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actions associated with the rules that evaluated to true. During this evaluation process, the engine may ascertain other derived facts based on these basic facts and the rules, which help the engine decide what actions to take. For instance, when examining an account, the engine may determine that it would fall below the minimum balance if the requested amount of money were withdrawn; this potential violation of the minimum balance rule may lead to aborting the transaction. Figure 12.2 shows the collaboration between business objects and the rule engine. While this figure shows the structural view of a system using a rule engine, figure 12.3 shows the behavioral view of these steps in a sequence diagram. At the beginning of this section, we discussed the three steps involved in using a rule engine. In figure 12.3, the call to initializeRules() corresponds to the first step of expressing the rules. This step is needed only once to initialize the rule engine before it can be used. The next two steps are executed each time an operation is called by the core business logic execution. In step 2, expressing the facts, we store the facts into the rule engine s working memory (also referred

OWC Features It s beyond the scope of this book to provide extensive coverage of the OWC PivotTable features, but we ll outline some of the key similarities and differences between the two types of pivot tables. The OWC PivotTable will contain the page, row, column, and data fields from your Excel PivotTable report. The fields can be moved to a new location, or removed from the pivot table. Click the Field List button in the OWC toolbar to open the field list and add more fields to the pivot table. The Summary functions for the data fields are those that appeared in the original Excel PivotTable and can t be changed. You can create custom calculations, such as Percent of Row, Calculated Totals, and Calculated Detail Fields.

Figure 12.3 The integration of business logic with business rules in a rule engine using current mechanisms. Whenever an operation is performed that may cause business rules to be fired, the operation must load the engine with the facts and ask it to perform the evaluation.

Changes to the rnd_init() Method in ha_spartancc int ha_spartan::rnd_init(bool scan) { DBUG_ENTER("ha_spartan::rnd_init"); current_position = 0; records = 0; ref_length = sizeof(long long); DBUG_RETURN(0); }.

to as asserting the facts) by calling the assertFact() method on the rule engine. Then we execute step 3, evaluating the rules, by calling the run() method on the rule engine. A conventional implementation of this scheme would require us to add the code for executing steps 2 and 3 to each operation in the business classes that might need to use business rules. Additionally, any change in the business rule requirements, including the use of a different engine, will necessitate changing all the operations in the business classes. In the next section, we see how AspectJ can simplify this process. 12.6.3 Modularizing with AspectJ Although a rule engine can help you separate the rule evaluation concern from the rule invocation, you still need to invoke the rule engine from each module in the system to which business rules may apply. The AspectJ-based solution we propose here separates the concern of invoking the rule engine from the core business logic. With this solution, the core business logic is unaware that the business rules are being applied and that a rule engine is part of the picture.

Items in the row, column, and data areas can be sorted, filtered, and grouped. For example, you can show only the top five customers, or the bottom 10 percent of your products.

Caution This is the point at which we start adding functionality beyond that of the example engine. Be

Figure 12.4 The collaboration between business logic, coordinating aspects, and the rule engine. The rule engine is set up with the rules. The aspect advises the important join points in the business logic to initialize the working memory of the rule engine and to request that rules be evaluated. The rule engine executes the actions corresponding to the matching rules.

sure to correctly specify your return codes. The example engine tells the optimizer a function is not supported by issuing the return statement DBUG_RETURN(HA_ERR_WRONG_COMMAND);. Be sure to change these to something other than the wrong command return code (e.g., 0).