Example-Driven Modeling Using

Michał Antkiewicz, Kacper Bąk, Krzysztof Czarnecki, Zinovy Diskin, Dina Zayan1, and Andrzej Wąsowski2

mantkiew@gsd.uwaterloo.ca 1University of Waterloo

2IT University of Copenhagen

MDEBE, MODELS, Miami, Sep. 29, 2013

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Domain Knowledge Transfer

Alice (SME) Bob (BA)

o Domain novice Domain experto Novice modeler• examples

Modeling expert• abstractions

Domain Model

Example-Driven Modeling [1]

“An approach to systematically using explicit examples for eliciting, modeling, verifying,

and validating complex domain knowledge”

Examples + AbstractionsModel =

[1] Bąk et al., Example-Driven Modeling. Model = Abstractions + Examples, NIER, ICSE'13 3

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Why Apply Example-Driven Modeling?

H1: Constructing models with the aid of explicit examples improves the quality of models.

H2: Augmenting models with explicit examples improves model comprehension among various stakeholders [2].

[2] Zayan, Antkiewicz, Czarnecki, Effects of Using Examples on Structural Model Comprehension (submitted)

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H3: Begin with examples or abstractions; switch

H4: Tools validate abstractions wrt. examples

H5: Variety of examples

H6: Positive and negative examples

How to do Example-Driven Modeling?

Languages? Methods? Tools?

We present a vision of how EDM should be done in a scenario, and how it can be

supported by a language and a tool

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class feature referencehttp://clafer.org

• Lightweight structural modeling language – One construct (clafer)/many roles– Feature and configuration modeling– Meta- and (partial) instance modeling

• Yet powerful– First-order predicate/relational logic– Constraint language inspired by Alloy

•

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Instance Generator

• Reasoner for Clafer– Finite-scope analysis– Model consistent

Þ All correct instantiations

– Model inconsistent Þ UnSAT Core + a near-miss instance

• Clafer Tools Binary Distributions [3]

[3] http://gsd.uwaterloo.ca/clafer-tools-binary-distributions

A Domain Knowledge Elicitation Scenario

Alice (SME) Bob (BA)

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Part 1: Examples only

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JuneSteven 1

midYearReview month -> June chair -> Steven room -> C participant 1..* onlineParticipant +C whiteboard audioConferencing

Our members often book rooms for meetings.

Give me an example of a room booking, please.

We have a mid-year review meeting in June. It is organized by Steven,a chair, and is held in the meeting room C that provides a whiteboard

and audioconferencing equipment to include online participants.

JuneStevenmidYearReview month -> June chair -> Steven room -> C participant$1 participant$2 onlineParticipant$1C whiteboard audioConferencing

ClaferIG

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Another example is an on-demand meeting organized within workhours. Joanna, a team-leader, sometimes meets other team members

in room D. They use a whiteboard and have no online participants.

Joanna

ondemandMeeting chair -> Joanna participant + onlineParticipant 0 room -> D

D whiteboard

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No, there are two chairs, but a meeting must have exactly one chair. Also, it is our policy that rooms cannot be booked for

meetings with online participants only. The maximum number of online participants supported by our system is 20. Finally, one cannot have a meeting with online participants without

audio conferencing equipment!

Al

John

aMeeting chair -> Al, John participant 0 onlineParticipant 25 room -> E

E whiteboard

Is this example valid?

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There's no chair, which is required. I am also unsure if we have any rooms without a whiteboard.

Tom

Ed

aMeeting participant -> Tom onlineParticipant -> Ed room -> F

F audioConferencing

Is this example valid?

Part 1: Summary

Examples helped ground the discussion, elicit the missing constraints, and uncover tacit knowledge

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Part 2: Abstraction Inference

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abstract Member

abstract Room

abstract Meeting

JuneSteven : MembermidYearReview : Meeting month -> June chair -> Steven room -> C participant -> Member + onlineParticipant -> Member 1..20

C : Room whiteboard audioConferencing

Joanna : Member

ondemandMeeting : Meeting chair -> Joanna room -> D participant -> Member + onlineParticipant -> Member 0

D : Room whiteboard

Let’s extract the commonality to the abstractions.

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abstract Member

abstract Room whiteboard ? audioConferencing ?

abstract Meeting chair -> Member room -> Room participant -> Member + onlineParticipant -> Member 0..20 [ some onlineParticipant => some room.audioConferencing ]

June

Steven : Member

C : Room whiteboard 1 audioConferencing

midYearReview : Meeting month -> June chair -> Steven room -> C onlineParticipant -> Member 1..20

Joanna : Member

D : Room whiteboard audioConferencing 0

ondemandMeeting : Meeting chair -> Member = Joanna room -> D onlineParticipant -> Member 0

redefinition

Part 2: Summary

The abstractions look the same as the examples thanks to redefinition [4][5].The abstractions can capture more general constraints than examples.

19[4] Bąk et al. Partial Instances via Subclassing, SLE’13[5] Bąk et al. Unifying class and feature modeling (submitted)

Part 3: Example Derivation

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aMember : Member 2..5

aMeeting : Meeting [ some onlineParticipant ]

aRoom : Room

So far, our abstractions look quite good. Let’s automatically derive a few examples. Are they valid?

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aMember$1 : MemberaMember$2 : MemberaMember$3 : Member

aMeeting : Meeting chair -> aMember$3 room -> aRoom participant -> aMember$3 onlineParticipant$1 -> aMember$3 onlineParticipant$2 -> aMember$2 onlineParticipant$3 -> aMember$1

aRoom : Room audioConferencing

aMember$1 : MemberaMember$2 : Member

aMeeting : Meeting chair -> aMember$2 room -> aRoom participant$1 -> aMember$1 participant$2 -> aMember$2 onlineParticipant -> aMember$2 aRoom : Room whiteboard audioConferencing

No, they are invalid! A chair cannot be a participant.Also, no member can participate both on-site and on-line.

ClaferIG

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abstract Meeting chair -> Member [ chair not in participant.ref ] [ chair not in onlineParticipant.ref ] room -> Room participant -> Member + onlineParticipant -> Member 0..20 [ no participant.ref & onlineParticipant.ref ] [ some onlineParticipant => some room.audioConferencing ]

Then we need to add the missing constraints.

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aMember$1 : MemberaMember$2 : MemberaMember$3 : MemberaMember$4 : MemberaMember$5 : Member

aMeeting : Meeting chair -> aMember$1 room -> aRoom participant -> aMember$5 onlineParticipant$1 -> aMember$4 onlineParticipant$2 -> aMember$3 onlineParticipant$3 -> aMember$2

aRoom : Room audioConferencing

aMember$1 : MemberaMember$2 : MemberaMember$3 : MemberaMember$4 : Member

aMeeting : Meeting chair -> aMember$1 room -> aRoom participant$1 -> aMember$4 participant$2 -> aMember$3 onlineParticipant -> aMember$2

aRoom : Room whiteboard audioConferencing

These examples are valid!

ClaferIG

Part 3: Summary

Automatic example derivation helped uncover missing constraints, extend and subsequently validate the model.

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Summary

• A vision for doing EDM• Applied Clafer & ClaferIG in a scenario– Abstraction inference– Example derivation– Abstractions checking

• Demonstrated supporting language features

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Conclusions (i)

• Variety of examples– Partial examples• Focus on an area

– Positive examples • Correct scenarios

– Near-miss negative examples • Constraint violations

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Conclusions (ii)

• Language design to support EDM– Single modeling concept: clafer– Unified syntax for examples and abstractions– Key mechanism: redefinition– Partial examples– Partial typing– Specialization– Extension

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Open Questions

• Cost/benefit ratio of EDM?– Study industrial use

• What type of examples?• How to collect them?• How many are needed?• How diverse are needed?• How to infer abstractions from examples?• How to support co-evolution?

Example-Driven Modeling Using

Thank You!

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