Modeling Flexible Business Processes with Business Rule Patterns Milan Milanović 1 , Dragan Gašević 2 , Luis Rocha 2 1 University of Belgrade, Serbia 2 Athabasca University, AB, Canada https://semtech.athabascau
Jan 19, 2015
Modeling Flexible Business Processes with Business Rule Patterns
Milan Milanović1, Dragan Gašević2, Luis Rocha2
1University of Belgrade, Serbia2Athabasca University, AB, Canada
https://semtech.athabascau.ca
Motivation Modeling flexible business process
Integration of rules in processes
Motivation Modeling flexible business process
Integration of rules in processes Patterns for Rules in BPs [Graml et al., 2007]
Control flow decisions
Control flow decisions
Rule types
DR IR PrR
Control flow decisions
Decision logic abstraction + Decision node to business rule binding + Decision with flexible input data + Decision flexible output + +
Data constraints
Constraints at predefined checkpoint + Constraints at multiple checkpoints + Constraints enforced by external data context +
Dynamic BP composition
Business rule-based subprocess selection +
Business rule-based process composition + +
Rule and Processes Observations
Implementation focus primarily Development complexity Weak integration with information modeling Questionable declarative definition of rules
To what extent can a rule-enhanced
business process modeling language address the observed problems
MODELS 2009
Research Objective
Rule-enhanced BP modeling language Integrates BPMN2 and R2ML (EDOC 2009)
Improved expressivity (BuRO 2010) A rule can be associated with a flow element Advice-like types – before, after around
Models rule-enhanced Orchestrations (CASCON 2009) Choreographies (EDOC 2010)
rBPMN
Rule Modeling REWERSE I1 Rule Markup Language (R2ML)
with a UML-based graphical concrete syntax
MODELS 2009
REWERSE I1 Rule Markup Language
MODELS 2009
Extension for Rule Models
rBPMN metamodel weaving
rBPMN Example
rBPMN Example
http://code.google.com/p/rbpmneditor/
rBPMN Editor
http://code.google.com/p/rbpmneditor/wiki/Patterns
Control Flow Decisions Decision logic abstraction pattern
Data Constraints Constraints at multiple checkpoints
Data Constraints Constraints at multiple checkpoints
Data Constraints Constraints enforced by external data context
Dynamic BP Composition Business rule-based subprocess selection
Dynamic BP Composition Business rule-based subprocess selection
Book Store Case Study
Case Study – Book Store
Case Study – Book Store
Constraints at predefined checkpoint
Case Study – Book StoreDecision point abstraction pattern
Case Study – Book Store
Rules in the process Reaction rules attached to R2
Case Study – Book Store
Case Study – Book StoreDecision node to business rule binding
Case Study – Book Store
Case Study – Book StoreSub-process selection
ComparisonPattern group Pattern name Original rBPMN
DR IR PrR DR IR PR RR
Control flow decisions
Decision logic abstraction + + +
Decision node to business rule binding + + + Decision with flexible input data + + + Decision flexible output + + +
Data constraints
Constraints at predefined checkpoint + +
Constraints at multiple checkpoints + + Constraints enforced by external data context + + +
Dynamic BP composition
Business rule-based subprocess selection + +
Business rule-based process composition + + + +
Systematic rules & process modeling Same abstraction level & shared vocabularies Declaratively expressed rules Higher potential for BP flexibility
MODELS 2009
Conclusion
Formal verification of rBPMN processes Petri Nets and well-formedness
Executable rBPMN Concrete syntax
Reduction of the graphical concrete syntax Semi-structure English for rules Controlled experiments
Maintainability and usability
MODELS 2009
Future Work
Thank you!
Questions?
https://semtech.athabascau.ca