Drools Introduction - rules engine - drools tutorial - business rules engine

• Java enterprise level application can be divided into three parts
• UI - User Interface (Frontend)
• Service layer which is in turn connected to a database
• Business layer
• We have a number of frameworks that handle the UI and service layer together, for example, Spring and Struts.
• Yet, we did not have a standard way to handle the business logic until Drools came into existence.

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• Drools is a Business Logic integration Platform (BLiP). It is written in Java.
• It is an open source project that is backed by JBoss and Red Hat, Inc.
• It extends and implements the Rete Pattern matching algorithm.
• In layman’s terms, Drools is a collection of tools that allow us to separate and reason over logic and data found within business processes.
• The two important keywords we need to notice are Logic and Data.


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• Drools is split into two main parts: Authoring and Runtime.
• Authoring: Authoring process involves the creation of Rules files (.DRL files).
• Runtime: It involves the creation of working memory and handling the activation.

• Drools is Rule Engine or a Production Rule System that uses the rule-based approach to implement and Expert System.
• Expert Systems are knowledge-based systems that use knowledge representation to process acquired knowledge into a knowledge base that can be used for reasoning.
• A Production Rule System is Turing complete with a focus on knowledge representation to express propositional and first-order logic in a concise, non-ambiguous and declarative manner.
• The brain of a Production Rules System is an Inference Engine that can scale to a large number of rules and facts.
• The Inference Engine matches facts and data against Production Rules - also called Productions or just Rules - to infer conclusions which result in actions.
• A Production Rule is a two-part structure that uses first-order logic for reasoning over knowledge representation.
• A business rule engine is a software system that executes one or more business rules in a runtime production environment.
• A Rule Engine allows you to define “What to Do” and not “How to do it.”

• Rules are pieces of knowledge often expressed as, "When some conditions occur, then do some tasks."

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• The most important part of a Rule is it’s when part. If the when part is satisfied, the then part is triggered.

• The process of matching the new or existing facts against Production Rules is called Pattern Matching, which is performed by the Inference Engine.
• There are a number of algorithms used for Pattern Matching including:
• Linear
• Rete
• Treat
• Leaps
• Drools Implements and extends the Rete Algorithm.
• The Drools Rete implementation is called ReteOO, signifying that Drools has an enhanced and optimized implementation of the Rete algorithm for object-oriented systems.

• Rules make it easy to express solutions to difficult problems and get the solutions verified as well.
• Unlike codes, Rules are written in less complex language; Business Analysts can easily read and verify a set of rules.

• The data resides in the Domain Objects and the business logic resides in the Rules.
• Depending upon the kind of project, this kind of separation can be very advantageous.

• The Rete OO algorithm on which Drools is written is already a proven algorithm.
• With the help of Drools, your application becomes very scalable.
• If there are frequent change requests, one can add new rules without having to modify the existing rules.

• By using Rules, you create a repository of knowledge (a knowledge base) which is executable.
• It is a single point of truth for business policy.
• Ideally, Rules are so readable that they can also serve as documentation.

• Tools such as Eclipse provide ways to edit and manage rules and get immediate feedback, validation, and content assistance. Auditing and debugging tools are also available.