as the customer) will have changes that need to be made as the process moves forward Next, we discuss the business review of the model It s crucial to get your customers buy in and sign-off of the logical model Once the customer has approved the model, you can document releases and work toward the agreed-upon system We cannot reiterate this point enough: You cannot skip this step It will save you days of pain down the line if the company needs to make changes to the requirements If you have agreed-upon release cycles, then you can simply add new changes at the expense of the project s time line or of other requirements Without this agreement, you will be engaged in discussions, even arguments, about the changes, and either your customer or your modeling team will end up dissatisfied with the outcome

In this section we combine descriptors with class decorators to create a powerful mechanism for creating validated attributes Up to now if we wanted to ensure that an attribute was set to only a valid value we have relied on properties (or used getter and setter methods) The disadvantage of such approaches is that we must add validating code for every attribute in every class that needs it What would be much more convenient and easier to maintain, is if we could add attributes to classes with the necessary validation built in Here is an example of the syntax we would like to use:

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Thread and process creation and destruction is one of the more expensive operations that occur in parallel programs Thus, if a program contains repeated fork and join sections, the simple solution, which would require repeated destruction and creation of UEs, might not be efficient enough Also, if at some point there are many more UEs than PEs, the program might incur unacceptable overhead due to the costs of context switches In this case, it is desirable to avoid the dynamic UE creation by implementing the fork/join paradigm using a thread pool The idea is to create a (relatively) static set of UEs before the first fork operation The number of UEs is usually the same as the number of PEs The mapping of tasks to UEs then occurs dynamically using a task queue The UEs themselves are not repeatedly created and destroyed, but simply mapped to dynamically created tasks as the need arises This approach, although complicated to implement, usually results in efficient programs with good load balance We will discuss a Java program that uses this approach in the Examples section of this pattern In OpenMP, there is some controversy over the best approach to use with this indirect mapping approach [Mat03] An approach gaining credibility is one based on a new, proposed OpenMP workshare construct called a taskqueue [SHPT00] The proposal actually defines two new constructs: a taskqueue and a task As the name implies, the programmer uses a taskqueue construct to create the task queue Inside the taskqueue construct, a task construct defines a block of code that will be packaged into a task and placed on the task queue The team of threads (as usually created with a parallel construct), playing the role of a thread pool, pulls tasks off the queue and executes them until the queue is empty Unlike OpenMP parallel regions, taskqueues can be dependably nested to produce a hierarchy of task queues The threads work across task queues using work stealing to keep all threads fully occupied until all of the queues are empty This approach has been shown to work well [SHPT00] and is likely to be adopted in a future OpenMP specification Examples As examples of this pattern, we will consider direct mapping and indirect mapping implementations.

@valid_string("name", empty_allowed=False) @valid_string("productid", empty_allowed=False, regex=recompile(r"[A-Z]{3}\d{4}")) @valid_string("category", empty_allowed=False, acceptable= frozenset(["Consumables", "Hardware", "Software", "Media"])) @valid_number("price", minimum=0, maximum=1e6) @valid_number("quantity", minimum=1, maximum=1000) class StockItem:

The osstat() function takes a lename and returns a named tuple with various items of information about the le, including its size, mode, and last modi ed date/time

def __init__(self, name, productid, category, price, quantity): selfname = name selfproductid = productid selfcategory = category selfprice = price selfquantity = quantity

of a parallel mergesort algorithm The indirect mapping solution makes use of a Java package FJTasks [Lea00b] The Examples section of the Shared Queue pattern develops a similar, but simpler, framework

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