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From MTL to Deterministic Timed Automata Dejan Nickovic Nir Piterman IST Austria Imperial College London (University of Leicester) Introduction Property-based analysis and synthesis of digital systems Specification Temporal Logic LTL


  1. From MTL to Deterministic Timed Automata Dejan Nickovic Nir Piterman IST Austria Imperial College London (University of Leicester)

  2. Introduction Property-based analysis and synthesis of digital systems Specification Temporal Logic LTL Model Controller Monitoring Checking Synthesis From MTL to Deterministic Timed Automata

  3. Introduction Property-based analysis and synthesis of digital systems Specification Temporal Logic LTL Non−Deterministic Automaton Model Controller Monitoring Checking Synthesis From MTL to Deterministic Timed Automata

  4. Introduction Property-based analysis and synthesis of digital systems Specification Temporal Logic LTL Non−Deterministic Automaton On−the−fly Determinization Model Controller Monitoring Checking Synthesis From MTL to Deterministic Timed Automata

  5. Introduction Property-based analysis and synthesis of digital systems Specification Temporal Logic LTL Subset Construction Deterministic Non−Deterministic Finite Automaton Automaton On−the−fly Determinization Model Controller Monitoring Checking Synthesis From MTL to Deterministic Timed Automata

  6. Introduction Property-based analysis and synthesis of digital systems Specification Temporal Logic LTL Subset Safra’s Construction Construction Deterministic Non−Deterministic Deterministic Finite Automaton Automaton ω -Automaton On−the−fly Determinization Model Controller Monitoring Checking Synthesis From MTL to Deterministic Timed Automata

  7. Introduction Property-based analysis and synthesis of real-time systems Real−time Specification MITL Model Controller Monitoring Checking Synthesis From MTL to Deterministic Timed Automata

  8. Introduction Property-based analysis and synthesis of real-time systems Real−time Specification MITL Non−Deterministic Timed Automaton On−the−fly Determinization Model Controller Monitoring Checking Synthesis From MTL to Deterministic Timed Automata

  9. Introduction Property-based analysis and synthesis of real-time systems Real−time Specification MITL ?? ?? Deterministic Timed Non−Deterministic Deterministic Finite Automaton Timed Automaton Timed ω -Automaton On−the−fly Determinization Model Controller Monitoring Checking Synthesis From MTL to Deterministic Timed Automata

  10. Introduction Property-based analysis and synthesis of real-time systems Real−time Specification MITL ?? ?? Deterministic Timed Non−Deterministic Deterministic Finite Automaton Timed Automaton Timed ω -Automaton On−the−fly Determinization Model Controller Monitoring Checking Synthesis Timed automata are non-determinizable in general!! From MTL to Deterministic Timed Automata

  11. Metric Temporal Logic - MTL • AP - set of atomic propositions Signal over AP - w : R ≥ 0 → 2 AP • • w p - projection of w to proposition p ∈ AP Syntax: ϕ :== p | ¬ ϕ 1 | ϕ 1 ∨ ϕ 2 | ϕ 1 U I ϕ 2 where p belongs to the set AP of atomic propositions and I is an interval of the form [ b, b ] , [ a, b ] , [ a, b ) , ( a, b ] , ( a, b ) , [ a, ∞ ) , ( a, ∞ ) where 0 ≤ a < b . • Derived operators: ✸ I ϕ = T U I ϕ and ✷ I ϕ = ¬ ✸ I ¬ ϕ • MITL - restricion of MTL to non-singular modalities From MTL to Deterministic Timed Automata

  12. MTL - Metric Temporal Logic Semantics: ( w, t ) | ↔ = p w p [ t ] = 1 ( w, t ) | = ¬ ϕ ↔ ( w, t ) �| = ϕ ( w, t ) | = ϕ 1 ∨ ϕ 2 ↔ ( w, t ) | = ϕ 1 or ( w, t ) | = ϕ 2 ∃ t ′ ∈ t + I st ( w, t ) | ( w, t ) | = ϕ 1 U I ϕ 2 ↔ = ϕ 2 ∧ ∀ t ′′ ∈ ( t, t ′ ) ( w, t ′′ ) | = ϕ 1 Formula ϕ satisfied by w if ( w, 0) | = ϕ From MTL to Deterministic Timed Automata

  13. MTL and Non-Determinism 1. Unbounded variability p → ✸ ( a,b ) q memorize changes p q t t + a t + b 2. Acausality p U ( a,b ) q p q t ′ t t + a t + b From MTL to Deterministic Timed Automata

  14. Signals with Bounded Variability • Signal w is of bounded variability k if for every proposition p , it changes its value at most k times in every interval of length 1 k − 1 1 2 3 k t t + 1 • Reasonable assumption for many applications • Almost all systems have a bound on the frequency they operate • From now on, we assume that every input signal is of bounded variability From MTL to Deterministic Timed Automata

  15. From MTL to Deterministic Timed Automata - Overview • Translation from MTL to deterministic TA assuming bounded variability of input signals MTL Specification From MTL to Deterministic Timed Automata

  16. From MTL to Deterministic Timed Automata - Overview • Translation from MTL to deterministic TA assuming bounded variability of input signals MTL Specification Translation Non−Deterministic TA Proposition Prediction Monitor Generator Non−Deterministic Deterministic TA Dependent TA From MTL to Deterministic Timed Automata

  17. From MTL to Deterministic Timed Automata - Overview • Translation from MTL to deterministic TA assuming bounded variability of input signals MTL Specification Translation Non−Deterministic TA Proposition Prediction memorizes events passive use of clocks Monitor Generator deterministic by Non−Deterministic discrete predictions Deterministic TA construction Dependent TA From MTL to Deterministic Timed Automata

  18. From MTL to Deterministic Timed Automata - Overview • Translation from MTL to deterministic TA assuming bounded variability of input signals MTL Specification Translation Non−Deterministic TA Proposition Prediction memorizes events passive use of clocks Monitor Generator deterministic by Non−Deterministic discrete predictions Deterministic TA construction Dependent TA Determinization Deterministic TA Proposition Prediction Monitor Generator Deterministic Deterministic TA Dependent TA From MTL to Deterministic Timed Automata

  19. Evaluating MTL Formulas - Overview • Computation of the truth value of a formula ϕ at time t with a delay at time t + f where f is a bound p U ( a,b ) q memorize evaluate p p p ( w, t ) �| = p U ( a,b ) q q t t + a t + b From MTL to Deterministic Timed Automata

  20. Evaluating MTL Formulas - Overview • Computation of the truth value of a formula ϕ at time t with a delay at time t + f where f is a bound p U ( a,b ) q memorize evaluate p ( w, t ) �| = p U ( a,b ) q q q t t + a t + b From MTL to Deterministic Timed Automata

  21. Evaluating MTL Formulas - Overview • Computation of the truth value of a formula ϕ at time t with a delay at time t + f where f is a bound p U ( a,b ) q memorize evaluate p ( w, t ) | = p U ( a,b ) q q q t t + a t + b From MTL to Deterministic Timed Automata

  22. Evaluating MTL Formulas - Overview • Computation of the truth value of a formula ϕ at time t with a delay at time t + f where f is a bound p U ( a,b ) q memorize evaluate p ( w, t ) | = p U ( a,b ) q q q t t + a t + b p U ( a, ∞ ) q memorize evaluate p p p ( w, t ) �| = p U ( a, ∞ ) q q t t + a From MTL to Deterministic Timed Automata

  23. Evaluating MTL Formulas - Overview • Computation of the truth value of a formula ϕ at time t with a delay at time t + f where f is a bound p U ( a,b ) q memorize evaluate p ( w, t ) | = p U ( a,b ) q q q t t + a t + b p U ( a, ∞ ) q memorize evaluate p ??? q q t t + a From MTL to Deterministic Timed Automata

  24. Evaluating MTL Formulas - Overview • Computation of the truth value of a formula ϕ at time t with a delay at time t + f where f is a bound p U ( a,b ) q memorize evaluate p ( w, t ) | = p U ( a,b ) q q q t t + a t + b p U ( a, ∞ ) q predict p U q memorize evaluate p q q t t + a From MTL to Deterministic Timed Automata

  25. Evaluating MTL Formulas - future Function • Computation of the truth value of a formula ϕ at time t by looking in the interval [ t, t + future ( ϕ )) future ( p ) = p future ( ¬ ϕ 1 ) = future ( ϕ 1 ) future ( ϕ 1 ∨ ϕ 2 ) = max ( future ( ϕ 1 ) , future ( ϕ 2 )) future ( ϕ 1 U ( a,b ) ϕ 2 ) = b + max ( future ( ϕ 1 ) , future ( ϕ 2 )) future ( ϕ 1 U ( a, ∞ ) ϕ 2 ) = 2 + a + max ( future ( ϕ 1 ) , future ( ϕ 2 )) • Why 2 additional lookaheads for future ( ϕ 1 U ( a, ∞ ) ϕ 2 ) ? [ t, t + a ) never sufficient to determine whether p U ( a, ∞ ) holds at t p q q t t + a From MTL to Deterministic Timed Automata

  26. Evaluating MTL Formulas - future Function • Computation of the truth value of a formula ϕ at time t by looking in the interval [ t, t + future ( ϕ )) future ( p ) = p future ( ¬ ϕ 1 ) = future ( ϕ 1 ) future ( ϕ 1 ∨ ϕ 2 ) = max ( future ( ϕ 1 ) , future ( ϕ 2 )) future ( ϕ 1 U ( a,b ) ϕ 2 ) = b + max ( future ( ϕ 1 ) , future ( ϕ 2 )) future ( ϕ 1 U ( a, ∞ ) ϕ 2 ) = 2 + a + max ( future ( ϕ 1 ) , future ( ϕ 2 )) • Why 2 additional lookaheads for future ( ϕ 1 U ( a, ∞ ) ϕ 2 ) ? [ t, t + a ) never sufficient to determine whether p U ( a, ∞ ) holds at t p q q t t + a From MTL to Deterministic Timed Automata

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