Quantitative Verification Arindam Chakrabarti * Krishnendu Chatterjee * Thomas A. Henzinger * Orna Kupferman ** Rupak Majumdar *** * UC Berkeley ** Hebrew.

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Presentation transcript:

Quantitative Verification Arindam Chakrabarti * Krishnendu Chatterjee * Thomas A. Henzinger * Orna Kupferman ** Rupak Majumdar *** * UC Berkeley ** Hebrew University *** UC Los Angeles

14 May 20044th OSQ Retreat, Santa Cruz, CA2 Outline What is the proposal ? What benefits do we get out of it ? Nailing down some details… Some interesting results. Summary

14 May 20044th OSQ Retreat, Santa Cruz, CA3 Formal Verification: Traditional approach Model: Labelled transition structure. Property: Classification of finite and/or infinite sequences of states into good and bad sets. Model-checking: Verification that all sequences of states generated by model are in good set.

14 May 20044th OSQ Retreat, Santa Cruz, CA4 Traditional approach: Models {a} {c} {b,c} {a,b} {a}

14 May 20044th OSQ Retreat, Santa Cruz, CA5 Traditional approach: Models {a} {c} {b,c} {a,b} {a} Each proposition maps each state to TRUE or FALSE.

14 May 20044th OSQ Retreat, Santa Cruz, CA6 Traditional approach: Models {a} {c} {b,c} {a,b} {a} Each proposition maps each state to TRUE or FALSE. Proposition: a

14 May 20044th OSQ Retreat, Santa Cruz, CA7 Traditional approach: Models {a} {c} {b,c} {a,b} {a} Each proposition maps each state to a boolean. Proposition: b

14 May 20044th OSQ Retreat, Santa Cruz, CA8 Extension 1: Quantitative Propositions, Models 1,3,4 0,2,5 34,23,1 8,4,9 3,2,4 Propositions: Each proposition maps each state to an integer.

14 May 20044th OSQ Retreat, Santa Cruz, CA9 Traditional approach: Properties A(a U c) {a} {c} {b,c} {a,b} {a}

14 May 20044th OSQ Retreat, Santa Cruz, CA10 Traditional approach: Properties A(a U c) {a} {c} {b,c} {a,b} {a} A property maps each path to TRUE or FALSE.

14 May 20044th OSQ Retreat, Santa Cruz, CA11 Extension 2: Quantitative Properties 1,3,4 0,2,5 34,23,1 8,4,9 3,2,4 max(sum(a)) while (sum(b) < 100)

14 May 20044th OSQ Retreat, Santa Cruz, CA12 Extension 2: Quantitative Properties max(sum(a)) while (sum(b) < 100) 1,3,4 0,2,5 34,23,1 8,4,9 3,2,4 112

14 May 20044th OSQ Retreat, Santa Cruz, CA13 Extension 2: Quantitative Properties max(sum(a)) while (sum(b) < 100) 1,3,4 0,2,5 34,23,1 8,4,9 3,2,4 115

14 May 20044th OSQ Retreat, Santa Cruz, CA14 Extension 2: Quantitative Properties max(sum(a)) while (sum(b) < 100) 1,3,4 0,2,5 34,23,1 8,4,9 3,2,4 188 A property maps each path to an integer.

14 May 20044th OSQ Retreat, Santa Cruz, CA15 Traditional approach: Model-checking problem {a} {c} {b,c} {a,b} {a} A(a U c) Check if any path in model violates the property (is mapped to FALSE).

14 May 20044th OSQ Retreat, Santa Cruz, CA16 Extension 3: Quantitative Model- checking problem 1,3,4 0,2,5 34,23,1 8,4,9 3,2,4 188 max(sum(a)) while (sum(b) < 100) Find the maximum (or minimum) value of the property on any path in the model.

14 May 20044th OSQ Retreat, Santa Cruz, CA17 Outline What is the proposal ? What benefits do we get out of it ? Nailing down some details… Some interesting results. Summary

14 May 20044th OSQ Retreat, Santa Cruz, CA18 Motor driver in a robot 0 stopslowfast 12 fast? slow?stop? slow? fast? stop? slow? fast?

14 May 20044th OSQ Retreat, Santa Cruz, CA19 Sensornet node with buffer of size 3 0 receivesend 1 send? receive? 2 send? receive? 3 send? receive?

14 May 20044th OSQ Retreat, Santa Cruz, CA20 Outline What is the proposal ? What benefits do we get out of it ? Nailing down some details… Some interesting results. Summary

14 May 20044th OSQ Retreat, Santa Cruz, CA21 Specifying properties using quantitative automata Property: maps each sequence of states to an integer. Quantitative automaton: States, input symbols, counters, guarded instructions on transitions, nondeterminism. Value of a run is given by limsup of values of a designated counter R0.

14 May 20044th OSQ Retreat, Santa Cruz, CA22 A Quantitative Automaton R1 := R1 + a R2 := R2 - b if R1 = R2 then R0 := c R1 := R1 + a R2 := R2 + b if R1 = R2 then R0 := c Maps each infinite sequence  = h a i,b i,c i i … to limsup c i such that  a i =  (-1) i ¢ b i

14 May 20044th OSQ Retreat, Santa Cruz, CA23 Outline What is the proposal ? What benefits do we get out of it ? Nailing down some details… Some interesting results. Summary

14 May 20044th OSQ Retreat, Santa Cruz, CA24 Some interesting results Infinite det- and nondet- hierarchies. Power of non-determinism. Undecidability of model-checking. Absence of finite-memory determinacy. Parametric-bounds, decidability, complexity. Parameter-finding cannot be automated. Quantitative  -calculus, correlations.

14 May 20044th OSQ Retreat, Santa Cruz, CA25 Some interesting results Infinite det- and nondet- hierarchies. Power of non-determinism. Undecidability of model-checking. Absence of finite-memory determinacy. Parametric-bounds, decidability, complexity. Parameter-finding cannot be automated. Quantitative  -calculus, correlations.

14 May 20044th OSQ Retreat, Santa Cruz, CA26 Examples Response time Fair maximum Resoure lifetime

14 May 20044th OSQ Retreat, Santa Cruz, CA27 Summary Quantitative extension to boolean verification framework. Motivation for doing so. Extended definitions for propositions, properties, and the model-checking problem. Some results (+ problems, solutions), examples.

14 May 20044th OSQ Retreat, Santa Cruz, CA28 Thanks for listening ! Questions, Comments, Suggestions ?