large process models and process model collections ... · large process models and process model...
TRANSCRIPT
Manfred Reichert, Barbara Weber, Victoria Torres
Large Process Models and Process Model Collections: - Challenges, Methods, Technologies -
Barbara Weber Victoria Torres Manfred Reichert
Presenters
Barbara Weber [email protected] University of Innsbruck
Manfred Reichert [email protected] University of Ulm
Victoria Torres [email protected] Polytechnic University of Valencia
Agenda
Challenges & Basic Notions
Part I: Large Process Models
Part II: Large Process Model Collections
Part III: Large Process Structures
References
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Large Process Models – An Example!
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Process Model
Process model
Node
Activity Event Control connector
Control edge
Data object
Atomic activity Complex activity Resource
Operation
contains
connect
is a is a is a
executes
contains
is a is a
input
output
contains
describes
Process model
Node
Activity Event Control connector
Control edge
Data object
Atomic activity Complex activity Resource
Operation
contains
connect
is a is a is a
executes
contains
is a is a
input
output
contains
describes
operational
structural Process Model
Process model
Node
Activity Event Control connector
Control edge
Data object
Atomic activity Complex activity Resource
Operation
contains
connect
is a is a is a
executes
contains
is a is a
input
output
contains
describes
operational
structural Process Model
Process model
Node
Activity Event Control connector
Control edge
Data object
Atomic activity Complex activity Resource
Operation
contains
connect
is a is a is a
executes
contains
is a is a
input
output
contains
describes
operational
structural Process Model
Process model
Node
Activity Event Control connector
Control edge
Data object
Atomic activity Complex activity Resource
Operation
contains
connect
is a is a is a
executes
contains
is a is a
input
output
contains
describes
operational
structural Process Model
Process model
Node
Activity Event Control connector
Control edge
Data object
Atomic activity Complex activity Resource
Operation
contains
connect
is a is a is a
executes
contains
is a is a
input
output
contains
describes
operational
structural Process Model
Process model
Node
Activity Event Control connector
Control edge
Data object
Atomic activity Complex activity Resource
Operation
contains
connect
is a is a is a
executes
contains
is a
input
output
contains
describes
operational
structural Process Model
is a
Process Model Collections
Process Model Collections
Sets of process models – Sharing goals
• Collections of process model variants – Targeted at different stakeholders
• Collections of process model user views – Described at different abstraction levels
• Collections of process model at different level of detail – Dealing with process model evolution
• Collections of process model versions – Stored within the same repository
• Collections of enterprise process models
--
15
Process Structures
System
Komponente Komponente Komponente
System
Gesamtsystem
SoftwareModultest
SoftwareDesign
Software Implementierung
KomponentenSpezifikation
KomponentenTest
SystemSpezifikation
SystemIntegration
SystemEntwurf
FahrzeugErprobung
Testfälle
Testfälle
Testfälle
Testfälle
Process Structures
Lifecycle Phases
Lifecycle Phases
Analysis & Design – BP identification and modelling
• Based on domain requirements • BP Modelling notation and languages
– Validation & Verification • Simulation techniques support Validation
» Resulting artefact: BP model
» Fostering communication between different stakeholders
Lifecycle Phases
Configuration – Implementation of BP models – Implementation platform has to be chosen – BP model preparation for enactment
• Interaction with the enterprise eco-system – users & existing systems
• Tests to check desired behaviour
» Resulting artefact: Ready-to-enact BP model
Lifecycle Phases
Enactment – BP instance execution
• Guaranteeing BP model constraints compliance – Monitoring & Visualizing techniques
• Allow discovering the status of active BP cases
» Resulting artefacts: » Business Process instances » Execution logs
Lifecycle Phases
Diagnosis – Analysis of execution logs
• Identification of poor quality designs – Fragments that are not used at all
• Identification of problems regarding execution environment adaptation
» Resulting artefact: Process model and configuration changes report
Lifecycle Phases
Evolution – Application of changes to BP models based on
• New requirements • Improvement opportunities
» Resulting artefact: BP Model more accurate to the BP and its environment
Agenda
Challenges & Basic Notions
Part I: Large Process Models
Part II: Large Process Model Collections
Part III: Large Process Structures
References
Challenge: Large Process Models
Challenge: Understanding process models of large size
Typical Quality Problems Process Model Smells
Process Model Smells PMS1: Non-intention Revealing Naming of Activities / Process Model
PMS2: Contrived Complexity
PMS3: Redundant Process Fragment
PMS4: Large Process Models
PMS5: Lazy Process Models
PMS6: Unused Branches
PMS7: Frequently Occurring Instance Changes
PMS8: Frequently Occurring Variant Changes
(Weber and Reichert 2008, Weber et al. 2011)
Refactoring Large Process Models
Identification of Process Model Smells
Application of Refactoring Techniques
RF1: Rename Activity
RF2: Rename Process Schema
RF3: Substitute Process Fragment
RF4: Extract Process Fragment
RF5: Replace Process Fragment by Reference
RF6: Inline Process Fragment
RF7: Re-label Collection
RF8: Remove Redundancies
Refactoring Techniques
Process Model Refactorings
(Weber and Reichert 2008, Weber et al. 2011)
Labeling of Process Models
PMS1. Non intention revealing naming of activities / process models
– Ambiguous or non intention revealing labels
– Inconsistent use of labeling styles
(Weber et al. 2011)
Example of Poor Labeling in SAP Reference Model
Poor labeling may lead to ambiguities – Plan a data transfer? or
– Transfer plan data?
Leopold et al. 2011
Number of ways students name an activity in a process model
Insights from a process modeling experiment with 113 students.
The following sentence in the process description
“Afterwards the scouting team attends games of the player they are interested in live in the football stadium.” resulted into 84 different ways for naming this particular activity.
Fahland 2012
Guidelines for Labeling of Process Models
Many guidelines stress the importance of proper labeling
(Malone 2003, Sharp and McDermott 2008)
Empirical insights show that verb-object style is best understandable
(Mendling et al. 2010)
Automatic Refactoring of Labels
Labels are automatically refactored from action-noun style to labels in verb-object style
(Leopold, Smirnov, and Mendling 2012)
Refactorings RF1: Rename Activity
RF7: Re-label Collection
Plan data transfer to EPC-PCA from profitability
analysis
Transfer plan data to EPC-PCA from
profitability analysis
Structured versus Unstructured Business Process Models
PMS2. Contrived Complexity – Unstructured process fragments are more difficult to
understand than well-structured ones (Mendling, Reijers, van der Aalst 2010)
Unstructured Process Model
Structured versus Unstructured Business Process Models
Unstructured Process Model
Well-structured Process Model
Automatic transformation of unstructured into structured model (Polyvyanyy et al. 2012)
Refactoring RF2: Substitute Process Fragment
Structured versus Unstructured Business Process Models
PMS2. Contrived Complexity – Process Fragments are syntactically often different,
but semantically equivalent (Gert et al. 2010)
(Gert et al. 2010)
Structured versus Unstructured Business Process Models
Automatic detection of semantically equivalent process fragments (Gert et al. 2010)
Refactoring RF2: Substitute Process Fragment
Redundant Process Fragments
PMS3: Redundant Process Fragments
– Clones can be commonly found in existing process models
(Dumas et al. 2012, Weber et al. 2011)
– More than 560 clones in the SAP reference model (Dumas et al. 2012, Weber et al. 2011)
Redundant Process Fragments
(Dumas et al. 2012)
Redundant Process Fragments
(Dumas et al. 2012)
Redundant Process Fragments
Method for automatically detecting exact clones (Dumas et al. 2012)
Detected clones can be automatically extracted to sub processes
Refactoring RF4: Extract Process Fragment RF5: Replace Process Fragment by Reference RF8: Remove Redundancies
Large Process Models
PMS4: Large Process Models – Literature reports about process models with several
hundred activities (Soto et al. 2008)
– Large process models tend to comprise more formal flaws than smaller ones (Mendling et al. 2008)
Large Process Models
Method for automatic modularization of business process models (Reijers et al. 2011)
Method for the automatic labeling of process models (Leopold et al. 2011)
Refactoring RF4: Extract Process Fragment RF5: Replace Process Fragment by Reference RF8: Remove Redundancies
Hierarchy in Conceptual Models Common Belief versus Empirical Evidence
Modularization is a widely used strategy to reduce
complexity in conceptual models
Hierarchical structures supported by many conceptual modeling languages
Empirical evidence on the benefits of hierarchy are contradictory
Hierarchisation in Conceptual Models A Systematic Literature Review
Work Findings Moody [15] Domain: ER-Models
Positive influence on accuracy, no influence / negative influence on time
Reijers et al. [16, 17] Domain: Business Process Models
Positive influence on understandability for one out of two models
Cruz-Lemus et al. [9, 18] Domain: UML Statecharts
Series of experiments, positive influence on understandability in last experiment
Cruz-Lemus et al. [13] Domain: UML Statecharts
Hierarchy depth of statecharts has no influence
Shoval et al. [14] Domain: ER-Models
Hierarchy has no influence
Cruz-Lemus et al. [8] Domain: UML Statecharts
Positive influence on understandability for first experiment, negative influence in replication
Cruz-Lemus et al. [12, 19] Domain: UML Statecharts
Hierarchy depth has a negative influence
(Zugal et al. 2011a)
Hierarchisation in Conceptual Models A Systematic Literature Review
Work Findings Moody [15] Domain: ER-Models
Positive influence on accuracy, no influence / negative influence on time
Reijers et al. [16, 17] Domain: Business Process Models
Positive influence on understandability for one out of two models
Cruz-Lemus et al. [9, 18] Domain: UML Statecharts
Series of experiments, positive influence on understandability in last experiment
Cruz-Lemus et al. [13] Domain: UML Statecharts
Hierarchy depth of statecharts has no influence
Shoval et al. [14] Domain: ER-Models
Hierarchy has no influence
Cruz-Lemus et al. [8] Domain: UML Statecharts
Positive influence on understandability for first experiment, negative influence in replication
Cruz-Lemus et al. [12, 19] Domain: UML Statecharts
Hierarchy depth has a negative influence
Under which circumstances can positive / negative influcences on understandability be expected?
Understanding Process Models Some Insights from Cognitive Psychology
Answering questions about a model
is a problem solving task
Three different problem solving processes (Larkin and Simon 1987) – Search – Recognition – Inference
Limitations of Working Memory
Central Concept: Working Memory
– Required by all conscious mental activities – Mental effort: utilization of working memory – Severely limited: 7 +/- 2 information „slots“ (Miller 1956) – Overflow: rapid performance decrease! (Sweller 1988) – Mental effort: amount of working memory used
(Paas et al. 2003)
Two Opposing Forces
Abstraction – hiding of irrelevant information (Parnas 1972) – supports human mind’s attention management
(Larking and Simon 1987)
Split-attention effect (Sweller and Chandler 1994) – Occurs when information from several sources needs
to be integrated – switching attention between models
Theoretical Framework for Measuring Understandability
question complexity
mental effort abstraction lowers
includes
hierarchy split-attention effect
performance
enables
causes
increases
determines
(Zugal et al. 2011a)
Hierarchical Model – Abstraction Question
'Define the problem' can be executed after 'Check if problem is already solved'.
Sub Process: Do Systematic Literature Review
Flat Model – Abstraction Question
'Define the problem' can be executed after 'Check if problem is already solved'.
Hierarchical Model – Fragmentation Question
'Describe initial approach' can be executed after 'Compile classification statistics'.
Sub Process: Do Systematic Literature Review
Flat Model – Fragmentation Question
'Describe initial approach' can be executed after 'Compile classification statistics'.
Hierarchisation is Always a Trade-off
Modularization is always a trade-off!
Also the optimal modularization can only increase the “average” understanding! – Some questions become easier to answer – Some questions become harder to answer
(Zugal et al. 2011a, Zugal 2011b, Zugal 2011c)
Hierarchisation is Always a Trade-off
Modularization is always a trade-off!
Also the optimal modularization can only increase the “average” understanding! – Some questions become easier to answer – Some questions become harder to answer
Dynamic modularization / visualization / navigation is needed !
(Zugal et al. 2011a, Zugal 2011b, Zugal 2011c)
The Role of External Memory
External memory – mechanism for reducing mental effort – Information storage outside the human
cognitive system (e.g., pencil and paper or a blackboard)
Cognitive Trace – Information taken from working memory
and stored in an external memory (e.g., to mark, update, and highlight information)
The Role of External Memory
External memory – mechanism for reducing mental effort – Information storage outside the human
cognitive system (e.g., pencil and paper or a blackboard)
Cognitive Trace – Information taken from working memory
and stored in an external memory (e.g., to mark, update, and highlight information)
For process models of large size tool support, which enables to offload information, is essential.
Visualizing and Abstracting Large Process Models
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39
modify CR
initiate CR request expertise
generate expertise
generate expertise
generate expertise
generate expertise
request evaluation
provide evaluation
provide evaluation
provide evaluation
request comments
provide comments
provide comments
provide comments
provide comments
approve CR instruct realisation conclude CR
approve CR instruct realisation conclude CRblack box
(legacy application)
manual(remodelling)
direct import
modify CR
initiate CR request expertise
generate expertise
generate expertise
generate expertise
generate expertise log-data
Miningindirect
Visualization Component
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üBBB
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ü
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Kost
en >
100
Kost
en ≤
100
Dok 73BDok 73B
Fr. Tschek Hr. Apruf Fr. Tschek Hr. Apruf Fr. Tschek
Fr. Tschek
Hr. Alau Hr. Alau
Prozess: Genehmigung ÄnderungAntrag B25KS vom 31.9.2005 Status 11.12.2005
09.11.2005 15.11.2005
24.11.2005 30.11.2005
08.12.2005
Prüferg.: OK
Genehmigung Änderung
ID Aktivität Anfang Abschluss DauerQ4
1 üAbt. XY-A7t09.11.200501.11.2005AAA
2 üAbt. XY-C4t15.11.200510.11.2005BBB
3 üAbt. XY-B7t24.11.200516.11.2005CCC
4 üAbt. XY-B4t30.11.200525.11.2005DDD
5 ûAbt. XY-A12t01.12.200516.11.2005EEE
6 üAbt. XY-A5t08.12.200502.12.2005FFF
7 }Abt. XY-C5t15.12.200509.12.2005GGG
8 Abt. XY-A6t23.12.200516.12.2005HHH
Abt. XY-A
Abt. XY-C
Abt. XY-B
Abt. XY-B
Abt. XY-A
Abt. XY-A
Abt. XY-C
Abt. XY-A
Bearbeiterheute
Antrag B25KS vom 31.9.2005
Status 11.12.2005
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XY.B
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XY-A
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≤ 100
Prozess: Genehmigung ÄnderungAntrag B25KS vom 31.9.2005 Status 11.12.2005
Process Visualization What is needed?
adapt display form (diagram, form, table, text, …)
abstracting information (process views)
adapting visual appearance (symbols, colors, …)
Process Visualization Dimensions
Process Visualization Abstracting Process Models: Goals
reduction aggregation
Goals: Decreasing the complexity of (large)
process models Eliminating or abstracting process
information
► Personalize process models through process views
Process views should be …
− easy to define − dynamically built if required
P1 P2 P3 P4
B FD
GEA
C
LH IX Y
Z
Y
Z X XXX Z K
J
Y
Z
EA LH IX X XXX
Process Visualization Abstracting Process Models: Goals
Reduction Eliminate activities Simplify the resulting schema Remove adjacent satellite objects
Aggregation Aggregate activities Aggregate adjacent objects if required
C
KI
HF
E
J
GA
D
LB
D1
D2 D3 D4
D5
X Y
X
Y Y
Y X
Z
Z
Z
Z
YC
I
HF L
D1
D2 D3 D4
D5
Y Y Y
Y
Y
CI
HF
L
D2 D4
D5
Y
Y Y
Y
Y
C
KI
HF
E
J
GA
D
LB
D1
D2 D3 D4
D5
X Y
X
Y Y
Y X
Z
Z
Z
Z
ZC
KI J
L
D1
D2 D3 D4
D5
X,Z Y
X,Y,Z
Y X
ABDEFGH
Z
Z
CKI J
L
D1D234
D5
Y
Y X
ABDEFGH
X,Z
X,Y,Z
Z
Z
Process Visualization Abstracting Process Models: Fundamental Techniques
Bobrik et al., 2007
Process Model Abstraction and Process Views in Proviado
(Bobrik, Bauer, & Reichert, 2007; Reichert et al., 2012)
Related approaches, e.g.,
– Smirnov, Reijers & Weske, 2011 – Eshuis & Grefen, 2008 – Schumm, Latuske & Leymann, 2011
Process Visualization Abstracting Process Models: The Proviado Approach
Attri
bute
Op.
High-level Operations
Data
Flo
w O
p.
Multi-Aspect Operations
Single-Aspect Operations
Elementary Operations
AGGREGATECF REDUCECF
Aggregate Reduce
ShowMyActivities ...AggrExecutedPart
Control Flow Attributes Application DataProcess
AggrSESEAggrShiftOut
AggrAddBranchRedActivity
AggrComplBranch...
...
...
Process Visualization Abstracting Process Models: The Proviado Approach
• A multi-layer approach for abstracting process models and building process views
C D EA
C D EBA
D EA
A E
RedActivity(B)
RedActivity(C)
RedActivity(D)
BA
rs
t
BA
r ∨ st
ReduceCF({B,C,D})
AB
C
AC
s
t
s
t
AD
F
A D F
AD
FB
RedActivity(B)
Further refactorings: but …
Elementary reduction operations
Process Visualization Abstracting Process Models: Elementary Operations
Attri
bute
Op.
High-level Operations
Data
Flo
w O
p.
Multi-Aspect Operations
Single-Aspect Operations
Elementary Operations
AGGREGATECF REDUCECF
Aggregate Reduce
ShowMyActivities ...AggrExecutedPart
Control Flow Attributes Application DataProcess
AggrSESEAggrShiftOut
AggrAddBranchRedActivity
AggrComplBranch...
...
...
AggrSESE
AggrAddBranch AggrAddBranch
AggrComplBranches AggrShiftOut
C DBA E
DA
BCEA
B C
ED
r
s
A B
Er
s
r ∨ sCD
A
B
GF
C
EDrs
t
AGF
r ∨ s
t
BCDE
AB
ED
C
AE
CBD
Elementary aggregation operations
C D EBA
A EBCD
AggrSequence
Non-connected activity sets
Process Visualization Abstracting Process Models: Elementary Operations
Attri
bute
Op.
High-level Operations
Data
Flo
w O
p.
Multi-Aspect Operations
Single-Aspect Operations
Elementary Operations
AGGREGATECF REDUCECF
Aggregate Reduce
ShowMyActivities ...AggrExecutedPart
Control Flow Attributes Application DataProcess
AggrSESEAggrShiftOut
AggrAddBranchRedActivity
AggrComplBranch...
...
...
ReductionSESE AggrSESE
BC
C DBA
DA
H: ‹S(A),E(A),S(B),E(B),S(C)›
H’: ‹S(A),E(A),S(BC)›
C DBA
DA
Process Visualization Abstracting Process Models: Elementary Operations
Elementary operations applied at the process instance level
Attri
bute
Op.
High-level Operations
Data
Flo
w O
p.
Multi-Aspect Operations
Single-Aspect Operations
Elementary Operations
AGGREGATECF REDUCECF
Aggregate Reduce
ShowMyActivities ...AggrExecutedPart
Control Flow Attributes Application DataProcess
AggrSESEAggrShiftOut
AggrAddBranchRedActivity
AggrComplBranch...
...
...
Let’s have a closer look at aggregations!
Process Visualization Abstracting Process Models: View Properties
Example: Aggregate activities from set {B,D}
AB
ED
CF
Process Visualization Abstracting Process Models: View Properties
AE
CFBD
AggrShiftOut
AggrAddBranch
How to aggregate these two activities?
Example: aggregate activities from set {B,D}
Alternative 1:
Alternative 2:
► Well-defined properties to characterize the resulting view!
AB
ED
CF
AE
CF
BD
AE
CFBD
AggrShiftOut
AggrAddBranch
Process Visualization Abstracting Process Models: View Properties
B C
D A
E F
• dependency-generating • inconsistent process state
• dependency-erasing • consistent process state
B C
D A
E F
BD C
A E
F
BD
C A
E F
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ü } ü
}
ü
}
}
Process Visualization Abstracting Process Models: View Properties
Properties of view-building operations:
-
AggrAddBranch
AB C
ED
r
s
A B
Er
s
r ∨ sCD
ReductionSESE
C DBA
DA
Process Visualization Abstracting Process Models: View Properties
correct fuzzy
Using views for process execution or process change:
• correct structure and consistent state are crucial
• view interpreted by process engine or change engine
Using views for process visualization:
• imprecision or loss of information is tolerable
• view interpreted by process participants
Process Visualization Abstracting Process Models: View Parameterization
Proviado addresses this issue by enabling parameterizable process views, i.e., the degree of imprecision or tolerable information loss may be flexibly chosen
Reichert, Kolb, Bobrik, & Bauer, 2012
3 strategies for aggregating an activity set (AggregateCF):
AD
IG
FLCB
E
HJ K
AF
IBCDEGH J KL
AF
I
BCDEGH
J KL
AI
FBC
DE
GHJ KL
A BCDEFGHIJKL
AF
I
BCDEGHKL
J
strategy = as-is strategy = expand strategy = subdivide
AD
IG
FLCB
E
HJ K A
D
IG
FLCB
E
HJ K A
D
IG
FLCB
E
HJ K
dependencies = non-erasing
dependencies = non-generating
dependencies = preserving
AggrShiftOut & AggrSESE
AggrAddBranch
AggrAddBranch & AggrSESE
4x AggrSESE
AggrSESE
Process Visualization Abstracting Process Models: View Parameterization
Attri
bute
Op.
High-level Operations
Data
Flo
w O
p.
Multi-Aspect Operations
Single-Aspect Operations
Elementary Operations
AGGREGATECF REDUCECF
Aggregate Reduce
ShowMyActivities ...AggrExecutedPart
Control Flow Attributes Application DataProcess
AggrSESEAggrShiftOut
AggrAddBranchRedActivity
AggrComplBranch...
...
...
TA BCDEFGHIJKLMNOPQRS
AggrSESE({B,C,D,E,F,G,H,I,J,K,L,M,N,O,P,Q,R,S})
B
OMS
LJ
D
N
KA
C
P
F
H
s
t
R
E
Q
G
IT
(Elementary Operation)
2
strategy = expandstates = consistentdependencies = preserving
View Parameterization:
AggrAddBranch ({B,F,G,J,M,N,P,Q,R})
B
OMS
LJ
D
N
KA
C
P
F
H
s
t
R
E
Q
G
IT
O
L
D
KAS
Hst
EI
T
BFGJMNPQR
C(Elementary Operation)
1
strategy = as-isstates = defaultdependencies = default
View Parameterization:
AggrAddBranch({B,J,M,N})AggrSESE({F,G})AggrSESE({P,Q,R})
AggrShiftOut({B,J,M,N})AggrSESE({F,G})AggrSESE({P,Q,R})
B
OMS
LJ
D
N
KA
C
P
F
H
s
t
R
E
Q
G
IT
DH
s
tE
IC
FG
3
strategy = subdividestates = defaultdependencies = default
View Parameterization:
AGGREGATECF({B,F,G,J,M,N,P,Q,R})(Single-Aspect Operation)
B
OMS
LJ
D
N
KA
C
P
F
H
s
t
R
E
Q
G
IT
Base Process Model
Process Visualization Abstracting Process Models: Single-Aspect Operations
Elementary operations for reducing and aggregating data elements: RedData and AggData
Process Visualization Abstracting Process Models: Other Process Aspects
B A
D 1
B A
RedData(D1)
BHF
EC
G
DA I
D1
D3
D2
D5 D6
BHF
EC
G
DA I
D12
D356
D4
D4
AggData({D1,D2}) AggData({D3,D5,D6})
Process Visualization Abstracting Process Models: Other Process Aspects
Basisprozessschema
REDUCEDF({D1,D2,D3,D4}) AGGREGATEDF({D1,D2,D3,D4})
AggData({D1, D2,D3,D4})
RedData({D1})RedData({D2})RedData({D3})RedData({D4})
FD
CA
E
B
D2 D3 D4
D1
FD
CA
E
B
D2 D3 D4
D1
FD
CA
E
B
D2 D3 D4
D1
FD
CA
E
B
FD
CA
E
B
D1234
Core Process Schema
Single-aspect operations for abstracting data flow: REDUCEDF and AGGREGATE DF
D1 D1
ABA
B
D1 D1
ABA
B
D1 D1
ABA
B
A B C
D1 D1
ABC
AdaptDE
AdaptDE
AdaptDE
AdaptDEa)
c)
b)
d)
Process Visualization Abstracting Process Models: Other Process Aspects
Adapting data flow edges in the context of control flow aggregations: AdaptDE
A user-friendly definition of process views requieres high-level view creation operations
Example of a high-level operation: ShowMyActivities – Eliminate all activities the current user is not involved in
Process Visualization Abstracting Process Models: High-level Operations
Attri
bute
Op.
High-level Operations
Data
Flo
w O
p.
Multi-Aspect Operations
Single-Aspect Operations
Elementary Operations
AGGREGATECF REDUCECF
Aggregate Reduce
ShowMyActivities ...AggrExecutedPart
Control Flow Attributes Application DataProcess
AggrSESEAggrShiftOut
AggrAddBranchRedActivity
AggrComplBranch...
...
...
AggrForeignActivities(User = X) 1. Choose high-level view operation and set its parameters
Process Visualization Abstracting Process Models: High-level Operations
Aggregate({B,C,D,G,H,I,J}, Param = {…}) 2. Map high-level operation to multi-aspect operation(s)
AggrShiftOut({B,C,D})
AggrSESE({G,H,I,J})
AdaptDE({D2}) AdaptDE({D3}) AdaptDE({D4})
AggrData({D2,D3}, …)
4. Determine corresponding single-aspect operations and apply them to the original process model; apply refactorings if applicable
B
J
HF
D
I
GA
C
K
E
LX Y
X
Y Y X
Z Z
X
XY Y
D1D2
D4
D3
B
J
HF
D
I
GA
C
K
E
LX Y
X
Y Y X
Z Z
X
XY Y
D1D2
D4
D3
BCDF
AK
E
LX Y
X
X
X
X
D1 D2
D4
GHIJY,Z
D3
BCDF
AK
E
LX Y
X
X
X
X
D1 D23
D4
GHIJY,Z
Example: Actor X: „Aggregate activities I am not involved in“
AGGREGATECF({B,C,D,G,H,I,J}, Param = {strategy = subdivide, …}) AGGREGATEDF({D2,D3})
3. Map multi-aspect operations(s) to single-aspect operations
B
KI
HF
D
J
GA
C
N
E
O P
L MX,Y
X X
Y
W W V
Y X X
V,Y W,V V
X,Y YX
Step 1
Step 2
Step 3
B HGAN
O
MX,Y
X X X X X,YX
Step 4
B HGA N O
MX,Y
XX X X
X,YX
Step 5
REDUCECF(S)Single-aspect Operation:
• Find SESE componentsS1 = {C,D,E}, S2 = {F},S3 = {I,J,K}, S4 = {L},S5 = {P}
RedSESE S1RedSESE S2RedSESE S3RedSESE S4RedSESE S5
Elementary Operations:
Simplification Operations
Initial process schema with activities of user X marked
Reduce(S)Multi-aspect Operation:
• Evaluate pred:
ShowMyActivities(user X)High-level Operation:
• Define predicate pred: Find all activities where actor X is not involved in
S = {C,D,E,F,I,J,K,L,P}
B
KI
HF
D
J
GA
C
N
E
O P
L MX,Y
X X
Y
W W V
Y X X
V,Y W,V V
X,Y YX
B
KI
HF
D
J
GA
C
N
E
O P
L MX,Y
X X
Y
W W V
Y X X
V,Y W,V V
X,Y YX
Process Visualization Abstracting Process Models: High-level Operations
Example: ShowMyActivities High-level Operations in Proviado:
• ShowActivitiesOfUser • AggrExecutedPart • ShowExecutedPath • GroupedAggregation • ViewByRelevance • ViewByPredicate • Subgraph • SubgraphRange • CutProcess • …
adapt display form (diagram, form, table, text, …)
abstracting information (process views)
adapting visual appearance (symbols, colors, …)
Process Visualization Dimensions
Initiation Expertise Evaluation Approval Realization
Initiation Expertise Evaluation Approval Realization
Change Request 000-W213-XQ-2146 Part: Speedometer Change: Improvement of Readability
ü ü } Start: 13.01.2006 End: 15.01.2006
Start: 15.01.2006 End: 23.02.2006
Start: 25.02.2006 End:
Process: CR_V2.1
Instance: 4215
Visu
aliz
atio
n
Process Visualization Visual Appearance of a Process Model: Issues
1. Which visual notation to use? A template mechanism is required that allows for the flexible definition of the
− visual appearance (e.g., geometry) of process objects − placeholders for attributes or (status) symbols
activity
End
}
Start
actor document
filename
Name Headline
Subheading
S start date end date
Initiation Expertise Evaluation Approval Realization Process: CR_V2.1
Instance: 4215
Visu
aliz
atio
n
Process Visualization Visual Appearance of a Process Model: Issues
1. Which visual notation to use? 2. When to use which visualization? Selection of a concrete visualization template may depend on the type of
a process element, attributes, process data, users, etc.
visualization of a process element
element typede
pend
s on
user preferences
status
attribute value
process or application
data
depends on
element = „activity“e.g.
status = „running“
activity.type = „testing“
e.g.
e.g.
Name
AttrValue
Symbol
AttrValueAttrValueAttrValue
state
element = „actor“Mr. Lucas
test goal
TEST
Name Name Name Name Name
Headline Subheading Subheading
S S S start date end date
start date end date
start date end date
start date end date
start date end date
S S
Initiation Expertise Evaluation Approval Realization Process: CR_V2.1
Instance: 4215
Visu
aliz
atio
n
Process Visualization Visual Appearance of a Process Model: Issues
Initiation Expertise Evaluation Approval Realization
Change Request 000-W213-XQ-2146 Part: Speedometer Change: Improvement of Readability
ü ü } Start: 13.01.2006 End: 15.01.2006
Start: 15.01.2006 End: 23.02.2006
Start: 25.02.2006 End:
1. Which visual notation to use? 2. When to use which visualization? 3. Which data? Where to add and how? Abstracting and formatting process data
− Formatting, e.g., date values − Abstracting, e.g. costs: "high " instead of 1.000.000 €
Filling template parameters with concrete process data
Initiation Expertise Evaluation Approval Realization Process: CR_V2.1
Instance: 4215
Visu
aliz
atio
n
Process Visualization Visual Appearance of a Process Model: Issues
Initiation Expertise Evaluation Approval Realization
Change Request 000-W213-XQ-2146 Part: Speedometer Change: Improvement of Readability
ü ü } Start: 13.01.2006 End: 15.01.2006
Start: 15.01.2006 End: 23.02.2006
Start: 25.02.2006 End:
1. Which visual notation to use? 2. When to use which visualization? 3. Which data? Where to add and how? 4. How shall the visualization style look like? Colors, fonts, lines, etc.
process (SVG)
stylesheet(CSS)
stylesheet(CSS)
adaptstyle
A2A1
A3A4 A5
CR-Process
A2A1
A3A4 A5
CR-Process
OEM
Supplier
A2A1
A3A4 A5
CR-Process
Initiation Expertise Evaluation Approval Realization Process: CR_V2.1
Instance: 4215
Visu
aliz
atio
n
Process Visualization Visual Appearance of a Process Model: Issues
How we addressed these issues in the Proviado visualization framework …
Process Visualization Visual Appearance of a Process Model: The Proviado Approach
Visualization Model logical description of all information required for creating a particular
process visualization, e.g., symbols, display form, layouting, …
Process CR1
A1 A2
A3 A4 A5
A1 A2
A3 A4 A5 Visualization
VisModel
VisModel
A1 A2
A3 A4
A5
Process CR1
R
S
T
Process Visualization Visual Appearance of a Process Model: The Proviado Approach
Basic principle: separate process data from its presentation
Visualization template defines 1. symbol to be used 2. data to be displayed 3. application context
Process Visualization Visual Appearance of a Process Model: The Proviado Approach
Examples of visualization templates
Bobrik et al., 2006
Process Visualization Visual Appearance of a Process Model: The Proviado Approach
Schema of a visualization templates
name attrVal
symbol
attrVal attrVal attrVal
state
symbol definition
input parameter
template definition
notation definition notation
template definition
template definition
parameterdefinition parameter parameter
name
describes
template
template
template
name attVal attrVal
describes
describes
...
...
...
describes
describes
<template id="default_act"> <inputs>...</inputs> <graphic> <symbol>...</symbol> <parameter name="Beschreibung" location="g/text[@name=’actname’]" value="act.getName()" /> <parameter name="Status" location="g/g[@name=’status’]"> <choice> <when test="act.getState()=RUNNING"> <use xlink:href="#act_state_RUNNING" /> </when> <when test="act.getState()=COMPLETED">...</when> ... </choice> </parameter> <parameter name=starttime" location="g/text/[@name=’starttime’]“ value="formatDate(act.getStart(), ’dd/mm/yyyy’)"/> ... </graphic> </template>
Name
End Start
JavaScript can be used for calculating parameter values
Parameter locations inside the symbol are specified using XPath
Symbol shapes are defined using SVG
Process Visualization Visual Appearance of a Process Model: The Proviado Approach
Defining a visualization templates for process elements
Process Visualization Visual Appearance of a Process Model: The Proviado Approach
Defining the application context of visualization templates
Visualizing of a a process element
element type
user preferences
status
attribute values
obj . nodetype = "activity "
activity . status = "completed"
activity . type = "testing"
obj . nodetype = "actor" Mr . Lucas
test goal
TEST
Name AttrValue
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Process Visualization Visual Appearance of a Process Model: The Proviado Approach
Defining the application context of visualization templates
Process Visualization Visual Appearance of a Process Model: The Proviado Approach
Process
Name AttrValue
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start : 01 . 08 . 2007 end : 05 . 08 . 2007 cost : 2500
start : 07 . 08 . 2007 end : 14 . 08 . 2007 cost : 4100
name : PartID value : XX 35 K 4 D 1
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references
references
Creating a process visualization
Process Visualization Visual Appearance of a Process Model: The Proviado Approach
Example
Personalized Visualization
Process Visualization Combining the Dimensions
adapt display form (diagram, form, table, text, …)
abstracting information (process views)
adapting visual appearance (symbols, colors, …)
Process Visualization Dimensions
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Process Visualization Display Form of a Process Model
CR-request
write CR-request
check CR-request
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Prozess: Genehmigung ÄnderungAntrag B25KS vom 31.9.2005 Status 11.12.2005
09.11.2005 15.11.2005
24.11.2005 30.11.2005
08.12.2005
Prüferg.: OKGenehmigung Änderung
ID Aktivität Anfang Abschluss DauerQ4
1 üAbt. XY-A7t09.11.200501.11.2005AAA
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Bearbeiterheute
Antrag B25KS vom 31.9.2005
Status 11.12.2005
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01.02. heute 01.03. 01.04. 01.05. 01.06.
recent Change Requests 18.04.2006
Goal: Experiment with other ways of displaying processes
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a) Form-based View b) Tree-based View c) EPC-based View
Process Visualization Display Form of a Process Model
Some concrete work we did in the proView project
Visualisierungskomponente
modify CR
initiate CR request expertise
generate expertise
generate expertise
generate expertise
generate expertise
request evaluation
provide evaluation
provide evaluation
provide evaluation
request comments
provide comments
provide comments
provide comments
provide comments
approve CR instruct realisation conclude CR
approve CR instruct realisation conclude CRblack box
(legacy application)
manual(remodelling)
direct import
modify CR
initiate CR request expertise
generate expertise
generate expertise
generate expertise
generate expertise log-data
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Prozess: Genehmigung ÄnderungAntrag B25KS vom 31.9.2005 Status 11.12.2005
09.11.2005 15.11.2005
24.11.2005 30.11.2005
08.12.2005
Prüferg.: OK
Genehmigung Änderung
ID Aktivität Anfang Abschluss DauerQ4
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Bearbeiterheute
Antrag B25KS vom 31.9.2005
Status 11.12.2005
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Process Visualization Summary: What we achieved in Proviado?
Updatable Process Model Abstractions
Focus of this presentation has been on the personalized visualization of large process models
Another fundamental issue: How to enable domain experts to change large process models!
Proviado proVie
Basic Idea: Using process views not
only for visualization purpose, but also as interface for changing the underlying core process model (CPM)
Updates of a process view then have to be correctly propagated to its CPM as well as all other views on this CPM
Necessitates a formal foundation
proView CPM
View 1' View 2 View n...
CPM‘
View 1' View 2 View n...
UpdateCPM(op1)
op1
a)
CPM‘
View 1' View 2' View n‘
op1'‘ op1'‘‘
...
b)
c)
Updatable Process Model Abstractions
Kolb, Kammerer & Reichert, 2012
Ambiguities when propagating view changes to the CPM
Updatable Process Model Abstractions
proView
C D E B A
AggrSESE(V1,{D,E}) RedActivity(V1,B)
C DE A
Core Process Model CPM
Process View V1 on CPM
Updatable Process Model Abstractions
proView
Updating a CPM and related views after a view update!
Agenda
Challenges & Basic Notions
Part I: Large Process Models
Part II: Large Process Model Collections
Part III: Large Process Structures
References
Business Process Repositories Basic Challenge: Dealing with Large Model Collections
Business Process Repositories
Standard repository features
– Check-in / check- out, access control, simple search queries
Advanced repository features – Extract, transform and compose process information – Filtering (i.e., clone, detection, similarity search,
querying) – Managing process variants – Merging – Navigating in repositories – … (La Rosa et al. 2011)
modify CR
initiate CRrequest
expertisegenerate expertise
generate expertise
generate expertise
generate expertise
request evaluation
provide evaluation
provide evaluation
provide evaluation
request comments
provide comments
provide comments
provide comments
provide comments
approve CR
instruct realisation
conclude CR
change needed
initiate CR
XOR
CR initiated
modify CR
CR modified
request expertise
expertise requested
V
generate expertise
generate expertise
generate expertise
V temp. exp. gen.
generate expertise
expertise generated
XOR
Prozessmodell-transformation
Prozessmodell-integration
approve CR
instruct realisation
conclude CR
request evaluation
provide evaluation
provide evaluation
provide evaluation
request comments
provide comments
provide comments
provide comments
provide comments
modify CR
initiate CRrequest
expertisegenerate expertise
generate expertise
generate expertise
generate expertise
Instanzdatenintegration
System A System B System C
1.
3.2.
Business Process Repositories: Extract, Transform, and Compose Process Fragments
(Bobrik 2008)
Process fragment composition
Process data transformation
Instance data correlation & integration
System A
AB
CD E
AC
BED
Einheitliches Prozessmodell für die Visualisierung
mapping
SO
R
P
Q
remodel
System D
black box
FH
GMI N
extract
load
logs
System B
FG
HI
System C
L M N
mining
L
transform
Business Process Repositories: Extract, Transform, and Compose Process Fragments
Business Process Repositories Filtering
Filtering
– Clone detection • finding exact matches
– Similarity search
• finding close matches
– Querying • looking for patterns
Business Process Repositories Filtering: Similarity Search
Searching for similar process models / process fragments – Given a query graph, find all process models in the
process model collection that are similar
(Dijkman et al. 2011)
When are two process models similar?
When are two process models similar? Similarity measure defines when two process models
are similar – Value between 0 and 1 – 0 indicates no similarity and 1 indicates identical
elements
(Dijkman et al. 2011)
Business Process Repositories Filtering: Similarity Search
When are two process models similar?
Label matching similarity – Similarity based on the labels of business process
model elements Structural similarity
– Measures similarity based on the labels of a business process model element, as well as the relations between these elements
Behavior similarity – Measure similarity based on the intended behavior of
process models
(Dijkman et al. 2011)
Business Process Repositories Filtering: Similarity Search
Querying a process model for patterns – Given a query graph, find all matching sub-graphs in
the process model collection
– Example of such a query language • BPMN-Q (Awad 2007): Queries expressed in BPMN;
usage of wildcard nodes and arcs possible
– Efficient querying of process fragments • Index for efficient querying (Yan, Dijkman, and Grefen
2012)
Business Process Repositories Filtering: Querying Process Models
Looking for patterns in a process model – What happens between A and E?
(Awad 2007, Awad et al. 2008)
Business Process Repositories Filtering: Querying Process Models
Looking for patterns in a process model – What happens from the start until B is reached?
(Awad 2007, Awad et al. 2008)
Business Process Repositories Filtering: Querying Process Models
Agenda
Challenges & Basic Notions
Part I: Large Process Models
Part II: Large Process Model Collections
Part III: Large Process Structures
References
Variability Sources of Variations
Cultural differences Types of customers
Country-specific regulations Types of goods
Religious
Christianity
Judaism
Hinduism Inferior
Nor
mal
Luxury Durable Services Delicate
Drugs administration M
oney
tran
sfer
Professional qualification Food packaging
Handicapped
Kid
VIP Loyal customer
Impu
lsiv
e cu
stom
ers
Language
Use of the language
tabo
o
aesthetics na
tiona
lity
race
Buying and Selling
rent
ing
Intellectual property protection
gender
hist
ory
location
Qua
lity
cont
rol
New customer
Impe
risha
ble
Industrial Example Flight Check-in
Generic process:
Variations due to: – Airline policies (e.g., check-in opening time) – Type of passenger (e.g., adult, child, handicapped) – Type of ticket (e.g., economy, business) – Type of carried items (e.g., pet) – etc.
Identify passenger Assign seat
Print boarding
card
Boarding card
Drop off luggage
» Hundreds of variants
Industrial Example Flight Check-in
Variant 1: – Online check-in – Adult flying with a business class ticket – International flight from EU to USA
Identify passenger Assign seat
Print boarding
card
Electronic Boarding card
Drop off luggage
Fill in ESTA form
23 hours before
departure Web
sys
tem
v
Cou
nter
des
k
v
Industrial Example Flight Check-in
Variant 2: – Counter desk check-in – Unaccompanied Minor (UM)
Identify passenger Assign seat
Print boarding
card
Boarding card
Drop off luggage
3 hours before
departure
Cou
nter
des
k
v
Assign UM seat
Localize staff to accompany
passenger Fill in UM
form
+ +
Industrial Example Flight Check-in
Variant 3: – Online check-in – Adult carrying overweight
Identify passenger
Assign seat
Print boarding
card
Boarding card
Drop off luggage
23 hours before
departure Web
sys
tem
v
Pay extra fee v
Cou
nter
des
k
Business Process Variability
How are Business Processes which are subject to
variability characterized?
Representing Variability Concepts
Variable parts – Parts being subject to variation (commonly known as
variation point)
Identify passenger Assign seat
Print boarding
card
Boarding card
Drop off luggage
Different timer start events
Different seat assignment according to the passenger
needs
Different types of boarding card (paper, sms)
Representing Variability Concepts
Alternatives that exist for each variable parts – Alternatives that fit in each variable part – Relationship constraints between such alternatives
Identify passenger
Fill in ESTA form
23 hours before
departure
3 hours before
departure
Fill in UM form
Fill in pet form
... Assign seat
Assign UM seat
Assign seat (pet company)
Assign seat (wheelchair)
Different timer start events Different seat assignment according to the passenger
needs
Representing Variability Concepts
Application context for each alternative – Conditions that make these variables being applied – Usually represented by a set of variables
Identify passenger
Fill in ESTA form
23 hours before
departure
3 hours before
departure
Fill in UM form
Fill in pet form
... Assign seat
Assign UM seat
Assign seat (pet company)
Assign seat (wheelchair)
Check-in type? • on-line • counter desk
Passenger needs? • No needs • Unaccompanied minor • Carrying a pet • wheelchair
Process Perspectives
Where can we find variability in a BP? – Behavioural – Functional – Informational – Organizational – Temporal – Operational
Process Perspectives
Behavioural It captures the dynamic behavior of a BP model and corresponds to the control flow between the activities. A control flow schema includes information about the order of the activities or the constraints for their execution.
Identify passenger
Fill in ESTA form
23 hours before
departure
3 hours before
departure
Fill in UM form
Fill in pet form
... Assign seat
Assign UM seat
Assign seat (pet company)
Assign seat (wheelchair)
Process Perspectives
Functional It specifies the decomposition of BPs, i.e., it represents the activities to be performed. While an atomic activity is associated with a single action, a complex activity refers to a subprocess or, more precisely, a sub-process model.
Identify passenger
Fill in ESTA form
23 hours before
departure
3 hours before
departure
Fill in UM form
Fill in pet form
... Assign seat
Assign UM seat
Assign seat (pet company)
Assign seat (wheelchair)
Identify passenger
Fill in ESTA form
Fill in UM form
Fill in pet form
Assign seat
Assign UM seat
Assign seat (pet company)
Assign seat (wheelchair)
Process Perspectives
Informational
Identify passenger Assign seat
Print boarding
card
Printed Boarding card
Drop off luggage
It concerns data and data flow, i.e., it represents the informational entities (e.g., data, artifacts, products, and objects) consumed or produced during the execution of BP activities.
Mobile Boarding card
Process Perspectives
Organizational It deals with the assignment of resources to the activities of a BP model, i.e., it represents the actors, roles (i.e., humans or systems), within an organization being in charge of executing certain BP activities.
Identify passenger Assign seat
Print boarding
card
Electronic Boarding card
Drop off luggage
Fill in ESTA form
23 hours before
departure Web
sys
tem
v
Cou
nter
des
k
v
Process Perspectives
Temporal
It deals with time issues and temporal constraints, i.e., it represents the occurrence of events during the course of a process, which affects the scheduling of activities from this process.
Identify passenger Assign seat
Print boarding
card
Electronic Boarding card
Drop off luggage
Fill in ESTA form
23 hours before
departure Web
sys
tem
v
Cou
nter
des
k
v
Process Perspectives
Operational
It refers to the implementation of process activities, i.e., the application services to be executed when an atomic activity is performed.
Identify passenger Assign seat
Print boarding
card
Electronic Boarding card
Drop off luggage
Fill in ESTA form
23 hours before
departure Web
sys
tem
v
Cou
nter
des
k
v
Self-service machine
Counter desk
Online
Limitations of Common BPMLs
Are common BPML constructs sufficient to
properly represent variability in BPs?
Limitations of Common BPMLs
Could we use...
– Conditional branching, – Separate process models, or – Sub-processes
… for such purpose?
Limitations of Common BPMLs
Could we use...
– Conditional branching, – Separate process models, or – Sub-processes
… for such purpose?
Limitations of Common BPMLs Conditional Branching
BPMLs could be used to represent process variant alternatives
Identify passenger
Fill in ESTA form
23 hours before
departure
3 hours before
departure
Fill in UM form
Fill in pet form
... Assign seat
Assign UM seat
Assign seat (pet company)
Assign seat (wheelchair)
Limitations of Common BPMLs Conditional Branching
(+) Allows visualizing all alternatives in one shoot
Alternatives
Alternatives Alternatives
Identify passenger
Fill in ESTA form
23 hours before
departure
3 hours before
departure
Fill in UM form
Fill in pet form
... Assign seat
Assign UM seat
Assign seat (pet company)
Assign seat (wheelchair)
Limitations of Common BPMLs Conditional Branching
(-) Hinders identifying existing variants
Identify passenger
Fill in ESTA form
23 hours before
departure
3 hours before
departure
Fill in UM form
Fill in pet form
... Assign seat
Assign UM seat
Assign seat (pet company)
Assign seat (wheelchair)
Limitations of Common BPMLs Conditional Branching
(-) Hinders differentiating between domain dependent and domain independent conditional branching Domain
dependent
Domain independent
... ...
Mobile phone
Pay-pal
Bank transfer
Credit card
...
+
+
+
+
Fill in UM form
Fill in pet form
Assign seat
Assign UM seat
Assign seat (pet company)
Assign seat (wheelchair)
Limitations of Common BPMLs
Could we use...
– Conditional branching, – Separate process models, or – Sub-processes
… for such purpose?
Cou
nter
des
k
v
Limitations of Common BPMLs Separate process models
(+) Each process variant in a separate model
Identify passenger Assign seat
Print boarding
card
Electronic Boarding card
Drop off luggage
Fill in ESTA form
23 hours before
departure Web
sys
tem
v
Variant 1:
Limitations of Common BPMLs Separate process models
(+) Each process variant in a separate model
Identify passenger
Assign UM seat
Print boarding
card
Boarding card
Drop off luggage
3 hours before
departure Cou
nter
des
k
v Localize staff to accompany
passenger Fill in UM form
+ +
Variant 2:
Limitations of Common BPMLs Separate process models
(-) Common fragments have to be replicated
Cou
nter
de
sk
v
Identify passenger Assign seat
Print boarding
card
Electronic Boarding card
Drop off luggage
Fill in ESTA form
23 hours before
departure Web
sys
tem
v
Variant 1:
Identify passenger
Assign UM seat
Print boarding
card
Boarding card
Drop off luggage
3 hours before
departure
Cou
nter
des
k
Localize staff to accompany
passenger Fill in UM form
+ + Variant 2:
Limitations of Common BPMLs Separate process models
(-) Changes need to be replicated in all variants
Cou
nter
de
sk
v
Identify passenger Assign seat
Print boarding
card
Electronic Boarding card
Drop off luggage
Fill in ESTA form
23 hours before
departure Web
sys
tem
v
Variant 1:
Identify passenger
Assign UM seat
Print boarding
card
Boarding card
Drop off luggage
3 hours before
departure
Cou
nter
des
k
Localize staff to accompany
passenger Fill in UM form
+ + Variant 2:
Sign airline form
Sign airline form
Limitations of Common BPMLs
Could we use...
– Conditional branching, – Separate process models, or – Sub-processes
… for such purpose?
Limitations of Common BPMLs Sub-processes
(+) Promotes the reuse of common fragments (+) Allows reducing the size of the model
Cou
nter
de
sk
v
Start check-in Assign seat
Print boarding
card
Electronic Boarding card
Drop off luggage
Fill in ESTA form
23 hours before
departure Web
sys
tem
v
Variant 1:
+
Identify passenger
Sign airline form
Limitations of Common BPMLs Sub-processes
(-) Variability related issues cannot be explicitly represented
Cou
nter
de
sk
v
Start check-in Assign seat
Print boarding
card
Electronic Boarding card
Drop off luggage
Fill in ESTA form
23 hours before
departure Web
sys
tem
v
Variant 1:
+
Identify passenger
Sign airline form
Limitations of Common BPMLs
Even though these techniques are supported by commercial BPM tools, they do not enable
transparent and explicit management of process variants
Variability in other Domains
Is there something out in other domains that
can be used?
Variability in the SPL domain
Software Product Line (SPL) Engineering – Put emphasis on Reusability and Flexibility by
• Consolidating and capitalizing on commonality through the product line
• Focusing on product variations – Objectives:
• Create a collection of similar software systems from a shared set of software assets using a common means of production
Language requirements
Variation point Alternative process element Alternative process element context Alternative process element relationship Variation point resolution time
Language requirements
Variation point
Precise position within a configurable process where different choices are possible depending on the current context or situation.
Variation point
Variation point Variation point
Identify passenger
Fill in ESTA form
23 hours before
departure
3 hours before
departure
Fill in UM form
Fill in pet form
... Assign seat
Assign UM seat
Assign seat (pet company)
Assign seat (wheelchair)
Language requirements
Alternative process element
Particular option that may be instantiated at a specific variation point and may refer to any modelling element such as activities and their control flow, resources, data, events, or operations.
Identify passenger
Fill in ESTA form
23 hours before
departure
3 hours before
departure
Fill in UM form
Fill in pet form
... Assign seat
Assign UM seat
Assign seat (pet company)
Assign seat (wheelchair)
Language requirements
Alternative process element context
Subset of process variables whose values make a particular alternative process element to become instantiated for a variation point.
Context variable
NO
UM
PET
WHEEL
Identify passenger
Fill in ESTA form
23 hours before
departure
3 hours before
departure
Fill in UM form
Fill in pet form
... Assign seat
Assign UM seat
Assign seat (pet company)
Assign seat (wheelchair)
Special needs?
Language requirements
Alternative process element relationship
Constraint of use between two or more alternative process elements. These constraints are defined based on semantic relationships to ensure the proper use of the involved alternative process elements within a specific context.
Identify passenger
Assign UM seat
Print boarding
card
Boarding card
Drop off luggage
3 hours before
departure Cou
nter
des
k
v Localize staff to accompany
passenger Fill in UM form
+ +
Inclusive
Language requirements
Variation point resolution time
This requirement should allow modellers to distinguish between variation points whose resolution depends on the initial context (configuration time) or on the current context of a process instance (enactment time).
Identify passenger
Fill in ESTA form
23 hours before
departure
3 hours before
departure
Fill in UM form
Fill in pet form
... Assign seat
Assign UM seat
Assign seat (pet company)
Assign seat (wheelchair)
Enactment time Configuration
time
Representing BP Variability
Two main approaches: – Behavioural-based approaches – Structural-based approaches
Two main approaches: – Behavioural-based approaches – Structural-based approaches
Representing BP Variability
Representing BP Variability Behavioural-based approaches
Behavioural-based approaches – Single modelling artefact (Configurable process model) – Process variant derivation by removing parts from the
configurable process model • Techniques for variant derivation:
– Configurable nodes and configuration requirements and guidelines
– Hiding and blocking
– Proposals found in BPM literature • C-EPC/C-iEPC (Rosemann et al. 2007/La Rosa et al. 2008) • C-YAWL (Gottschalk et al. 2008)
Representing BP Variability Behavioural-based approaches
Configuring configurable process elements
Con
figur
atio
n of
Var
iant
s Pr
oces
s- M
odel
ing
Context
Configurable process model
A
B C
D
C D
E D F
G
H
I
J
K …
Process family
A G
H
I
J
K …
A B C G
H
I
J
K …
A D G
H
I
J
K …
Representing BP Variability Behavioural-based approaches
C-iEPC – Configurable nodes
• Connectors – Restrict their behaviour or SEQ
• Functions – Configured as ON, OFF, or OPT
• Objects – 2 Dim: Optionality and specialization
• Roles – 2 Dim: Optionality and specialization
– Configuration... • Requirements
– State hard configuration constraints
• Guidelines – State soft configuration constraints
Representing BP Variability Behavioural-based approaches
C-iEPC – Configurable nodes
• Connectors – Restrict their behaviour or SEQ
• Functions – Configured as ON, OFF, or OPT
• Objects – 2 Dim: Optionality and specialization
• Roles – 2 Dim: Optionality and specialization
– Configuration... • Requirements
– State hard configuration constraints
• Guidelines – State soft configuration constraints
Representing BP Variability Behavioural-based approaches
C-iEPC
– Configurable nodes
• Connectors – Restrict their behaviour or SEQ
• Functions – Configured as ON, OFF, or OPT
• Objects – 2 Dim: Optionality and specialization
• Roles – 2 Dim: Optionality and specialization
– Configuration... • Requirements
– State hard configuration constraints
• Guidelines – State soft configuration constraints
Representing BP Variability Behavioural-based approaches
C-iEPC – Configurable nodes
• Connectors – Restrict their behaviour or SEQ
• Functions – Configured as ON, OFF, or OPT
• Objects – 2 Dim: Optionality and specialization
• Roles – 2 Dim: Optionality and specialization
– Configuration... • Requirements
– State hard configuration constraints
• Guidelines – State soft configuration constraints
Representing BP Variability Behavioural-based approaches
C-iEPC – Configurable nodes
• Connectors – Restrict their behaviour or SEQ
• Functions – Configured as ON, OFF, or OPT
• Objects – 2 Dim: Optionality and specialization
• Roles – 2 Dim: Optionality and specialization
– Configuration... • Requirements
– State hard configuration constraints
• Guidelines – State soft configuration constraints
Representing BP Variability Behavioural-based approaches
C-iEPC – Configurable nodes
• Connectors – Restrict their behaviour or SEQ
• Functions – Configured as ON, OFF, or OPT
• Objects – 2 Dim: Optionality and specialization
• Roles – 2 Dim: Optionality and specialization
– Configuration... • Requirements
– State hard configuration constraints
• Guidelines – State soft configuration constraints
Understandability Task Process Variant Extraction
C-iEPC – Let’s derive the variant where:
• Unaccompanied Minor (UM) • Check-in luggage • No luggage overweight
Understandability Task Process Variant Extraction
C-iEPC
• Connectors
• XORc2 = SEQ1b
Understandability Task Process Variant Extraction
C-iEPC
• Connectors
• XORc2 = SEQ1b • XORc6 = SEQ2b
Understandability Task Process Variant Extraction
C-iEPC
• Connectors
• XORc2 = SEQ1b • XORc6 = SEQ2b
• Functions • Fill in ESTA form = OFF
Understandability Task Process Variant Extraction
C-iEPC
• Connectors
• XORc2 = SEQ1b • XORc6 = SEQ2b • XORc9 = OR
• Functions • Fill in ESTA form = OFF
Understandability Task Process Variant Extraction
C-iEPC
• Connectors
• XORc2 = SEQ1b • XORc6 = SEQ2b • XORc9 = OR
• Functions • Fill in ESTA form = OFF • Localize staff = ON
Understandability Task Process Variant Extraction
C-iEPC
• Connectors
• XORc2 = SEQ1b • XORc6 = SEQ2b • XORc9 = OR
• Functions • Fill in ESTA form = OFF • Localize staff = ON • Drop off lugg. = ON
Understandability Task Process Variant Extraction
C-iEPC
• Connectors
• XORc2 = SEQ1b • XORc6 = SEQ2b • XORc9 = OR • XORc12 = OR
• Functions • Fill in ESTA form = OFF • Localize staff = ON • Drop off lugg. = ON
Understandability Task Process Variant Extraction
C-iEPC
• Connectors
• XORc2 = SEQ1b • XORc6 = SEQ2b • XORc9 = OR • XORc12 = OR
• Functions • Fill in ESTA form = OFF • Localize staff = ON • Drop off lugg. = ON • Pay extra fee = OFF
Understandability Task Process Variant Extraction
C-iEPC • Roles
• c1 = Economy class counter • c4 = Economy class counter • c5 = Economy class counter • c7 = Economy class counter • c10 = Economy class counter • c11 = Economy class counter
• Objects • C8 = Paper boarding card
Understandability Task Process Variant Extraction
C-iEPC
Mental process followed in C-EPC:
1. Inspect all configurable nodes 2. Evaluate the associated requirements 3. Configure configurable nodes accordingly
Process Variant Extraction Task Cognitive discussion
C-iEPC – Cognitive discussion
• 3 basic operations: – Locating elements
» Easy to perform thanks to their visual differences – Evaluating Boolean expressions
» Can be pretty challenging depending on the complexity of the expression
» Some evaluations depend on previous decisions – Adapting the model accordingly
» Elements have to be mentally removed
⇒Complexity depends on how many requirements have to be analyzed
Two main approaches: – Behavioural-based approaches – Structural-based approaches
Representing BP Variability
Representing BP Variability Structural-based approaches
Structural-based approaches – Several modelling artefacts
• Base model • Change operations
– Process variant derivation through the application of change operation to the base model
– Proposals found in BPM literature • Provop (Hallerbach et al. 2010)
• Rule representation and processing (Kumar and Wen 2012)
Con
figur
atio
n of
Var
iant
s Process family
A G
H
I
J
K …
A B C G
H
I
J
K …
A D G
H
I
J
K …
Representing BP Variability Structural-based approaches
Provop
Choosing and applying options
Proc
ess-
Mod
elin
g
Context
Options
... Delete
Option n
Modify ... Insert
Option 1
... Move
Base model A D G I K …
Provop – Base model
• Policies: Standard process Most frequently used process Minimal average distance Superset of all process variants Intersection of all process variants
Representing BP Variability Structural-based approaches
Adjustment Points
Variant: Passenger with no special needs, dropping off luggage, carrying luggage excess
Provop – Change Options
• Allow deriving new variants • Are applied to the base model
Representing BP Variability Structural-based approaches
Provop – Options Constraints
• Relationships : Implication, Exclusion, Order, etc.
Representing BP Variability Structural-based approaches
Provop – Context Model
Representing BP Variability Structural-based approaches
Understandability Task Process Variant Extraction
Provop – Let’s derive the variant where:
• Unaccompanied Minor (UM) • Check-in luggage • No luggage overweight
Understandability Task Process Variant Extraction
Provop 1. Examine all change options and their Boolean
expressions
Variant: Unaccompanied minor, check-in luggage, no luggage overweight
Understandability Task Process Variant Extraction
Provop 2. Select all change options satisfying the given context
Variant: Unaccompanied minor, check-in luggage, no luggage overweight
Understandability Task Process Variant Extraction
Provop 3. Determine whether all options can be applied
according to the constraint model
Variant: Unaccompanied minor, check-in luggage, no luggage overweight
Understandability Task Process Variant Extraction
Provop 4. Locate the variation points where options apply
Variant: Unaccompanied minor, check-in luggage, no luggage overweight
Understandability Task Process Variant Extraction
Provop 4. Locate the variation points where options apply
Variant: Unaccompanied minor, check-in luggage, no luggage overweight
Understandability Task Process Variant Extraction
Provop 4. Locate the variation points where options apply
Variant: Unaccompanied minor, check-in luggage, no luggage overweight
Understandability Task Process Variant Extraction
Provop 4. Mentally integrate change options into the base model
Variant: Unaccompanied minor, check-in luggage, no luggage overweight
Understandability Task Process Variant Extraction
Provop 4. Mentally integrate change options into the base model
Variant: Unaccompanied minor, check-in luggage, no luggage overweight
Understandability Task Process Variant Extraction
Provop 4. Mentally integrate change options into the base model
Variant: Unaccompanied minor, check-in luggage, no luggage overweight
Understandability Task Process Variant Extraction
Provop 4. Mentally integrate change options into the base model
Variant: Unaccompanied minor, check-in luggage, no luggage overweight
Understandability Task Process Variant Extraction
Provop 4. Mentally integrate change options into the base model
Variant: Unaccompanied minor, check-in luggage, no luggage overweight
Understandability Task Process Variant Extraction
Provop 4. Mentally integrate change options into the base model
Variant: Unaccompanied minor, check-in luggage, no luggage overweight
Understandability Task Process Variant Extraction
Provop 4. Mentally integrate change options into the base model
Variant: Unaccompanied minor, check-in luggage, no luggage overweight
Understandability Task Process Variant Extraction
Provop 4. Mentally integrate change options into the base model
Variant: Unaccompanied minor, check-in luggage, no luggage overweight
Understandability Task Process Variant Extraction
Provop 4. Mentally integrate change options into the base model
Variant: Unaccompanied minor, check-in luggage, no luggage overweight
Process Variant Extraction Task Cognitive discussion
Provop
Mental process followed in Provop:
1. Examine all change options and their Boolean expressions 2. Select all change options satisfying the given context 3. Determine whether all options can be applied according to the
constraint model 4. Locate the variation points where options apply 5. Mentally integrate change options into the base model
Process Variant Extraction Task Cognitive discussion
Provop – Cognitive discussion
• Two main operations: – Selecting change options
» Boolean expression need to be evaluated » All are expressed in terms of context variables » Check for conflicts in the constraint model
– Applying change options into the base model » Determine by the change distance between the base
model and the variant to be derived. » The type of operation influences the complexity (delete
vs. insert)
Language Support Comparison Structural vs Behavioural
C-EPC Provop Variation Point + + Alternative process elements F, B, O, I F, B Alternative process element context + + Alternative process element relationships +/- + Variation point resolution time - -
functional (F), behavioral (B), organizational (O), Informational (I) perspectives
Qualitative Comparison
Discussion – Modelling elements
• In C-EPC are mainly deleted • In Provop can be added, deleted, and moved » Deletion presumably involves less cognitive effort
Qualitative Comparison
Discussion – Variability modelling elements
• Single artefact in C-EPC – Configurable process model » Works for small models » Overload for large models
• Separate artefacts in Provop – base model, change options, options constraint, context
model » Abstraction mechanisms favour model understanding
Qualitative Comparison
Discussion – Boolean expressions
• C-EPC: Represented in terms of the model structure – Forces to keep track of previous decisions – Presumably imposing bigger mental effort
• Provop: Represented in terms of context variables – Semantics is explicit in the model » Presumably imposing less mental effort
Business Process Repositories Merging Process Models: Behavioral Approach
La Rosa et al, 2010
Process (Variant) Models
…
(Configurable) Process Model
merge
1. Configurations are very costly
2. Variants are difficult to maintain
Original reference process model S
…customization & adaptation
Process variant S1 Process variant S2 Process variant Sn
mining & learning
Discovered reference process model S’
Control differences Goal: Less configurations!
e.g., discover a new reference process model having lower average weighted distance to the variants than the original reference process model has!
Why?
1. Limit the efforts to update reference model
2. Avoid spagatti-like structure
3. Obtain the flexibility to only perform the important changes
Business Process Repositories Merging Process Models: Structural Approach
Business Process Repositories Merging Process Models: Structural Approach
Li, Reichert, & Wombacher 2012
Applying Heuristics Search to Scenario 2
Variants
d=1
d = 2
d =
3
Original reference
model No search distance
constraint
Force 1:close to variants
Force 2: close to reference
Snc : Search result without
constraint
Original Reference model
Process variants
Intermediate search result
Search steps
Discovered Reference Model
Sc: Search result with constraint
Business Process Repositories Merging Process Models: Structural Approach
A B Z
…
SCkidSB
kidSAkid …
A B C YZ
Best kid when changing A
Best kid when changing Y
Best kid when changing B
Best kid is better than parent
Best kid is NOT better than parent
SZkid SY
kid
Best kid when changing Z
Best kid when changing C
Search tree based on best kids Skidaj
Start
Original reference model S
SsibBest sibling of all best kids
B Terminating condition: No kid is better than its parent
Search result
Applying Heuristics Search to Scenario 2
Business Process Repositories Merging Process Models: Structural Approach
Can we find a model closer to the variants by performing saying only 3 changes of the old reference model?
Average (weighted) distance of S to the variants: 4 high-level changes (NP-hard complexity)
Business Process Repositories Merging Process Models: Structural Approach
Example (1)
Business Process Repositories Merging Process Models: Structural Approach
Example (2)
Business Process Repositories Merging Process Models: Structural Approach
Healthcare Case Study
Business Process Repositories Navigating in Respositories and Large Process Models
Level of granularity
Process World Process Areas Processes Process Step
Business Process Repositories Navigating in Respositories and Large Process Models
Practical demands: Navigate in Large Process Models
Navigation within one single dimension (forward/backward)
Views are predefined
No comprehensive tool support available
comprises a sequence of user interactions allows process participants to navigate from a default
visualization of a large process to more specific ones
Business Process Repositories Navigating in Respositories and Large Process Models
Process Navigation (niPRO)
niPRO - Hipp, Mutschler & Reichert, 2012
Geographic dimension
View dimension
Business Process Repositories Navigating in Respositories and Large Process Models
niPRO Core Navigation Model – Inspired by Google Earth
niPRO - Hipp, Mutschler & Reichert, 2012
Level 1 The Globe Process world
Level 2 Continents Process areas
Level 3 Countries Processes
Level 4 Cities Process steps
Geographic dimension
View dimension
Business Process Repositories Navigating in Respositories and Large Process Models
niPRO Core Navigation Model – Inspired by Google Earth
3-dimensional navigation concept
Business Process Repositories Navigating in Respositories and Large Process Models
niPRO - Hipp, Mutschler & Reichert, 2012
Initial situation • 3-dimensional
navigation space
• Different navigation states (g, s, v)
• State transitions (= user interactions)
119
Business Process Repositories Navigating in Respositories and Large Process Models
120
Some Challenges – How to guide the user through the navigation space? – How to recommend certain paths within the navigation
space (i.e., to reduce number of interactions)? – How to remove specific navigation states being not
reasonable… – How to assist users when the navigation space gets
more complex… A process navigation model is needed
Business Process Repositories Navigating in Respositories and Large Process Models
Typical use case A developer wants to
see which process step has to be done, after he completed the current process step.
Business Process Repositories Navigating in Respositories and Large Process Models
Start: (0,0,0) End: (1,1,0)
Typical use case A developer wants to
see which process step has to be done, after he completed the current process step.
Business Process Repositories Navigating in Respositories and Large Process Models
Agenda
Challenges & Basic Notions
Part I: Large Process Models
Part II: Large Process Model Collections
Part III: Large Process Structures
References
System
Komponente Komponente Komponente
System
Gesamtsystem
Large Process Structures Motivation
Interacting process fragments. The arcs show the interactions that need to take place between fragment instances.
Large Process Structures A Simple Example
Mans et al., 2012
Proclets provide a framework for modeling and executing workflows
A Proclet can be seen as a lightweight workflow process able to interact with other Proclets (potentially at different levels of aggregation).
A Proclet class specifies which tasks need to be executed and in which order, i.e., the Proclet class defines the process followed by individual Proclets. One instance is called a Proclet instance.
Large Process Structures Proclets
Proclet classes for the illustrated scenario Mans et al., 2012
Large Process Structures Proclets
Large Process Structures Proclets
Mans et al., 2012
Product Process Product Process =
Process
Process
Process Process Process
Process
Process
Process
Process Process
Process structure needs to be adapted when product
structure changes!
Large Process Structures Data-driven Process Structures: Motivation
Modeling
Brett-Test Telematik
Brett-Test Komponente Brett-Test
Komponente Brett-Test Komponente
Brett-Test Innenraum
Auswahl Komponenten
Brett-Test Motor
Brett-Test Komponente
Prüfstand Motor E/E-Klausur
Release
Execution
Dynamic Adaptation
Exception Handling
Large Process Structures Data-driven Process Structures: Motivation
Modeling
System
Komponente Komponente Komponente
System
GesamtsystemBrett-Test Telematik
Brett-Test Komponente Brett-Test
Komponente Brett-Test Komponente
Brett-Test Innenraum
Auswahl Komponenten
Brett-Test Motor
Brett-Test Komponente
Prüfstand Motor E/E-Klausur
Release
Corepro: Integrated Support of Data-driven Process Structures
Execution
Dynamic Adaptation
Exception Handlung
Data-driven Process Structure
Large Process Structures Data-driven Process Structures: Motivation
Large Process Structures Data-driven Proess Structures: Motivation
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Tür-SG Beifahrer
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Spezifi-zieren Spezifiziert AngeliefertBestellen
Klima-Steuergerät low
S ESicht-Prüfung
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Spezifi-zieren Spezifiziert AngeliefertBestellenKlima Display
S ESicht-Prüfung
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Spezifi-zieren Spezifiziert AngeliefertBestellen
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S ESicht-Prüfung
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Spezifi-zieren Spezifiziert AngeliefertBestellen
Klima Bedieneinheit 2
S ESicht-Prüfung
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Spezifi-zieren Spezifiziert AngeliefertBestellen
Klima Bedieneinheit 1
S ESicht-Prüfung
[i.O.]
[Nicht i.O.]
Spezifi-zieren Spezifiziert AngeliefertBestellen
Motor-SG Diesel 2
S ESicht-Prüfung
[i.O.]
[Nicht i.O.]
Spezifi-zieren Spezifiziert AngeliefertBestellen
Klima Bedieneinheit 3
S ESicht-Prüfung
[i.O.]
[Nicht i.O.]
Installieren
InstallierenInstallieren
Installieren
InstallierenInstallieren
InstallierenInstallieren
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τ τ
Data-Driven Process Structures: The Corepro Approach
Large Process Structures Corepro
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Data Structure
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Object Life Cycles / Life Cycle Coordination Model
Large Process Structures Corepro
Müller et al. 2007
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Prototyp umgebaut
UmbauMechanik
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AuswahlKomponenten
Konfiguration gebildet
Muster Aufgebautτ Brett-
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KomponenteS EMelden[i.O.]
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Installieren
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BR212, Rel. 02/08
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Telematik High V2.2
Head-Up UnitV3.14
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Telematik High V2.2
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nutztKomp
TV TunerV1.83
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TV Tuner V1.83
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BestätigungMuster
M o d e l l e b e n e
I n s t a n z e b e n e
Release-bildung
Release Gebildet
Prototyp umgebaut
UmbauMechanik
Rück-dokumentationS E
AuswahlKomponenten
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Muster Aufgebautτ Brett-
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Bestellung Komponente angeliefert AbgesichertAbsicherungS EMelden[i.O.]
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TV TunerV1.83
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Prototyp umgebaut
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AuswahlLieferant Ausgewählt Aufgebautτ
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Spezifi-zieren Spezifiziert AngeliefertBestellen
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Spezifi-zieren Spezifiziert AngeliefertBestellenKlima Display
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Spezifi-zieren Spezifiziert AngeliefertBestellen
Klima Bedieneinheit 2
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Spezifi-zieren Spezifiziert AngeliefertBestellen
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Installieren
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τ τ
• Significant reduction of modeling efforts for process engineers
• Formal operational semantics allows for correct executability
• Soundness can be guaranteed on an abstracted level
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BR212, Rel. 02/08
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Telematik High V2.2
Head-Up UnitV3.14
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Telematik High V2.2
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Change Operation (Data Structure) 1) removeRelation(Telematik High
V2.2, TV Tuner V1.83, nutztKomp);
2) removeObject(TV Tuner V1.83);
Change Operation (Process Structure) 1) removeExtTrans(Telematik High V2.2 .
Muster Aufgebaut, Installieren, TV Tuner V1.83 . E);
2) removeOLC(Tuner V1.83);
Data-driven Process Adaptation
Large Process Structures Data-driven Process Structures: Corepro
Müller et al. 2008a
BR212, Rel. 02/08
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Bestellung Komponente angeliefert AbgesichertAbsicherungS EMelden
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[i.O.]
BR212, Rel. 02/08
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Telematik High V2.2
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TV TunerV1.83
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Gesamtsystem
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Komponente
InstallierenhatKomp
TV Tuner V1.83
BestätigungMuster
I n s t a n z e b e n e
Release-bildung
Release gebildet
Prototyp umgebaut
UmbauMechanik
Rück-dokumentationS E
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Konfiguration gebildet
Muster aufgebautτ Brett-
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Bestellung Komponente angeliefert AbgesichertAbsicherungS EMelden
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Bestellung Komponente angeliefert AbgesichertAbsicherungS EMelden
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[i.O.]
YIELD!
YIELD!
YIELD! YIELD!
YIELD!
YIELD!YIELD!
JUMP
RESET RESET
JUMP Step 1
Step 2
Step 3
Forward Recovery
Large Process Structures Data-driven Process Structures: Corepro
Exception Handling
Graphical User Interface of COREPROSim Automatic Creation and Execution of a Process Structure Dynamic Adaptation and Exception Handling Simulating Large Process Structures
NotActivated
Activated
Done
Skipped
Inkonsistenzerkannt
Waiting
Processing
Fired
Disabled
Zustandsmarkierungen Transitionsmarkierungen
Defining the Model Level with Correctness Checks
Large Process Structures Data-driven Process Structures: Corepro Proof-Of-Concept
Müller et al. 2008b
= Objektzustand Interne Transition mit verknüpftem Prozess und Transitionsbedingung= = Endzustand= Startzustand
PD = Product Development, HW = Hardware, SW = Software
Process Description of the ISO Norm Data Model in COREPRO-Sim OLC of Object Type "System" Life Cycle Coordination Model Instance Level: Data Structure and Automatically Created Process Structure
Large Process Structures Corepro: Case Study ISO 26262 -- Road Vehicles, Functional Safety
References
Ahmed Awad: BPMN-Q: A Language to Query Business Processes. EMISA 2007: 115-128.
Ahmed Awad, Gero Decker, Mathias Weske: Efficient Compliance Checking Using BPMN-Q and Temporal Logic. BPM 2008: 326-341.
Bobrik, R.; Reichert, M.; Bauer, T.: Requirements for the Visualization of System-Spanning Business Processes. Proc 16th Int’l Workshop on Database and Expert Systems Applications (DEXA’05), IEEE Computer Society, pp. 948–954 (2005)
Bobrik, R.; Bauer, T.; Reichert, M.: Proviado – Personalized and Configurable Visualizations of Business Processes. Proc 7th Int’l Conf on Electronic Commerce and Web Technologies (EC-Web’06) LNCS 4082, pp. 61–71 (2006)
Bobrik, R.; Reichert, M.; Bauer, Th.: View-based Process Visualization. In: Proc Int‘l Conf on Business Process Management (BPM’07) LNCS 4714, pp. 88–95 (2007)
Remco M. Dijkman, Marlon Dumas, Boudewijn F. van Dongen, Reina Käärik, Jan Mendling: Similarity of business process models: Metrics and evaluation. Inf. Syst. 36(2): 498-516 (2011)
M. Dumas, L. Garcia-Banuelos, M. La Rosa, R. Uba. Fast Detection of Exact Clones in Repositories of Business Process Models. Information Systems (to appear).
Eshuis, R., Grefen, P.: Constructing Customized Process views. Data Knowl Eng, 64, pp. 419-438 (2008)
Christian Gerth, Markus Luckey, Jochen Malte Küster, Gregor Engels: Detection of Semantically Equivalent Fragments for Business Process Model Change Management. IEEE SCC 2010: 57-64
D. Fahland: Number of ways students name an activity in a process model. http://dirksmetric.wordpress.com/2012/08/17/number-of-ways-student-name-an-activity-in-a-process-model/, [accessed on 2012/08/12]
Figl, K., Laue, R.: Cognitive Complexity in Business Process Modeling. In Proc. CAiSE'11, 452-466.
Gottschalk, F., van der Aalst, W.M.P., Jansen-Vullers, M.H., La Rosa, M.: Configurable Workflow Models. International Journal of Cooperative Information Systems 17(2): 177-221 (2008).
Hallerbach, A., Bauer, T., Reichert, M.: Capturing variability in business process models: the Provop approach, J. Soft. Maintenance. 22(6-7): 519-546 (2010)
Hipp, Markus and Mutschler, Bela and Reichert, Manfred (2012) Navigating in Complex Business Processes. In: Proc. 23rd Int'l Conf on Database and Expert Systems Applications (DEXA'12), Part II, Vienna, Austria, September 3-6, 2012, LNCS 7447, Springer, pp. 466-480.
Kolb, J.; Kammerer, K.; Reichert, M. : Updatable Process Views for User-centered Adaption of Large Process Models. Proc 10th Int'l Conf on Service Oriented Computing (ICSOC'12), (2012)
Kumar, A., Wen, Y.: Design and management of flexible process variants using templates and rules. International Journal Computers in Industry 63(2), pp. 112-130 (2012).
La Rosa, M., Dumas, M., ter Hofstede, A.H.M. , Mendling, J., Gottschalk, F.: Beyond Control-Flow: Extending Business Process Configuration to Roles and Objects. In Proc. ER’08, 199-215.
La Rosa, M., Dumas, M., Uba, R., Dijkman, R.M.: Merging business process models. In: OTM Confs (1), LNCS, vol. 6426, pp. 96–113. Springer (2010)
Marcello La Rosa, Hajo A. Reijers, Wil M. P. van der Aalst, Remco M. Dijkman, Jan Mendling, Marlon Dumas, Luciano García-Bañuelos: APROMORE: An advanced process model repository. Expert Syst. Appl. 38(6): 7029-7040 (2011) Larkin, J.H., Simon, H.A.: Why a Diagram is (Sometimes) Worth Ten Thousand Words. Cognitive Science 11 (1987) 65-100 Henrik Leopold, Jan Mendling, Hajo A. Reijers: On the Automatic Labeling of Process Models. CAiSE 2011: 512-520
Henrik Leopold, Sergey Smirnov, Jan Mendling: Recognising Activity Labeling Styles in Business Process Models. Enterprise Modelling and Information Systems Architectures 6(1): 16-29 (2011)
Henrik Leopold, Sergey Smirnov, Jan Mendling: On the refactoring of activity labels in business process models. Inf. Syst. 37(5): 443-459 (2012)
Müller, D.; Reichert, M.; Herbst, J.: Data-driven Modeling and Coordination of Large Process Structures. In: 15th Int'l Conf. on Cooperative Information Systems (CoopIS'07), Vilamoura, Portugal, LNCS 4803, Springer, pp. 131-149 (2007).
Müller, D.; Reichert, M.; Herbst, J.: A New Paradigm for the Enactment and Dynamic Adaptation of Data-driven Process Structures. In: 20th Int'l Conf. on Advanced Information Systems Engineering (CAiSE'08), Montpellier, France, LNCS 5074, Springer, pp. 48-63 (2008a)
Müller, D.; Reichert, M.; Herbst, J.; Köntges, D.; Neubert, A.: COREPRO-Sim: A Tool for Modeling, Simulating and Adapting Data-driven Process Structures. In: 6th Int'l Conf. on Business Process Management (BPM'08 Demonstrations), Milan, Italy, LNCS 5240, Springer, pp. 394-397 (2008b)
Li, C., Reichert, M., Wombacher, A. (2011) Mining Business Process Variants: Challenges, Scenarios, Algorithms. Data & Knowledge Engineering, Vol. 70, No. 5, pp. 409-434.
T. Malone, K. Crowston, G. Herman, Organizing business knowledge: the MIT process handbook, MIT Press, 2003.
Mans, R.; van der Aalst, W.; Russel, N.; Bakker, P.; Moleman, A.: Lightweight Interacting Patient Treatment Processes. International Journal of Knowledge-Based Organizations (to appear in 2012)
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