1 automating business rule adaptation for web-based information systems mei tian 1, ajit singh 2,...

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Automating Business Rule Adaptation for

Web-Based Information Systems

Mei Tian1, Ajit Singh2,

Kumaraswamy Ponnambalam1, Raymond Lee2

1Systems Design Engineering, University of Waterloo

2 Electrical and Computer Engineering, University of Waterloo

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Presentation Outline

• Introduction

• Business Rule Model

• Implementation

• Case Study

• Future Work

3

Web-Based Information Systems

back-end database

business logic

middleware

client application

JRMPhttp

• 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

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Research Subareas

• Business rule representation

• Business rule extraction

• Business rule management

• Business rule processing

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Research Background

• Business rules representation

External

Conceptual

Internal

Users,analyzers Structured English, etc.

Designer, developer BRML, etc.

Physical machine Binary code

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Research Background

• Business rule extraction

• Data analyzing

• Programming analyzing

• Hybrid

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Research Background

• Business rule management

• Repository-based method

• artificial Intelligence

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Research Background

• Business rules processing

• Procedural programming

• SQL trigger

• Declarative programming

• Constraint programming

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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

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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

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Solution Strategies (1)

• A general business rule model

• A rule system and a distributed business

rule framework

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Solution Strategies (2)

• A EJB design pattern and the bean

relationship information

• Rule dependency graph, rule-firing-

history, and rule label

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Business Rule Model

OrganizationModelname: String

ruleType: Stringpriority: StringtriggeredClass: StringtriggerMethod: StringtriggerLocation: Stringimplementor: Stringdescription: String

name: Stringeffective:Dateexpiration:Date

BusinessRuleSet

BusinessRule1*

* 1 CommonKnowledge

Model

*

*

1

*

TermRule FactRule ActionRule DerivationRule

ApplicationRuleSet

appName:String setName:Stringsource:String

ShareRuleSet

RuleChecker

description: String 1 *

Legend: class * 1 Many-to-one association generalization

Implementer1*ruleName:String

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Business Rule Types

TermRule FactRule ActionRule DerivationRule

name: StringruleType: Stringpriority: StringtriggeredClass: StringtriggerMethod: StringtriggerLocation: Stringimplementor: StringDescription: String

BusinessRule

TransformationRule

InitialDerivationRule

SelfDerivationRule

IndirectDerivationRule

InferenceRule

ValidationRule

Legend: class generalization

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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.

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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.

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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

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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.

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InitialDerivation Rule

• Describes initialization value of an class attribute.

• Example:

The first customer ID is “1000”

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SelfDerivation Rule

• Describes how an attribute’ value is derived from former instance’s value on the same attribute.

• Example:

a new customer ID = max(customerID) + 1

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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

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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

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Enterprise Java Beans

• Server-side component architecture

• Simplifies building distributed applications

• Enterprise beans

- Entity beans

- Session beans

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Rule Adaptation Automation System

Rule Engine

Application Server

Rule Builder

Rule Beans

Rule Adaptation Automation System

HTTP

JDBC

EJB Beans Generator

JDBC

Deploy

EJB Finder

Rule Repository

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Case: Maria’s Computer Product Store

• User authentication

• An Online catalogue and shopping cart

• Invoice generation

• Bill Functionality

• Special price promotion

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MCPS-Business Flow

Login

User Profile

Product List View Shopping Cart

Check Out

Invoice

Rule Execution Feedback

New Customer

Service List

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MCPS-Object Model (Business Logic Tier)

Account Wrapper

Customer Wrapper

Invoice Wrapper

Account Customer Invoice

ShoppingCart

Transactions Transactions Wrapper

Product

Product Wrapper

1

1

1

1

1

1

1

1

1

* 1

1

1

*11

1

1

1 *1 1

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Rules in MCPS (1)

• Validation Rule

• The account balance must be greater than 0.

• Transformation Rule

• After generating an invoice, deduct the user’s

account balance by the invoice amount.

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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.

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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

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Rules in MCPS (4)

• IndirectDerivation Rule

• The Shipping fee is $20 for each order.

• The tax value is 15% of the product total value

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Rules in MCPS (5)

• IndirectDerivation Rule

•The invoice total value is the amount of product total value, tax value, and shipping fee.

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Rules in MCPS (6)

• IndirectDerivation Rule

• If a customer buys products worth more than $100, he will get a 10% discount.

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Case Build Procedure

Test andModification

Object model for business

logic tier

Object Model for

Presentationtier

Business rulesGenerate beans

Write ShoppingCartsession bean

Build rulesArrange

rule sequenceWrite Jsp files

Design

Develop

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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

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Metrics Analysis 

Line Of Code (Loc)

CPS MCPS MCPS(Hand-

coded)

Hand-codePercentage

Java Files 8643 13774 1588 12%

JSP Files 9316 1159 1159 100%

Deployment Files 681 1025 9 0.1%

Other 315      

Overall 18955 15958 2756 17%

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RAAS Features (1)

• 3-tier architecture

• Automatically triggers the rules at run time

• Changes the rules without re-deploying the

application systems

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RAAS Features (2)

• Decides rule sequence for IndirectDerivation rules

• Re-evaluates rules based on changed conditions

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Contributions

• Proposed a general and extensible business rule model

• Explored a component-based distributed business rule framework

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Future Work

• Enhance the rule model

• Performance issue

• Extracting rules from legacy system and specification documents

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Questions ??