Cédric Favre Barbara Jobstmann Niels Lohmann Dirk Fahland
Jana Koehler Karsten Wolf
Hagen Völzer
IBM Research Zürich EPF Lausanne Universität Rostock Humboldt-Universität
zu Berlin

Find errors as early as possible
Analysis on Demand?
business process
model
simulation 

X code generation  .bpel 
business process workflow engine 
modeler
error in process model  unreliable simulation results
 erroneous translation
 erroneous execution
find errors as early as possible
find control-flow errors: check soundness
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Finding errors in practice
Analysis on Demand?
 an example from practice, not well-structured
 
sound?
need: automated analysis
?
how often on every save, load, export, on demand
h ow fast? press a button … < 500 ms
Which techniques allow analysis on demand? 3

Outline
Analysis on Demand?
 Soundness and how difficult is it?
 Techniques for efficient analysis
 Experimental results
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Error (1): Lack of Synchronization
sound = no deadlock + no lack of synchronization
Analysis on Demand?
P1 : B
Lack of Synchronization:
A X D two tokens on one edge
C
State Space of P1:
D
C
B
A C D D
C B B
D
Naïve analysis: build state space and find error state
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Error (2): Deadlock
sound = no deadlock + no lack of synchronization
Analysis on Demand?
P2 : B
Deadlock:
A X D token cannot proceed
C
State Space of P2:
B
A
C
Naïve analysis: build state space and find error state
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How difficult is soundness analysis?
Analysis on Demand?
 a sample of 735 industrial business processes
 all expressed with:
A B X (“free choice” constructs)
 analysis by naïve state space exploration:
 intractable for 4 processes only
 problem: state space explosion
 n parallel activities  2n states
 found 4 sound processes with >> 1,000,000 states
 naïve analysis is incomplete in practice
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Outline
Analysis on Demand?
 Soundness and how difficult is it?
 Techniques for efficient analysis
 Experimental results
8

Partial order reduction
Analysis on Demand?
 naïve analysis:
 build each state: check if deadlock
 partial order reduction
 build only one path from entry to exit
 no deadlock on path  no deadlock in the rest
 yields exponential reduction
 works also for lack of synchronization
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Refined Process Structure Tree (RPST)
 decompose process into fragments (single entry and single exit)
Analysis on Demand?
P A
A1 A2
P par
B B1 A seq B split/join
X
B2 A1 A2 B1 B2
 analyze each fragment
A: B1
A1 A2 B:
B2
 error in a fragment ↔ process unsound
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Avoid state space exploration
A
Analysis on Demand?
 heuristics on fragments, e.g. A1 A2
 A: only sequence  sound
 B: one XOR-split, n0 XOR-join B B1
 unsound X
B2
 structural reduction:
A1 A2
 rules for reducing process model
 reduction to single node  sound
A12
 infer behavior from model structure
 e.g. S-coverability (in Woflan) = partial check for unsoundness
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Outline
Analysis on Demand?
 Soundness and how difficult is it?
 Techniques for efficient Analysis
 Experimental results
12

Experiment
Analysis on Demand?
 a sample of 735 industrial business processes
 size of processes:
 nodes: max. 118
 parallel branches: max. 66
 state space: max. >> 1,000,000
 experiment: 3 tools (different techniques)
 complete analysis on all processes
 # sound: 374 (50%)
 max. analysis time: 91 ms, avg. 10 ms
 analysis on demand
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Detailed results
sound
Analysis on Demand?
Petri LoLA: model checker +
net partial order reduction unsound:
max. 50 ms
max. > 1,000,000 decision within 6500 states error-trace
IBM WebSphere sound
heuristics
workflow decompose frag-
IBM WebSphere Business Modeler unsound:
graph state space
(RPST) ment erroneous
exploration
fragments
heuristics decides 97% of all fragments
decision within 165 states per fragment max. 62 ms
Woflan
sound
workflow structural Woflan state space
net S-coverability unsound + info
reduction exploration
133 processes
735 processes decision
sound unsound + info
251 processes 351 processes within 12 states max. 91 ms
one exception: 1 sec 14

Diagnostic information
 only 50% sound models
Analysis on Demand?
 state-space exploration A1 A2
 trace to error
B1
 experiment: traces of
X
reasonable length
B2 deadlock
 RPST fragments
 one error per fragment B B1
 can detect multiple errors X
 experiment: B2
unsound  2-7 error fragments
XOR/AND mismatch
 Woflan
 nodes that cause the error
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Conclusion
Analysis on Demand?
 checked soundness of 735 industrial business processes
 naïve state space exploration incomplete in practice
 apply reduction techniques (state space, structure)
 experiment with 3 different approaches
 max. < 91 ms per process
 allows for analysis on demand
 choose analysis technique depending on diagnostic info
 trace to error
 anti-patterns
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Future work
Analysis on Demand?
 Present diagnostic information to modeler
 Check models with more involved constructs
 e.g. BPMN event handler
 Check advanced properties
 Different combinations of techniques
 RPST fragments + partial order reduction
 Try by yourself: www.service-technology.org/soundness
 process models and
 links to: LoLA / IBM WebSphere + RPST plugin / Woflan
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