This document discusses managing business logic using rule-based technologies. It provides a brief history of rule-based systems starting in the 1970s. Production rules use an if/then structure to represent logic. Rule engines allow dynamic changes to rules separate from software development and provide a single source of business rules. Pattern matching is key to rule engines, which can be used for applications like insurance underwriting and fraud detection. Popular rule engines include CLIPS and Drools.

1. “Managing Business Logic
with rule based
technologies”
Michael Neale
OSDC – Sydney - 2008

2. And a little about me:
“first Australian JBoss Employee”
Was lonely for a while (but now we are part of Red Hat
family !).

3. Rules/Expert Systems
•Were once delivered as expert system shells
•Extract logic “out of code”
•Explicit rules
•“On the fly” changes to rules

4. History
•1970's – MYCIN
•Production Rules
•Generalised into a “shell” that can be re-used
•90's - “business rule engines”

5. Production Rules
•if/when <condition> then <action>
•Logic programming
•Logical chaining
•
•(you may remember prolog)

6. Why bother?
•“Greenspunning”
•Have been in use for some time
•Being declarative is (often) good for you

7. When to use
•Domain expertise available
•Dynamic changes to rules separate from SDLC
•One point of truth for “the business rule”

8. Pattern Matching
•Pattern matching is central
•... but a quality “model” is needed
•results in looser coupling
•... which means longer term change tolerance

10. Engines
... inference or scripting engine?

11. Scripting approach
Simple, easy

12. Higher order logic
•Higher order logic
•Dealing with knowledge bases with lots of “static” data
•RETE algorithm (an optimisation)

13. Rete

14. Changed facts
Stable facts
Rules
“Agenda”
Rules finding facts or facts finding rules?

15. Example applications
•Underwriting, pricing insurance
•Real time traffic monitoring and recommendation
•Mortgage pricing
•Claim (insurance) process legal compliance
•VISA, Mastercard fraud detection
•Logistics routing

16. User interface
“visual metaphors”

18. A dose of reality
•Over-promising in the 90's
•Underdelivering
•“who needs a programmer”

19. CLIPS
Thanks NASA !
(defrule engine-sluggish ""
(engine-sluggish yes)
(not (repair ?))
=>
(assert (repair "Clean the fuel line.")))
(defrule engine-misfires ""
(engine-misfires yes)
(not (repair ?))
=>
(assert (repair "Point gap adjustment.")))

20. Clips integration
•Shell or command line style
•Detailed C API and sample code
•clips.h
•Embed it in your native apps

21. Drools
•Targets JVM (also a .Net port) at present
•Originated from codehaus community (now jboss)
•Has developer + analyst tools

22. Drools example
rule engine-sluggish
when
Engine(sluggish = true)
not Repair()
then
insert(new Repair(“clean fuel line”))
end
rule engine-misfires:
when
Engine(misfires=true)
not Repair()
then
insert(new Repair(“Point gap adjustment”))
end

23. Thanks...
Questions?
michaelneale.blogspot.com
twitter.com/michaelneale
http://friendfeed.com/rooms/osdc