automatic workflow graph refactoring and completion - ibm › researcher › files › ... ·...

IBM Zurich Research Laboratory | Business Integration Technologies

© 2008 IBM Corporation

The 6th International Conference on Service Oriented Computing (ICSOC 2008)

December 2008

Automatic Workflow GraphRefactoring and Completion

Jussi Vanhatalo [email protected] Völzer [email protected] Leymann [email protected] Moser [email protected]


© 2008 IBM Corporation2

Workflow graphs

� A workflow graph represents the control flow of a business process model

– Business Process Modeling Notation (BPMN)

– UML 2 Activity Diagrams

– Event-driven Process Chains (EPCs)

Processbank account

payment

Processcredit card

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Prepareshipment

Receiveorder

Deliverproduct



Research problem: How to complete a workflow graph?

� Use case: Complete a partial workflow graph at modeling time [Gschwind, Koehler, Wong, BPM 2008]

– Add exclusive and/or parallel gateways to join the open ends

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p2 eProcessbank account

payment

Processcredit card

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Prepareshipment

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Soundness of a completion

� A completed workflow graph should be sound:

– No deadlock, and

– No lack of synchronizationDeadlock

Lack of synchronization

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Why would we benefit from an automatic technique?

� Other use cases:

– Local termination detection

– Runtime optimization

� Difficulties:

– A completion may be complicated

– Workflow graphs may be large

• Hundreds of edges and nodes

– Should be sound for execution

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Outline

� Introduction to the research problem

� Automatic completion of workflow graphs

– The refined process structure tree (RPST)

– Fast completion technique

– General completion technique

– Hybrid completion technique

� Automatic refactoring of workflow graphs

� Conclusion



The refined process structure tree (RPST)

� An R-fragment is a set of edges that form a connected subgraph that has exactly one entry node and exactly one exit node.

� An canonical R-fragment does not overlap with any R-fragment.

– Therefore, the canonical R-fragments form a hierarchy.

� The refined process structure tree is the tree of canonical R-fragments of a workflow graph G, such that the parent of a canonical R-fragment F is the smallest canonical R-fragment of G that properly contains F.

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[Vanhatalo, Völzer,Koehler, BPM 2008]



Fast completion technique

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� Fast: Computed in linear time based on the refined process structure tree

� An incomplete technique

� Finds a user-friendly completion: each join of the completion is paired with a split

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1) Simplecompletion

& RPST

2) R-fragment based node splitting

3) Determinegateway types

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General completion technique

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� A complete technique: finds a completion if it exists

� Finds a compact completion

� Based on state space exploration: exponential worst case complexity



General completion technique

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1) Compute the final states, i.e., S1 = {e1, e3}, S2 = {e2, e3}

2) Compute a set of tests, where

� each test has exactly one end node from each final state, and

� each end node is in at least one test.� I.e., T1 = {e1, e2}, T2 = {e3}

3) Create an XOR-join for each test, and connect the end nodes of this test to this XOR-join

4) Create an AND-join, and connect the XOR-joins of each test to this AND-join



Existence of a completion

� Some workflow graphs may not have a (sound) completion

� We characterize the workflow graphs for which a completion exists

– We can determine this with an algorithm

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Hybrid completion technique

� Combines the best of both worlds:– Fast in practice

• Transforms the workflow graph using the fast technique• The general technique only applied locally• With our library: at most 38 states instead of more than 100,000 states

– A complete technique – Finds a user-friendly completion: join-split pairing, where applicable

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The general completion vs. the hybrid completion

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Result of the hybrid completion technique

Result of the general completion technique



Outline




– Refactoring technique

– Other use cases of the refined process structure tree

� Conclusion



Automatic refactoring of workflow graphs

� A well-structured workflow graph has matching pairs of splits and joins

– Easier to comprehend [van der Aalst et al., 2002], and analyze [Vanhatalo et al., ICSOC 2007]

� We present an RPST based refactoring technique that splits nodes to make a workflow graph more well-structured

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Original workflow graph Well-structured version



Other use cases of the refined process structure tree

� Translating a graph-based process model (e.g. BPMN) into a block-based process model (e.g. BPEL) [Vanhatalo et al., BPM 2008]

� Speeding up control-flow analysis [Vanhatalo et al., ICSOC 2007]

� Pattern-based editing [Gschwind et al., BPM 2008]

� Process merging [Küster et al., BPM 2008]

� Understanding large process models

� Subprocess detection



Outline




� Conclusion



Conclusions

� New completion techniques

1. The fast completion technique

• Based on the refined process structure tree• Fast but incomplete

2. The general completion technique

• Complete but potentially slow

3. The hybrid completion technique

• Complete and faster than the general technique

� A new refactoring technique

– Transforms a workflow graph into a more well-structured form



Backup slides



Refactoring technique for making structure more explicit

� The RPST based refactoring technique

– Splits nodes based on R-fragments

• If an R-fragment has more than one entry edge (or exit edge), then split the entry node (or the exit node) to normalize the R-fragment

� Results a normal form that is, in general, more well-structured

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Use Cases of a Completion Technique

� Complete a partial workflow graph at modeling time

� Runtime optimization:

– Execute models containing inclusive OR-joins faster

– Turn off the dead-path-elimination (DPE) in BPEL

� Local termination detection at the single end node



The Normal Process Structure Tree

� An N-fragment is a set of nodes that form a connected subgraph that has exactly one entry edge and exactly one exit edge.

� An canonical N-fragment does not overlap with any N-fragment.

– Therefore, the canonical N-fragments form a hierarchy.

� The normal process structure tree is the tree of canonical N-fragments of a workflow graph G, such that the parent of a canonical N-fragment F is the smallest canonical N-fragment of G that properly contains F.

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The Refined Process Structure Tree

� An R-fragment is a set of edges that form a connected subgraph that has exactly one entry node and exactly one exit node.

� An canonical R-fragment does not overlap with any R-fragment.

– Therefore, the canonical R-fragments form a hierarchy.

� The refined process structure tree is the tree of canonical R-fragments of a workflow graph G, such that the parent of a canonical R-fragment F is the smallest canonical R-fragment of G that properly contains F.

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More Precisely:

� If anything inside a fragment F is executed, then

– the entry node was executed before, and

– the exit node will be executed afterwards

� A boundary node is an entry if

– all incoming edges are outside F, or

– all outgoing edges are inside F

� A boundary node is an exit if

– all incoming edges are inside F, or

– all outgoing edges are outside F

� A fragment F is a connected subgraph that has

– exactly two boundary nodes,

– one entry, and one exit

� [Tarjan and Valdes, 1980]These boundary nodes are

neither entries nor exits

Not a fragment!

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References

� [HT73] J. Hopcroft and R. E. Tarjan. Dividing a graph into triconnected components. SIAM J. Comput., 2:135–158, 1973.

� [Val78] Jacobo Valdes Ayesta. Parsing flowcharts and series-parallel graphs. PhD thesis, Stanford, CA, USA, 1978.

� [TV80] Robert E. Tarjan and Jacobo Valdes. Prime subprogram parsing of a program. In POPL ’80: Proceedings of the 7th ACM SIGPLAN-SIGACT symposium on Principles of programming languages, pages 95–105, New York, NY, USA, 1980. ACM.

� [JJP94] Richard Johnson, David Pearson, and Keshav Pingali. The program structure tree: Computing control regions in linear time. In Proceedings of the ACM SIGPLAN’94 Conference on Programming Language Design and Implementation (PLDI), pages 171–185, 1994.

� [Joh95] Richard Craig Johnson. Ecient program analysis using dependence flow graphs. PhD thesis, Ithaca, NY, USA, 1995.

� [GM00] Carsten Gutwenger and Petra Mutzel. A linear time implementation of SPQR-trees. In Joe Marks, editor, Graph Drawing, volume 1984 of Lecture Notes in Computer Science, pages 77–90. Springer, 2000.

� [VVL07] Jussi Vanhatalo, Hagen Völzer, and Frank Leymann. Faster and more focused control-flow analysis for business process models though SESE decomposition. In 5th International Conference on Service-Oriented Computing (ICSOC), volume 4749 of Lecture Notes in Computer Science, pages 43–55. Springer-Verlag Berlin Heidelberg, September 2007.

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