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Chapter 18 Process Configuration. Florian Gottschalk Marcello La Rosa. Overview. Introduction to Configurable Process Models Process Configuration in YAWL Questionnaire-driven Approach for Process Configuration Tool Support Conclusions. What is a configurable process model?.
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Chapter 18Process Configuration Florian Gottschalk Marcello La Rosa
Overview • Introduction to Configurable Process Models • Process Configuration in YAWL • Questionnaire-driven Approach for Process Configuration • Tool Support • Conclusions
What is a configurable process model? Integrated representation of multiple variants of a same process in a given domain, which can be configured for a specific setting, leading to an indivi-dualized process model. commonality = + variation point variability Tape variant Film variant
Configurable Process Models in the Process Lifecycle design configuration individualization implementation execution
Features of a Configurable Process Model • should guide the user to a model that fits his requirements • must be able to generate all possible process variants • must be a complete, integrated set of all possible process variants • is the least common multiple of all process variations
A Theoretical explanation Inheritance Inheritance Configuration Configuration Inheritance of workflow behavior: Superclass Variant A Configurable Model Subclass Variant B Superclass
Configuration Techniques • Blocking • Hiding • also called skipping block block τ hide τ hide τ hide
Port Configuration enabled Ports hidden (skipped) blocked Task
Port types in YAWL • Flow of tokens is determined by functions assigned to a YAWL task: • join input ports • split output ports • rem cancellation port • nofi multiple instance configuration
Input ports (inflow) • XOR-join • Task is enabled if a token arrives from any arc • One input port for each incoming arc • AND-join • Task is enabled if tokens are arriving from all arcs • One input port for the whole task • OR-join • Task is enabled if tokens are arriving from all arcs from which a token can potentially arrive • One input port for the whole task
Output ports (outflow) • XOR-split • Task releases one token via one of the arcs • One output port for each outgoing arc • AND-split • Task releases tokens via all arcs only • One output port for the whole task • OR-split • Task can release tokens via any combination of outgoing arcs • One output port for every combination of outgoing arcs
Configuration Example (A, B, C, E) (A, B, C, E) or (A, B, D, E) (B, C, E)
Cancellation ports (inflow) • Cancellation also represents an inflow of tokens, but can also take 0 tokens • Takes the maximum number of available tokens, similar to the OR-join • One cancellation port for the whole task • Hiding of Cancellation ports makes no sense • No skippable action between the activation of the cancellation port and the outflow of tokens
Multiple Instance configuration • Increase of the minimal number of instances to be started • Decrease of the maximal number of instances to be started • Increase of the threshold value • Restrict dynamic creation of instances to static creation
Multiple Instance configuration • Increase of the minimal number of instances to be started • Decrease of the maximal number of instances to be started
Multiple Instance configuration • Increase of the threshold value
Multiple Instance configuration dyn • Restrict from dynamic to static instance creation
Questionnaire-driven configuration • Configuring a process model can be difficult and time-consuming, due to: • size of the variability space, • complexity of the domain. • Domain experts usually have little or no knowledge about modeling notations (e.g. in the screen business). • Need to facilitate the configuration of process models by domain experts, without requiring process modeling knowledge.
Questionnaire-based approach • Configuration can be simplified if carried out by answering a set of questions no need to be aware of modeling notations. • The basic concepts of the approach are questions and domain facts: • a question is composed of a set of domain facts; • a domain fact encodes a business choice and can be set to “true” or “false”. • Variation points in the process model are mapped to boolean expressions over domain facts. • Questions may affect one or multiple variation points:
Domain constraints • The configuration space of the domain is restricted by a set of propositional logic domain constraints over the domain facts. • By means of domain constraints, answers to questions may be determi- ned by previous answers. DC10: f11 f12 DC11: f10⇒ f12 DC11 DC10
Mapping process models to questionnaire models A mapping links process facts to domain facts: C-EPC C-YAWL The mapping ensures domain compliance and process model correctness.
Constraints in action MC22: pON⇔ f13 MC25: pON⇔ f15 d e PC4 DC6 DC8 MC22 MC25 Mapping Process constraints Domain constraints c4 DC6: f5⇒ f13 PC4: pON⇒ pSEQ d b4 DC8: f8⇒ f15
Application of the approach Mapping Questionnaire model + = input to answers Individualized Model Interactive Questionnaire Configurable Process Model
Tool support: Synergia • Open-source • Modular: 6 standalone applications, • Provides end-to-end support for process model configuration, • Independent of specific modeling notations, • Supports C-EPC and C-YAWL.
Discussion • Is there a need for configurable models? • Do you have the same experience that highly-standardized processes (such as the Order Fulfillment example) are still adapted to individual needs? • Is it feasible to create configurable models? • What do you think about how we individualized the Order Fulfillment model compared to the intended use of your software? • Are configurable models useful? • Can you imagine that you provide similar models which can be adapted “without drawing arcs and nodes”?
Conclusions • Process Configuration is a viable mechanism to automate the derivation of customized models from a reference model in a specific domain • Process Configuration in YAWL is grounded in the concept of Inheritance of Workflow Behavior and is achieved via 2 operators: hide, block • The Questionnaire-based approach facilitates the configuration of (complex) process models such as the Order Fulfillment example by non-modeling experts • Tool support is available with the Synergia toolset
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