Modeling collaboration systems with Paradigm

Suzana Andova

joint work with

Luuk Groenewegen (LIACS) and Erik de Vink (FSA)

Collaboration systems

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Modeling Complex systems = components + cooperation

Component

Component

Component

collaboration

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Complex systems = components + cooperationS

Component

Component

Component

collaborationComponent

Component

Component

collaboration

Component

Component

Component

collaboration

Separate concerns: 1. Only static architecture

assignmentcollaboration

of Gr.1

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Student1

Student3

Student2

Separate concerns: 2. Collaboration dynamics

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Student1

Student3

Students2

assignment collaboration of Gr.1

Separate concerns: 3. Component (local) dynamics

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Student1

Student3

Students2

assignment collaboration of Gr.1

All together: collaboration on the assignment Gr.1

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Student1

Student3

Students2

assignment collaboration of Gr.1

Student1

Student3

Students2

assignment Y collaboration of Gr.5

All together: collaboration on all assignments

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Student1

Student3

Students2

assignment X collaboration of Gr.1

Student1

Student3

Students2

assignment Y collaboration of Gr.5

What can go wrong?

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Student1

Student3

Students2

assignment X collaboration of Gr.1

collaboration within the

group!

student’s own

planning

1. Inconsistency in the collaborations 2. Inconsistency in the local planning and/or

participation in the collaborations

Conclusion: needed be modeled and analyzed together

Paradigm language – modeling power

1. Language for describing collaboration between components

2. Notions to specify all concerns: architecture, collaboration dynamics and local component dynamics in the language

3. To model consistencies between all these concepts

4. Paradigm is very much suitable for modeling of system reconfiguration/ adaptation/ evolution (my favorite),

for instance• adding or removing a component from a collaboration, • changing the local behavior without destructing

collaborations, etc.

Paradigm language – model analysis

1. Paradigm has formally defined semantics

2. Translation of Paradigm in Process algebra TCP has been formally defined

3. This allows for (yet manual) translation of Paradigm models to mCRL2, which further allows for model analysis

4. Adding probabilistic behaviour to Paradigm, still only via examples

5. Translation of these models to PRISM for quantitative analysis

Paradigm language – open ends

1. Paradigm has formally defined semantics2. Translation of Paradigm in Process algebra TCP has been

formally defined? Which techniques can we use from PA to be applied

directly to Paradigm?

3. Translation (yet manual) of Paradigm models to mCRL2, which further allows for model analysis? Can we do better? More structure in the translation, thus

closer to automated translation4. Probe to add probabilistic behaviour to Paradigm, still only

via examples? To investigate how to integrate probabilistic semantics in

Paradigm, more examples, generalization?

For interested students

1. Will be given more examples of Paradigm models 2. Will be given PA and/or mCRL2 specifications to help

understanding Paradigm models easily and quickly3. Will be provided sufficient literature and supervision from me

and/or Erik de Vink 4. Possibilities to extend this work to master projects

Coordinates:

Suzana Andovas.andova@tue.nlHG 5.36phone: 5089

Erik de Vinkevink@win.tue.nlHG 6.72phone: 3146

Literature to start/continue with

• S. Andova, L.P.J. Groenewegen and E.P. de Vink,

Dynamic Consistency in Process Algebra: From Paradigm to ACP, Science of Computer Programming 76(8), 2011, page 711-735.

• S. Andova, L.P.J. Groenewegen and E.P. de Vink,

Towards reduction of Paradigm coordination models,

Proc. PACO 2011, EPTCS 60, 2011.

• S. Andova, L.P.J. Groenewegen and E.P. de Vink,

Towards Dynamic Adaptation of Probabilistic Systems,

Proc. ISOLA 2010, LNCS 6416, 2010, page 143-159.

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