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Dynamic Workflow Modeling and Analysis. J . Wang and R. Rosca Department of Software Engineering Monmouth Universit y. Outline. Motivation An intuitive and formal workflow model Well-formed workflows Verification Tool support Conclusion and future work. Motivation.

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dynamic workflow modeling and analysis

Dynamic Workflow Modeling and Analysis

J. Wang and R. Rosca

Department of Software Engineering

Monmouth University

Dynamic Workflow Modeling and Analysis

outline
Outline
  • Motivation
  • An intuitive and formal workflow model
  • Well-formed workflows
  • Verification
  • Tool support
  • Conclusion and future work

Dynamic Workflow Modeling and Analysis

motivation
Motivation
  • Driven by workflow design for incident command systems
  • Frequent changes of the course of action dictated by incoming events
    • Calls for on-the-fly verification of the workflow correctness
  • Predominantly volunteer-based workforce
    • Needs intuitive features for the description and modification of the WF
  • High stake
    • Needs formal approach (no ambiguity, allows analysis)
  • We introduced the Workflow Intuitive Formal Approach (WIFA) to meet the needs

Dynamic Workflow Modeling and Analysis

wifa workflow definition
WIFA Workflow Definition

A workflow is WF = (T, P, C, A, S0), where

  • T = {T1, T2, …Tm} is a set of tasks, m ≥ 1.
  • P = (p)mxm is the precedence matrix of the task set. If Ti is the direct predecessor of Tj, then pij = 1; otherwise, pij = 0.
  • C = (c)mxm is the conflict matrix of the task set. cij {0, 1} for i = 1, 2, …m and j =1, 2, … m.
  • A = (A(T1), A(T2), …, A(Tm)) defines pre-condition set for each task. TkT, A(Tk): *Tk . Let set A’A(Tk). Then TiA’ implies pik = 1.
  • S0{0, 1, 2, 3}m is the initial state of the workflow.

Dynamic Workflow Modeling and Analysis

example

T2

T6

T5

T4

T1

T7

T8

T3

Example

T = {T1, T2, …, T8},

A(T1) = Ø, A(T2) = {{T1}, {T6}}, A(T3) = {{T1}},

A(T4) = {{T2}}, A(T5) = {{T4}},

A(T6) = A(T7) = {{T5}}, A(T8) = {{T3, T7}}.

S0 = (1, 0, 0, 0, 0, 0, 0, 0).

,

Dynamic Workflow Modeling and Analysis

individual task state values
Individual Task State Values
  • S(Ti) = 0 means Ti is not executable at state S and not executed previously.
  • S(Ti) = 1 means Ti is executable at state S and not executed previously.
  • S(Ti) = 2 means Ti is not executable at state S and executed previously.
  • S(Ti) = 3 means Ti is executable at state S and executed previously.

Dynamic Workflow Modeling and Analysis

state transition rules
State Transition Rules
  • A set of rules to guide workflow execution
  • Denote by Sa(Ti)Sbthat task Tiis executed under state Sa, and the new state after the execution is Sb.
  • Rules: TjT,
    • If Tj = Ti then Sb(Tj) = 2. (Tj is just executed)
    • If Sa(Tj) = 0:
      • If pij = 1 and A’A(Tj) such that Sb(Tk) = 2 for any TkA’, then Sb(Tj) = 1;
      • otherwise Sb(Tj) = 0.

Dynamic Workflow Modeling and Analysis

state transition rules8

3

2

0

1

State Transition Rules
  • Sa(Tj) = 1

If cij = 0 then Sb(Tj) = 1; otherwise Sb(Tj) = 0.

  • Sa(Tj) = 2

If pij = 1 and A’A(Tj) such that Sb(Tk) = 2 for any TkA’, then Sb(Tj) = 3; otherwise Sb(Tj) = 2.

  • Sa(Tj) = 3

If cij = 0 then Sb(Tj) = 3; otherwise Sb(Tj) = 2.

State value change of a task

Dynamic Workflow Modeling and Analysis

state transition rules9
State Transition Rules
  • Example

T4

T2

T5

T7

T1

c23 = 1

T6

T3

S0 =(1, 0, 0, 0, 0, 0, 0)

S1 =(2, 1, 1, 0, 0, 0, 0)

S2 =(2, 2, 0, 1, 0, 0, 0)

S3 =(2, 0, 2, 0, 0, 1, 0)

… …

Dynamic Workflow Modeling and Analysis

modeling power

T2

T6

T5

T4

T1

T7

T8

T3

Modeling Power
  • Sequential execution
  • Conflict (decision making)
  • Concurrency
  • Synchronization
  • Loop

c23 = 0

c67 = 1

A(T2) = {{T1},{T2}}

A(T8) = {T3, T7}

Dynamic Workflow Modeling and Analysis

reachability tree

(1 0 0 0 0 0 0 0)

T1

(2 1 1 0 0 0 0 0)

T2

T3

(2 2 1 1 0 0 0 0)

(2 1 2 0 0 0 0 0)

T2

T3

T4

T4

(2 2 2 1 0 0 0 0)

(2 2 1 2 1 0 0 0)

(2 2 2 2 1 0 0 0)

T3

T5

T5

(2 2 1 2 2 1 1 0)

(2 2 2 2 2 1 1 0)

T3

T7

T6

T6

(2 3 1 2 2 2 0 0)

(2 3 2 2 2 2 0 0)

(2 2 2 2 2 0 2 1)

T3

T2

T2

T8

(2 2 1 3 2 2 0 0)

(2 2 2 3 2 2 0 0)

(2 2 2 2 2 2 0 2)

T3

T4

T6

T4

(2 2 1 2 3 2 0 0)

(2 2 2 2 3 2 0 0)

T6

T3

T5

T5

(2 2 1 2 2 3 1 0)

(2 2 2 2 2 3 1 0)

T3

T7

T7

(2 2 1 2 2 2 2 0)

(2 2 2 2 2 2 2 1)

T3

T8

(2 2 2 2 2 2 2 2)

Reachability Tree

Dynamic Workflow Modeling and Analysis

well f ormed workflows
Well-Formed Workflows
  • All reachable states form reachable set R
  • A workflow is well-formed if and only if the following two behavior conditions are met:
        • There is no dangling task
        • Given any reachable state, there is always an execution path leading the workflow to finish
  • Validation of a WF being well-formed requires the reachability analysis of the WF

Dynamic Workflow Modeling and Analysis

confusion f ree workflows
Confusion-Free Workflows
  • To simplify workflow modeling and verification
  • A confusion-free workflow
    • Is a well-formed workflow
    • Either all tasks triggered by the same task are in conflict, or no pairs of them are in conflict
    • A task becomes executable either when all of its predecessor tasks are executed, or when any one of them is executed
  • XOR-In-and-Out
  • AND-In-AND-Out
  • AND-In-XOR-Out
  • XOR-In-XOR-Out

Dynamic Workflow Modeling and Analysis

workflow dynamics
Workflow Dynamics
  • A couple of theorems developed for quick on-the-fly well-formedness verification
    • Theorem for adding new tasks to a WF, such that the new WF can preserve the confusion-free, well-formed properties (in the paper).
    • Theorem for deleting a task from the WF such that the new WF can preserve the confusion-free, well-formed properties.
    • Theorems for changing business rules that express task dependencies

Dynamic Workflow Modeling and Analysis

lemma 1

Tk

Tk1

Tk2

WFA

WFB

Lemma 1
  • Given a workflow WFA= (T, P, C, A, S0) with TkT. As shown in Fig, WFB = (T’, P’, C’, A’, S’0) is obtained by replacing Tk with Tk1 and Tk2, such that
    • *Tk1 = *Tk, Tk2* = Tk*, Tk1* = {Tk2} and * Tk2 = {Tk1},
    • A’ (Tk1) = A(Tk);
    • C’(Ti, Tj) = C(Ti, Tj) for Ti, Tj Tk*,

Then WFB is confusion-free well-formed iff WFA is confusion-free well-formed.

Dynamic Workflow Modeling and Analysis

lemma 2

Tk1

Tk2

Tk1

Tk2

WFA

WFB

Lemma 2
  • Let WFA = (T, P, C, A, S0) be a well-formed confusion-free workflow with Tk1, Tk2T, Tk1* = * Tk2 = , and Tk2 is not a predecessor of Tk1. As shown in the figure, WFB = (T’, P’, C’, A’, S’0) is obtained by introducing precedence constraint between Tk1 and Tk2 such that Tk1 is an immediate predecessor of Tk2. Then WFB is also well-formed and confusion-free.

Dynamic Workflow Modeling and Analysis

adding a new task
Adding a new task

Tk

Ti

WF

Tk

Ti

*Tk ≠ , Tk* = 

Tk

WF

*Tk = , Tk* ≠ 

WF

*Tk ≠ , Tk* ≠ 

Dynamic Workflow Modeling and Analysis

changing dependency

T6

T3

T5

T4

T7

T8

T1

T2

Changing dependency

T6

T3

T5

T4

T7

T8

T1

T2

Dynamic Workflow Modeling and Analysis

deleting a task

T6

T3

T3

T5

T5

T4

T4

T7

T7

T8

T8

T1

T1

T2

T2

Deleting a task

Dynamic Workflow Modeling and Analysis

tool support for editing validation and enactment of w f s
Tool Support for Editing, Validation and Enactment of WFs

Dynamic Workflow Modeling and Analysis

tool features
Tool Features
  • Saving workflow in XML or as an image
  • Drag and Drop interface
  • Dynamically change tasks/workflow properties
  • Zooming in and out to focus on specific sections of the workflow
  • Validate workflow
  • Visually step through workflow in design window
  • Step forward/backward through the simulation
  • Auto-play speed adjustment
  • Audit log – for post incident analysis

Dynamic Workflow Modeling and Analysis

conclusion
Conclusion
  • Introduced a new formalism to support dynamic workflow modeling and verification
  • Developed a set of theorems to validate the on-the-fly workflow changes
  • Implemented a tool to allow easy workflow construction, modification, verification and execution

Dynamic Workflow Modeling and Analysis

future work
Future Work
  • Data dependency
  • Decision support
  • Inter-organizational workflows
  • Tool enhancement

Dynamic Workflow Modeling and Analysis