Presentation on theme: "1 Automating Business Rule Adaptation for Web-Based Information Systems Mei Tian 1, Ajit Singh 2, Kumaraswamy Ponnambalam 1, Raymond Lee 2 1 Systems Design."— Presentation transcript:
1 Automating Business Rule Adaptation for Web-Based Information Systems Mei Tian 1, Ajit Singh 2, Kumaraswamy Ponnambalam 1, Raymond Lee 2 1 Systems Design Engineering, University of Waterloo 2 Electrical and Computer Engineering, University of Waterloo
2 Presentation Outline Introduction Business Rule Model Implementation Case Study Future Work
3 Web-Based Information Systems back-end database business logic middleware client application JRMP http Three-Tier architecture
4 What Are Business Rules? Formal statements about the data and processes of an enterprise Presented as program logic in enterprise application
5 Business Rule Examples If a customer buys product worth more than $100 in an order, he will get a 10% discount. If the product in warehouse is less than 5, reorder this product. Shipping fee is $20 for each order.
6 Why Automation Business rules change quickly Business rules are often embedded with the data access and application logic To speed up the application development To reduce maintenance cost
7 Research Subareas Business rule representation Business rule extraction Business rule management Business rule processing
8 Research Background Business rules representation External Conceptual Internal Users,analyzers Structured English, etc. Designer, developer BRML, etc. Physical machine Binary code
9 Research Background Business rule extraction Data analyzing Programming analyzing Hybrid
10 Research Background Business rule management Repository-based method artificial Intelligence
11 Research Background Business rules processing Procedural programming SQL trigger Declarative programming Constraint programming
12 Challenges No standard business rule model No distributed business rule framework Difficult to define a flexible rule interface How to find the rule firing order without an inference engine
13 Assumptions Rules have been found somehow Rules are correct with no conflict and redundancy Target to small/middle size information systems Not use artificial intelligence
14 Solution Strategies (1) A general business rule model A rule system and a distributed business rule framework
15 Solution Strategies (2) A EJB design pattern and the bean relationship information Rule dependency graph, rule-firing- history, and rule label
16 Business Rule Model Organization Model name: String ruleType: String priority: String triggeredClass: String triggerMethod: String triggerLocation: String implementor: String description: String name: String effective:Date expiration:Date BusinessRuleSet BusinessRule 1* *1 Common Knowledge Model * * 1 * TermRuleFactRuleActionRuleDerivationRule ApplicationRuleSet appName:StringsetName:String source:String ShareRuleSet RuleChecker description: String 1* Legend: class *1 Many-to-one associationgeneralization Implementer 1* ruleName:String
18 Term Rule Defines the vocabulary of a business Not implemented as a part of an Information System(IS) Example: A telephone line is an asset.
19 Fact Rule Documents the relationship between items Aggregation, association, generalization belongs to, identified by In an IS, implemented as relationship between classes, entity beans, or tables Example: A student has a student ID.
20 Action Rule States the conditions under which actions must be taken Transformation Rule: Transforms the execution from one event to another Validation Rule: States what kind of value for an attribute is valid
21 Action Rule Examples Transformation Rule Example: After a user pays, ship the products and deduct the quantity from product inventory. Validation Rule Example: The product inventory must be greater than zero.
22 InitialDerivation Rule Describes initialization value of an class attribute. Example: The first customer ID is 1000
23 SelfDerivation Rule Describes how an attribute value is derived from former instances value on the same attribute. Example: a new customer ID = max(customerID) + 1
24 IndirectDerivation Rule Describes how the value of one attribute is derived by some other attributes through a mathematic formula or inference. Example: invoice total value = product total value + tax value – discount
25 Rule Automation Technologies Java Technology - Ensures portability and vendor independency Enterprise Java Beans - Simplifies building of distributed application MS-SQL 6.5 as back-end database
31 Rules in MCPS (1) Validation Rule The account balance must be greater than 0. Transformation Rule After generating an invoice, deduct the users account balance by the invoice amount.
32 Rules in MCPS (2) InitialDerivation Rule The customer ID for the first customer is 1000. The account ID for the first account is 1000. The invoice ID for the first invoice is 1000.
33 Rules in MCPS (3) SelfDerivation Rule A new customer ID is the current maximum customer ID add one. the rule for new account ID the rule for new invoice ID
34 Rules in MCPS (4) IndirectDerivation Rule The Shipping fee is $20 for each order. The tax value is 15% of the product total value
35 Rules in MCPS (5) IndirectDerivation Rule The invoice total value is the amount of product total value, tax value, and shipping fee.
36 Rules in MCPS (6) IndirectDerivation Rule If a customer buys products worth more than $100, he will get a 10% discount.
37 Case Build Procedure Test and Modification Object model for business logic tier Object Model for Presentation tier Business rules Generate beans Write ShoppingCart session bean Build rules Arrange rule sequence Write Jsp files Design Develop
38 MCPS Architecture (Technology View) HTTP Request HTML WorkStation Browser Application Server Database Java Bean JSP Session bean Rule Engine Entity Bean UI Logic Business Logic
39 Metrics Analysis Line Of Code (Loc) CPSMCPS (Hand- coded ) Hand-code Percentage Java Files 864313774158812% JSP Files 93161159 100% Deployment Files 681102590.1% Other 315 Overall 1895515958275617%
40 RAAS Features (1) 3-tier architecture Automatically triggers the rules at run time Changes the rules without re-deploying the application systems
41 RAAS Features (2) Decides rule sequence for IndirectDerivation rules Re-evaluates rules based on changed conditions
42 Contributions Proposed a general and extensible business rule model Explored a component-based distributed business rule framework
43 Future Work Enhance the rule model Performance issue Extracting rules from legacy system and specification documents