Modeling for Sustainability

Modeling for SustainabilitySeminar at Lancaster UniversityDecember 5, 2016

Benoit Combemale (Inria & Univ. Rennes 1)http://people.irisa.fr/[email protected]@bcombemale

DiverSE Research Group

DiverSE team (env. 40 people)- 8 faculty members- 1 Research Engineer- ~20 PhD students- ~6 Software Engineers- ~6 Post doc

- 2Modeling for Sustainability – B. Combemale (Univ. Rennes 1) – December 4th, 2016

Complex Software-Intensive Systems

Software intensive systems

- 3

• Multi-engineering approach• Some forms of domain-specific modeling • Software as integration layer• Openness and dynamicity

Modeling for Sustainability – B. Combemale (Univ. Rennes 1) – December 4th, 2016

Aerodynamics

Authorities

Avionics

SafetyRegulations

Airlines

PropulsionSystem

MechanicalStructure

EnvironmentalImpact

NavigationCommunications

Human-Machine

Interaction

4

Multipleconcerns,

stakeholders, tools and methods

5

Aerodynamics

Authorities

Avionics

SafetyRegulations

Airlines

PropulsionSystem

MechanicalStructure

EnvironmentalImpact

NavigationCommunications

Human-Machine

Interaction

Heterogeneous Modeling

Model-Driven Engineering (MDE)

Distribution

« Service Provider Manager »

Notification Alternate Manager

« Recovery Block Manager »

ComplaintRecovery Block

Manager

« Service Provider

Manager »

Notification Manager


Complaint Alternate Manager

« Service Provider

Manager »

Complaint Manager

« Acceptance Test Manager »

Notification Acceptance Test

Manager


Complaint Acceptance Test

Manager


NotificationRecovery Block

Manager

« Client »

User Citizen Manager

Fault tolerance Roles

ActivitiesViews

Contexts

Security

Functional behavior

Bookstate : StringUser

borrow

return

deliver

setDamagedreserve

Use case

PlatformModel Design

ModelCode Model

Change one Aspect and Automatically Re-Weave:From Software Product Lines…..to Dynamically Adaptive Systems



- 7

J. Whittle, J. Hutchinson, and M. Rouncefield, “The State of Practice in Model-Driven Engineering,” IEEE Software, vol. 31, no. 3, 2014, pp. 79–85.

"Perhaps surprisingly, the majority of MDE examples in our study followed domain-specific modeling paradigms"

Distribution


Notification Alternate Manager


ComplaintRecovery Block

Manager

« Service Provider

Manager »

Notification Manager


Complaint Alternate Manager

« Service Provider

Manager »

Complaint Manager


Notification Acceptance Test

Manager


Complaint Acceptance Test

Manager


NotificationRecovery Block

Manager

« Client »

User Citizen Manager

Fault tolerance Roles

ActivitiesViews

Contexts

Security

Functional behavior

Bookstate : StringUser

borrow

return

deliver

setDamagedreserve

Use case

PlatformModel Design

ModelCode Model

Change one Aspect and Automatically Re-Weave:From Software Product Lines…..to Dynamically Adaptive Systems



- 8

Engineering Modeling Languages: Turning Domain Knowledge into Tools, by Benoit Combemale, Robert B. France, Jean-Marc Jézéquel, Bernhard Rumpe, Jim R.H. Steel, and Didier Vojtisek. Chapman and Hall/CRC, pp.398, 2016. Companion website: http://mdebook.irisa.fr



- 9

Editors(textuals, graphicals, …)

Test generators

Simulators

Analyzers

Refactoring

Checkers(static & dynamics)

Translators

Compilers

Code generators

Etc.

Engineering Modeling Languages: Turning Domain Knowledge into Tools, by Benoit Combemale, Robert B. France, Jean-Marc Jézéquel, Bernhard Rumpe, Jim R.H. Steel, and Didier Vojtisek. Chapman and Hall/CRC, pp.398, 2016. Companion website: http://mdebook.irisa.fr


- 10

J-M. Favre, D. Gasevic, R. Lämmel, and E. Pek. "Empirical language analysisin software linguistics," In Software Language Engineering, volume 6563 of LNCS, pages 316–326. Springer, 2011.

"Software languages are software too"


Software Language Engineering (SLE)

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• Application of systematic, disciplined, and measurable approaches to the development, deployment, use, and maintenance of software languages

• Supported by various kind of "language workbench"• Eclipse EMF, Xtext, Sirius, Melange, GEMOC, Papyrus• Jetbrain’s MPS• Spoofax• MS DSL Tools• Etc.

• Various shapes and ways to implement software languages• External, internal or embedded DSLs, Profile, etc.• Grammar, metamodel, ontology, etc.

• More and more literature, a dedicated Intl. conference (ACM SLE, cf. http://www.sleconf.org)…


- 12

J. Whittle, J. Hutchinson, and M. Rouncefield, “The State of Practice in Model-Driven Engineering,” IEEE Software, vol. 31, no. 3, 2014, pp. 79–85.

"A clear challenge, then, is how to integrate

multiple DSLs."


Globalization of Modeling Languages

- 13

Supporting coordinated use of modelinglanguages leads to what we call the globalizationof modeling languages, that is, the use of multiple modeling languages to support coordinateddevelopment of diverse aspects of a system.

Benoit Combemale, Julien DeAntoni, Benoit Baudry, Robert B. France, Jean-Marc Jezequel, Jeff Gray, "Globalizing Modeling Languages," Computer, vol. 47, no. 6, pp. 68-71, June, 2014


Globalization of Modeling Languages

- 14

• DSMLs are developed in an independent mannerto meet the specific needs of domain experts,

• DSMLs should also have an associatedframework that regulates interactions needed to support collaboration and work coordination across different system domains.

Benoit Combemale, Julien DeAntoni, Benoit Baudry, Robert B. France, Jean-Marc Jezequel, Jeff Gray, "Globalizing Modeling Languages," Computer, vol. 47, no. 6, pp. 68-71, June, 2014


Globalization of Modeling Language

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• Context: new emerging DSML in open world⇒ impossible a priori unification⇒ require a posteriori globalization

• Objective: socio-technical coordination to support interactions across different system aspects

⇒ Language-based support for technical integration of multiples domains⇒ Language-based support for social translucence

• Community: the GEMOC initiative (cf. http://gemoc.org)

"Globalizing Domain-Specific Languages," Combemale, B., Cheng, B.H.C., France, R.B., Jézéquel, J.-M., Rumpe, B. (Eds.). Springer, Programming and Software Engineering, Vol. 9400, 2015.


The GEMOC Initiative

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An open and international initiative to• coordinate (between members)• disseminate (on behalf the members)

worldwide R&D effortson the globalization of modeling languages

http://gemoc.org

@gemocinitiative


The GEMOC Studio

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Design and integrate your executable DSMLs

http://gemoc.org/studioLanguageWorkbench

ModelingWorkbench

Edit, simulate and animate your heterogeneous models


The GEMOC Community


- 19

"On the unification power of models"


⎯ Jean Bézivin

From Software Systems

- 20

• software design models for functional and non-functional properties


Engineers

System Models

Software

To Cyber-Physical Systems

- 21

Engineers

System Models Cyber-PhysicalSystem

sensors actuators

Physical System

Software

<<controls>><<senses>>

• multi-engineering design models for global system properties

• models @ runtime (i.e., included into the control loop) for dynamic adaptations


To Smart Cyber-Physical Systems

- 22

Engineers

System Models SmartCyber-Physical System

Context

sensors actuators

Physical System

Software


• analysis models (incl. large-scale simulation, constraint solver) of the surrounding context related to global phenomena (e.g. physical, economical, and social laws)

• predictive models (predictive techniques from AI, machine learning, SBSE, fuzzy logic)

• user models (incl., general public/community preferences) and regulations (political laws)


An MDE Approach for Smart CPS Development

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• Convergence of engineering and scientific models

• A modeling framework to support the integration of data from sensors, open data, laws, regulations, scientific models (computational and data-intensive sciences), engineering models and preferences.

• Domain-specific languages for socio-technical coordination• to engage engineers, scientist, decision makers, communities

and general public• to integrate analysis/predictive/user models into the control loop

of smart CPS


Application to Sustainability Systems

- 24

• Sustainability systems are smart-CPS for managing resource production, transport and consumption, for the sake of sustainability

• Ex: smart grids, smart city/home/farming, etc.

• Sustainability systems must balance trade-offs between the social, technological, economic, and environmental pillars of sustainability

• involve complex decision-making with heterogeneous analysis models, and large volumes of disparate data varying in temporal scale and modality


Application to Sustainability Systems

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• Scientific models are used to understand sustainability concerns and evaluate alternatives (what-if/for scenarios)

• Engineering models are used to support the development and runtime adaptation of sustainability systems.

How to integrate engineering and scientific models in a synergistic fashion to support informed decisions, broader engagement, and dynamic adaptation in sustainability systems?

B. Combemale, B. Cheng, A. Moreira, J.-M. Bruel, J. Gray, "Modeling for Sustainability," MiSE@ICSE 2016


Using MDE in Sustainability Systems

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The Sustainability Evaluation ExperienceR (SEER)⎯ 1st Modelling For Sustainability Workshop @ Bellairs, 2016

Policy makers(e.g., mayor)

Communities(e.g., farmers)

General public(e.g., individuals)

open data regulations

physical laws

explore the future

andmake it happen



- 27

• Smart Cyber-Physical Systems

Sustainability System(e.g., smart farm)

(

Context

sensors actuators

Production/Consumption

System (e.g. farm)

Software




- 28

• Based on informed decisions• with environmental, social and economic laws• with open data

Heuristics-Laws

Scientists

Open DataScientific Models / Physical Laws (economic, environmental, social)

SEER


(

Context

sensors actuators


System (e.g. farm)

Software

<<controls>><<senses>><<supplement

field data>>

<<feed>>

<<integrate>>

<<explore model relations (tradeoff,

impact and conflict)>>



- 29

• Providing a broader engagement• with "what-if" scenarios for general public and policy makers

Heuristics-Laws

Scientists

Open Data

General Public(e.g., individuals) Policy Makers

(e.g., mayor)

MEEs("what-if" scenarios)

Scientific Models / Physical Laws (economic, environmental, social)

SEER


(

Context

sensors actuators


System (e.g. farm)

Software

<<controls>><<senses>>Communities(e.g., farmers)

<<supplementfield data>>

<<provide configuration, preferences, questions>>

<<present possible future and variable indicators>>

<<feed>>

<<integrate>>




Heuristics-Laws

Scientists

Open Data


(e.g., mayor)



SEER


(

Context

sensors actuators


System (e.g. farm)

Software


<<adapt>>




<<feed>>

<<integrate>>




- 30

• Supporting automatic adaptation• for dynamically adaptable systems



- 31

• Application to health, farming system, smart grid…

Heuristics-Laws

Scientists

Open Data


(e.g., mayor)



SEER


(

Context

sensors actuators


System (e.g. farm)

Software


<<adapt>>




<<feed>>

<<integrate>>




Heuristics-Laws

Scientists

Open Data


(e.g., mayor)



SEER


(

Context

sensors actuators


System (e.g. farm)

Software


<<adapt>>




<<feed>>

<<integrate>>



Farming System Modeling

- 32

Farmers

Agronomist

IrrigationSystem

in collaboration with

Jean-Michel Bruel, Benoit Combemale, Ileana Ober, Hélène Raynal, "MDE in Practice for Computational Science," International Conference on Computational Science (ICCS), 2015.


- 33

https://github.com/gemoc/farmingmodeling

Farming System Modeling


Conclusion

- 34

• From MDE to SLE• Language workbenches support DS(M)L development

• On the globalization of modeling languages• Integrate heterogeneous models representing different

engineering concerns• Language interfaces to support structural and behavioral

relationships between domains (i.e., DSLs)

• From software systems to smart CPS• Interactions with the physical world limited to (i.e., fixed, in closed

world) control laws and data from the sensors• What about the broader context in which the system involves?

• Physical / social / economic laws • Predictive models• Regulations, user preferences


Conclusion

- 35

• Require to integrate scientific models in the control loop of smart CPS to provide more informed decisions, a broader engagement, and eventually relevant runtime reconfigurations

• SEER is a particular instantiation of such a vision for sustainability systems

Software is eating the world, but…may the world drive software!


Open Challenges

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• Diversity/complexity of DSL relationships• far beyond structural and behavioral alignment, refinement,

decomposition• Separation of concerns vs. Zoom-in/Zoom-out

• Live and collaborative modeling• minimize the round trip between the DSL specification, the

model, and its application (interpretation/compilation)• Model experiencing environnements• What-if/for scenarios

• Integration of analysis and predictive models into DSL semantics


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"If you believe that language design can significantlyaffect the quality of software systems, then it shouldfollow that language design can also affect the quality of energy systems. And if the quality of suchenergy systems will, in turn, affect the livability of our planet, then it’s critical that the languagedevelopment community give modeling languagesthe attention they deserve." − Bret Victor (Nov., 2015), http://worrydream.com/ClimateChange


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