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AltaRica A Formal Language for Event Oriented Modeling A. Rauzy IML/CNRS & ARBoost Technologies Marseilles, France

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Contents I.Introductory Examples II.Motivations III.Formal Model IV.Tools V.Examples of Use VI.Perspectives

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Contents I.Introductory Examples II.Motivations III.Formal Model IV.Tools V.Examples of Use VI.Perspectives

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A repairable component node component state s: {working,failed,repair}; event failure, startRepair, endRepair; trans (s=working) |- failure -> s:=failed (s=failed) |- startRepair -> s:=repair; (s=repair) |- endRepair -> s:=working; init s:=working edon

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A Valve node valve state closed:bool; flow input:float:in; output:float:out; event open, close; trans closed |- open -> closed:=false; not closed |- close -> closed:=true; init closed := true; assert output = if closed then 0 else input; edon

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Two Valves in Series node twoValves flow input:float:in; output:float:out; sub A:valve, B:valve; assert A.input = input, B.input = A.output, output = B.output; edon

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A repairable component and its repairer node repairableSystem event startRepair, endRepair; sub C:component, R:repairer; sync startRepair = C.startRepair and R.startJob, endRepair = C.endRepair and R.endJob; edon

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Contents I.Introductory Examples II.Motivations III.Formal Model IV.Tools V.Examples of Use VI.Perspectives

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Motivations: Reliability Engineering Target systems: nuclear power plants, chemical plants, avionic systems, … Assess the risk and its consequences: what can go wrong ? what is the expectation that something goes wrong ? what are the consequences ?

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Motivations: Reliability Enginering Analyses: Determination of failure scenarii Assessment of failure probability Ranking of components with respect to their contribution to the risk

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Motivations: Reliability Engineering Classical formalisms (Fault Trees, Markov Graphs, Petri Nets) –Well defined semantics –Easy to handle –Textual and graphical –Good tradeoffs expressivity/efficiency … but Lack of structure (PN, MG) or Lack of expressivity (FT) Models are hard to design and to maintain

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The AltaRica Project AltaRica: a high level formal description language based on the notion of mode automata compilation into low level formalisms (efficiency) synergy with formal methods (e.g. model checking)

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System Analysis Dynamic Systems/Simulation: Differential Equations e.g. Modelica Code generation: Data-Flow models e.g. State Charts, Lustre Reliability Engineering: Event driven models, non-determinism e.g. Fault Trees, Petri nets, AltaRica

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Contents I.Introductory Examples II.Motivations III.Formal Model IV.Tools V.Examples of Use VI.Perspectives

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Mode Automata s=1 t=0 s=1 t=0 s=0 t=1 mode event : g(S,I) |- e -> S:=f(S,I) [Marininchi98, Rauzy02] A = S: state variables I: input variables O: output variables E: events : transitions : transfer function : initial state O = (S,I) IOS

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Algebra of Mode Automata ProductConnection Synchronization of events Operations on mode automata Synchronization G1 |- e1 -> S1:=f1 G2 |- e2 -> S2:=f2 G3 |- e3 -> S2:=f3 e = e1 and (e2 or e3) G1 and (G2 or G3) |- e -> S1 := if G1 then f1 else S1 S2 := if G2 then f2 else S2 S3 := if G3 then f3 else S3 fire the fireable local transitions

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Two Valves in Series node twoValves flow input:float:in; output:float:out; sub A:valve, B:valve; assert A.input = input, B.input = A.output, output = B.output; edon

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A repairable component and its repairer node repairableSystem event startRepair, endRepair; sub C:component, R:repairer; sync startRepair = C.startRepair and R.startJob, endRepair = C.endRepair and R.endJob; edon

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Mode Automata: External View View Time schedule traces mode

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Mode Automata … generalize fault trees, Markov graphs, Petri nets (P1>0) and (P2=0) |- T -> P1:=P1-1, P3:=P3+2; P3 P1 P2 T 2 remote interactions … generalize block-diagrams … make it possible to define hierarchies, packages, …

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Categories of Events Timed events: take a non null time Stochastic events (default) Probability distributions with parameters (exponential, Weibull,...) Dirac events Instaneous events: take no time and may have a priority Immediate events Conditional events

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A Spare Unit

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A Periodically Tested Component

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The Extern Clause The role of the extern clause is: to give some interpretation to the model, e.g. priorities to transitions, probability distributions to events, to give tools a specific information, to provide some mechanism to extend the language. In AltaRica Data-Flow, the syntax of the extern clause is normalized: node … extern law = exponential(0.001) ; parameter lambda = 0.001; … edon type of the information specified element value

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Commutation of the syntax and the semantics node System sub A:Component, B.Component, R:RepairMen … edon node S state A.s, B.s, R.s; … edond syntactic composition reachability graphs reachability graph synchronized product

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Contents I.Introductory Examples II.Motivations III.Formal Model IV.Tools V.Examples of Use VI.Perspectives

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Tools Workbenches Powerful graphical user interfaces for the design of models Graphical simulators OCAS (Dassault Aviation), SimFia (EADS-APSYS), Saraa (Airbus) Assessment tools Compilers to Fault Trees Compilers to Markov Graphs Stochastic simulators Generators of sequences Compilers to formal languages (Lustre, SMV) Model-Checkers AltaTools, Mec V (LaBRI), Combava (ARBoost Technologies)

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Combava: an AltaRica Data-Flow Toolbox node Cmp state s: … edon AltaRica Data-Flow Fault Trees alta-a2b Aralia Markov Graphs alta-mrk Mark-XPR Monte-Carlo simulation alta-sto Generation of sequences, model checking alta-seq Stepwise simulation alta-sim

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Contents I.Introductory Examples II.Motivations III.Tools IV.Formal Model V.Examples of Use VI.Perspectives

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Models Designed So Far 3 categories of models Functional models Mainly academic (Bordeaux) -> model checking Simple and huge dysfunctional models (~ bloc diagrams), e.g. Dassault F7X, … Compilation into fault trees Treatment chain validated by certification authorities Complex but (relatively) small models, e.g. Total, Production availability, High integrity protection systems Markov analyses, Monte-Carlo simulation

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Production Availability HPS-A HPS-B HPS-C DEH-A DEH-B CMP-A CMP-B MUP 45% 65% 52% 100% HPS8.91 10 DEH3.11 10 CMP3.50 10 2.54 10 3.95 10 5.14 10 -5 -3 MUP0.001 well tank

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Markov Analyses AltaRica model alta-a2g Multi Phase Markov models with rewards command fileMark-XPR Steady state probability Transient probability Mean sojourn time Expectation of any quantity defined on states

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Generation of (relevant) sequences AltaRica Automaton Sequence automaton alta-seqsequences automaton mySequences s1: #l not failed : s1; s1: #l failed : s2; init s1 : #l := 1; accept s2; end Model-checking: same automata with a Büchi acceptance criterion

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Contents I.Introductory Examples II.Motivations III.Tools IV.Formal Model V.Examples of Use VI.Perspectives

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Perspectives Find the “good” states/events formalism for reliability studies sound mathematical basis graphical representation generalization of currently used formalisms looped systems hierarchy algorithmic & complexity issues (tradeoff) connection with functional models hybrid systems higher level modeling

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Motivations Find the “good” states/events formalism for reliability studies sound mathematical basis graphical representation generalization of currently used formalisms looped systems hierarchy algorithmic & complexity issues (tradeoff) connection with functional models hybrid systems higher level modeling These issues are well addressed by current version(s) of AltaRica

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Motivations sound mathematical basis graphical representation generalization of currently used formalisms looped systems hierarchy algorithmic & complexity issues (tradeoff) connection with functional models hybrid systems higher level modeling Find the “good” states/events formalism for reliability studies

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Higher Level Modeling Need for Connection to external routines Structured types Parametric descriptions High level operations … and even object oriented modeling Extension of the language

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Motivations Find the “good” states/events formalism for reliability studies sound mathematical basis graphical representation generalization of currently used formalisms looped systems hierarchy algorithmic & complexity issues (tradeoff) connection with functional models hybrid systems higher level modeling

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Normalized Graphics Simple mode automata Petri nets Hierarchical descriptions Interaction diagrams

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Motivations Find the “good” states/events formalism for reliability studies sound mathematical basis graphical representation generalization of currently used formalisms looped systems hierarchy algorithmic & complexity issues (tradeoff) connection with functional models hybrid systems higher level modeling

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Electric Nets

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Motivations Find the “good” states/events formalism for reliability studies sound mathematical basis graphical representation generalization of currently used formalisms looped systems hierarchy algorithmic & complexity issues (tradeoff) connection with functional models hybrid systems higher level modeling

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Hybrid Systems Mixing discrete events and continuous variation, e.g. temperature controller

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Motivations sound mathematical basis graphical representation generalization of currently used formalisms looped systems hierarchy algorithmic & complexity issues (tradeoff) hybrid systems higher level modeling connection with functional models Find the “good” states/events formalism for reliability studies

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From functional to dysfunctional analyses Sensors Command automaton [e.g. state chart] Sensors may be subject to different failure modes How failures of sensors impact the command? How to derive the dysfunctional model from the functional model? Don’t expect a silver bullet !

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Architecture

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Industrial Perspectives Airbus (Rosas, A350) Dassault Systems (Catia System) ClearSy (Atelier B)

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Copyright © 2012, SAS Institute Inc. All rights reserved. ANALYTICS IN BIG DATA ERA ANALYTICS TECHNOLOGY AND ARCHITECTURE TO MANAGE VELOCITY AND VARIETY,

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