Vrification probabiliste de proprits de modles AltaRica 3.0 - - PowerPoint PPT Presentation

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Vrification probabiliste de proprits de modles AltaRica 3.0 - - PowerPoint PPT Presentation

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Vrification probabiliste de proprits de modles AltaRica 3.0 Benjamin Aupetit OpenAltaRica, IRT SystemX Laboratoire de Gnie Industriel, CentraleSuplec 16 Mars 2017 Journe "Jeunes Ingnieurs Jeunes Chercheurs" 1

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Vérification probabiliste de propriétés de modèles AltaRica 3.0

Benjamin Aupetit OpenAltaRica, IRT SystemX Laboratoire de Génie Industriel, CentraleSupélec

16 Mars 2017 Journée "Jeunes Ingénieurs Jeunes Chercheurs"

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Introduction

Encadrement de thèse :

  • Antoine Rauzy (Pr) (IPK, NTNU)
  • Jean-Marc Roussel (MCF HDR) (LURPA, ENS Cachan)

Projet OpenAltaRica, IRT SystemX

  • Michel Batteux (Dr) (IRT SystemX)

Projet OpenAltaRica :

  • Partenaires Premium
  • Partenaires Adhérent

16 Mars 2017 Journée "Jeunes Ingénieurs Jeunes Chercheurs"

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Introduction

Thèse

  • Débutée en Octobre 2014
  • Fin prévue en Septembre 2017

16 Mars 2017 Journée "Jeunes Ingénieurs Jeunes Chercheurs"

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Vérification probabiliste de propriétés de modèles AltaRica 3.0

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Introduction

  • Safety Assessment
  • Predictive analysis

– Probabilistic – On models of a system

  • Dynamic behavior
  • Modeling formalism: AltaRica 3.0

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OpenAltaRica Project

16 Mars 2017 Journée "Jeunes Ingénieurs Jeunes Chercheurs"

Systems Specifications Models

class HydraulicPump Boolean working (init = false); event failure (delay = exponential(lambda)); transition failure: working -> working := false; end

AltaRica 3.0

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Objectives : Develop the ecosystem around the AltaRica 3.0 modeling language for the safety analysis of critical systems

OpenAltaRica Project

16 Mars 2017 Journée "Jeunes Ingénieurs Jeunes Chercheurs"

  • Federate a community of users.

Forum

  • The Platform OpenAltaRica
  • The reference Implementation;
  • Software tools the more accurate.
  • Integration with other

engineering disciplines

  • Comply with certification processes

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OpenAltaRica Project

AltaRica 3.0 Workshop

16 Mars 2017 Journée "Jeunes Ingénieurs Jeunes Chercheurs"

AltaRica 3.0 Editor

Fault Trees compiler Stepwise simulator Markov Chains generator Stochastic simulator Model Checker Sequences generator Specifications AltaRica 3.0 Descriptions

block Plane_HydraulicSystem block HydraulicLine1 Pump P1, P2; Valve V1, V2,V3; …. assertion V1.inFlow := P1.outFlow; …. end …. end

class NRC Boolean working (init = true); parameter Real lambda = 0.00001; event failure (delay = exponential(lambda)); transitions failure: working -> working := false; end class Pump extends NRC; Boolean inFlow, outFlow (reset = false); assertion if working then outflow := inFlow; end class Valve extends NRC; Boolean inFlow, outFlow (reset = false); assertion if working then outflow := inFlow; end

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Pilot Interface Physical Computing Modules

Stochastic Simulation

Landing System:

  • AltaRica 3.0 modeling:

– 129 components, ~1000 variables – State-space size: 2.6 × 10105

16 Mars 2017 Journée "Jeunes Ingénieurs Jeunes Chercheurs"

Landing System example

Handle Lights Analogical Switch ElectroValves Cylinders Sensors Computing Module A Computing Module B x3 x5 x6 x36

The Landing Gear System Case Study, F. Boniol, V. Wiels (ONERA), ABZ 2015

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Stochastic Simulation

16 Mars 2017 Journée "Jeunes Ingénieurs Jeunes Chercheurs"

State-space exploration

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Stochastic Simulation

Stochastic simulation problems:

  • Correctness

– Quality assurance

  • Performance

– Significant results

  • Usefulness

– Exploiting the tool to obtain useful informations

  • n the system

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Stochastic Simulation

  • Standards
  • DO-178C/ED-12C : Software Considerations in Airborne Systems and Equipment Certification
  • DO-330/ED-215 : Tool Qualification

– The user has to qualify the tool used

  • Evaluation kit

– To allow the user to evaluate the correctness, performances and pertinence of a stochastic simulation tool

16 Mars 2017 Journée "Jeunes Ingénieurs Jeunes Chercheurs"

Vers la définition d’un kit d’évaluation pour les simulateurs stochastiques, B. Aupetit, M. Batteux, A. Rauzy, J.-M. Roussel, Lambda-Mu 20 (2016)

A C B D A C B D A C B D

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Stochastic Simulation

Performances improvement

  • Compilation techniques
  • Use of the Evaluation Kit and profilage

Landing System example

  • Simulation of 2 × 109 landing/take-off
  • Original : 3 years (estimated)
  • Improved : 17 hours
  • 1500 times faster

16 Mars 2017 Journée "Jeunes Ingénieurs Jeunes Chercheurs"

AltaRica 3.0 Stochastic Simulation Evaluation kit AltaRica 3.0 Stochastic Simulator Execution results (profilage) Tool Improvement

Improving performances of the AltaRica 3.0 stochastic simulator, B. Aupetit, M. Batteux, A. Rauzy, J.-M. Roussel, ESREL (2015) 12

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Stochastic Simulation

Properties

  • Classical safety properties and indicators

– MTBF : Mean Time Between Failures – MTTF : Mean Time To Failures – MTTR : Mean Time To Repair

  • Classical performances properties and indicators

– Availability, …

  • Complex properties

– Probability to not detect a failure when in a critical state – Mean time to perform a specific action when in a critical state – Probability to recover from a critical state

Landing System example:

– Gears are indicated out but are not – Gears are moving when the doors are not open – Gears are not locked out more than 15s after the order without alarm

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Stochastic Simulation

Stochastic simulation problems :

  • Correctness

– Quality assurance –  Solution : Evaluation Kit

  • Performance

– Significant results –  Solution : Profilage and Optimizations

  • Usefulness

– Exploiting the tool to obtain useful information on the system –  Solution : Stochastic Model-Checking

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Stochastic Model-Checking

Stochastic Model-Checking :

  • Interaction between

– Stochastic simulation – Properties checking

  • To obtain statistical results
  • Landing System example
  • Safety properties

– 11 False occurrence out of 𝟑 × 𝟐𝟏𝟘 operations

  • Probability: 𝟔. 𝟔 × 𝟐𝟏−𝟘
  • Margin of error (95%): 𝟖. 𝟓 × 𝟐𝟏−𝟐𝟓

16 Mars 2017 Journée "Jeunes Ingénieurs Jeunes Chercheurs"

Stochastic Simulation Properties checking Stochastic Model-Checking Results  Req 1 : 100 % ± 0.01  Req 2 : 100 % ± 0.01  Req 3 : 42 % ± 0.01 Not OK

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Conclusion

  • Tools must be evaluated before being used
  • Complex safety properties can be checked using stochastic

simulation Continuation

  • Property expression language
  • Stochastic model-checking tool

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Vérification probabiliste de propriétés de modèles AltaRica 3.0

Benjamin Aupetit OpenAltaRica, IRT SystemX Laboratoire de Génie Industriel, CentraleSupélec

16 Mars 2017 Journée "Jeunes Ingénieurs Jeunes Chercheurs"

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