Taxonomy of Flexible Flexible Linguistic Commitments Dr. Vadim - - PowerPoint PPT Presentation

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Taxonomy of Flexible Flexible Linguistic Commitments Dr. Vadim - - PowerPoint PPT Presentation

Sep 17, 2023 143 likes •650 views

Taxonomy of Flexible Flexible Linguistic Commitments Dr. Vadim Zaytsev aka @grammarware FlexMDE 2015 What if you miss? Type a quote here. Johnny Appleseed

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Taxonomy of Flexible Linguistic Commitments

  • Dr. Vadim Zaytsev aka @grammarware

FlexMDE 2015

Flexible

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–Johnny Appleseed

“Type a quote here.”

http://cheezburger.com/635909/funny-memes-images-that-prove-design-isnt-for-everybody

What if you miss?

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Mega start

Source Model Transformation Instance Target Model

Jean-Marie Favre, Towards a Basic Theory to Model MDE, 2004.

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Mega start

Source Model

ε

Source Language Transformation Instance Transformation Function Target Model

ε

Target Language

Jean-Marie Favre, Towards a Basic Theory to Model MDE, 2004.

ε

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Mega start

Source Model

ε

Source Language Source Metamodel Transformation Instance Transformation Function Transformation Model Target Model

ε

Target Language Target Metamodel

μ μ μ

Jean-Marie Favre, Towards a Basic Theory to Model MDE, 2004.

ε

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Mega start

Source Model

ε

Source Language

χ

Source Metamodel Transformation Instance Transformation Function Transformation Model Target Model

ε

Target Language Target Metamodel

μ μ χ μ

Jean-Marie Favre, Towards a Basic Theory to Model MDE, 2004.

ε

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Focus

Source Model

ε

Source Language

χ

Source Metamodel Transformation Instance Transformation Function Transformation Model Target Model

ε

Target Language Target Metamodel

μ μ χ μ ε

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Problem 0: Precision

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Two languages

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One language

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Tell me about your refactoring

✓ You accept ✓ all of Java ✓ nothing else ✓ Transform it ✓ Produce ✓ nothing besides ✓ use all features

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Two languages

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Assumed commitment

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Partial applicability

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Language subset

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Conservative mapping

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Liberal mapping

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Robust mapping

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Antirobust mapping

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Fault recovery

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Fault tolerance

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Overtolerance

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Shotgun effect

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Shotgun

http://langsec.org/

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Problem I: Application

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Function extension

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Function extension

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Goal is clear

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Function extension

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Function extension

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Goal is unclear

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Problem II: Composition

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Liberal + conservative = ?

might not be the same extension!

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Streamliners

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=

identity

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Use of =

partial to complete applicability

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  • canoniser
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function composition

  • Use of
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  • codifier
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Use of

preventing the shotgun effect

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normaliser

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Use of

function composition

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Problem III: Calibration

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  • ~

calibrator

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~

regulator

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Problem IV: Overapproximation

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(L→L)→(L→L)→(L→L)

we might get a subset in the end

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id || (L→L) is (L→L)

the only case where streamliners do not help

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Conclusion

✓ Flexible commitments everywhere ✓ Can be considered precisely ✓ Mapping extension is not trivial ✓ Composition with streamliners ✓ Calibration is still not trivial ✓ Occasional overapproximation ✓ Demo at 16:15! ✓ Questions?