1. The Time-abstracting Bisimulation Equivalence  on TA states: Preserve discrete state changes. Abstract exact time delays. s1s2 s3  a s4  a 11 s1s2 s3  22 s4   1,  2  R

2. The Time-abstracting Quotient Graph - Nodes = symbolic states (equivalence classes). - Edges = symbolic transitions (discrete and time). Finite symbolic graph: Basic property: pre-stability Q1Q2 s1s2   a Q1Q2 s1s2 a Q1  pre (Q2) = Q1 a time The quotient induced by the greatest time-abstracting bisimulation defined on the TA.

3. Verification on the Quotient graph: Linear-time Every cycle in the quotient graph contains an infinite run and vice versa. Q1Q4Q3Q2 s1s2s3s4 s5... Timed Büchi Automata model checking DFS for cycles or SCCs in the quotient graph

4. Verification on the Quotient graph: Branching-time If s1  s2, then for any TCTL formula , s1 satisfies  iff s2 satisfies . TCTL model checking CTL model checking in the quotient graph 11 s1s2 s3  22 s4  s5 s6  Due to determinism of time.

5. Regions – Alternativ Definition x y 123 1 2

6. Problem with regions  Number of regions over n clocks: Explosion in number of clocks Explosion in maximal constant  Reachability is PSPACE complete for a single TA

7. Zones From infinite to finite State (n, x=3.2, y=2.5 ) x y x y Symbolic state (set ) (n, ) Zone: conjunction of x-y n

8. Symbolic Transitions n m x>3 y:=0 x y delays to conjuncts to projects to x y 1<=x<=4 1<=y<=3 x y 1<=x, 1<=y -2<=x-y<=3 x y 3<x, 1<=y -2<=x-y<=3 3<x, y=0 Thus (n,1 (m,3<x, y=0) a

9. A1 B1 CS1 V:=1V=1 A2 B2 CS2 V:=2V=2 Init V=1 2 ´´ V Criticial Section Fischer’s Protocol analysis using zones Y<10 X:=0 Y:=0 X>10 Y>10 X<10

10. Fischers cont. B1 CS1 V:=1V=1 A2 B2 CS2 V:=2V=2 Y<10 X:=0 Y:=0 X>10 Y>10 X<10 A1,A2,v=1A1,B2,v=2A1,CS2,v=2B1,CS2,v=1CS1,CS2,v=1 Untimed case A1

11. Fischers cont. B1 CS1 V:=1V=1 A2 B2 CS2 V:=2V=2 Y<10 X:=0 Y:=0 X>10 Y>10 X<10 A1,A2,v=1A1,B2,v=2A1,CS2,v=2B1,CS2,v=1CS1,CS2,v=1 Untimed case Taking time into account X Y A1

12. Fischers cont. B1 CS1 V:=1V=1 A2 B2 CS2 V:=2V=2 Y<10 X:=0 Y:=0 X>10 Y>10 X<10 A1,A2,v=1A1,B2,v=2A1,CS2,v=2B1,CS2,v=1CS1,CS2,v=1 Untimed case Taking time into account X Y A1 10 X Y

13. Fischers cont. B1 CS1 V:=1V=1 A2 B2 CS2 V:=2V=2 Y<10 X:=0 Y:=0 X>10 Y>10 X<10 A1,A2,v=1A1,B2,v=2A1,CS2,v=2B1,CS2,v=1CS1,CS2,v=1 Untimed case Taking time into account A1 10 X Y X Y

14. Fischers cont. B1 CS1 V:=1V=1 A2 B2 CS2 V:=2V=2 Y<10 X:=0 Y:=0 X>10 Y>10 X<10 A1,A2,v=1A1,B2,v=2A1,CS2,v=2B1,CS2,v=1CS1,CS2,v=1 Untimed case Taking time into account A1 10 X Y X Y X Y

15. Fischers cont. B1 CS1 V:=1V=1 A2 B2 CS2 V:=2V=2 Y<10 X:=0 Y:=0 X>10 Y>10 X<10 A1,A2,v=1A1,B2,v=2A1,CS2,v=2B1,CS2,v=1CS1,CS2,v=1 Untimed case Taking time into account A1 10 X Y X Y X Y

16. Forward Rechability Passed Waiting Final Init INITIAL Passed := Ø; Waiting := {(n0,Z0)} REPEAT - pick (n,Z) in Waiting - if for some Z’ Z (n,Z’) in Passed then STOP - else (explore) add { (m,U) : (n,Z) => (m,U) } to Waiting; Add (n,Z) to Passed UNTIL Waiting = Ø or Final is in Waiting Init -> Final ?

17. Forward Rechability Passed Waiting Final Init n,Z INITIAL Passed := Ø; Waiting := {(n0,Z0)} REPEAT - pick (n,Z) in Waiting - if for some Z’ Z (n,Z’) in Passed then STOP - else (explore) add { (m,U) : (n,Z) => (m,U) } to Waiting; Add (n,Z) to Passed UNTIL Waiting = Ø or Final is in Waiting n,Z’ Init -> Final ?

18. Forward Rechability Passed Waiting Final Init n,Z INITIAL Passed := Ø; Waiting := {(n0,Z0)} REPEAT - pick (n,Z) in Waiting - if for some Z’ Z (n,Z’) in Passed then STOP - else /explore/ add { (m,U) : (n,Z) => (m,U) } to Waiting; Add (n,Z) to Passed UNTIL Waiting = Ø or Final is in Waiting n,Z’ m,U Init -> Final ?

19. Forward Rechability Passed Waiting Final Init INITIAL Passed := Ø; Waiting := {(n0,Z0)} REPEAT - pick (n,Z) in Waiting - if for some Z’ Z (n,Z’) in Passed then STOP - else /explore/ add { (m,U) : (n,Z) => (m,U) } to Waiting; Add (n,Z) to Passed UNTIL Waiting = Ø or Final is in Waiting n,Z’ m,U n,Z Init -> Final ?

20. Canonical Dastructures for Zones Difference Bounded Matrices Bellman 1958, Dill 1989 x<=1 y-x<=2 z-y<=2 z<=9 x<=1 y-x<=2 z-y<=2 z<=9 x<=2 y-x<=3 y<=3 z-y<=3 z<=7 x<=2 y-x<=3 y<=3 z-y<=3 z<=7 D1 D2 Inclusion 0 x y z 12 2 9 0 x y z 23 3 7 3 ? ? Graph

21. Bellman 1958, Dill 1989 x<=1 y-x<=2 z-y<=2 z<=9 x<=1 y-x<=2 z-y<=2 z<=9 x<=2 y-x<=3 y<=3 z-y<=3 z<=7 x<=2 y-x<=3 y<=3 z-y<=3 z<=7 D1 D2 Inclusion 0 x y z 12 2 9 Shortest Path Closure Shortest Path Closure 0 x y z 12 2 5 0 x y z 23 3 7 0 x y z 23 3 6 3 3 3 Graph ? ? Canonical Dastructures for Zones Difference Bounded Matrices

22. Bellman 1958, Dill 1989 x<=1 y>=5 y-x<=3 x<=1 y>=5 y-x<=3 D Emptiness 0 y x 1 3 -5 Negative Cycle iff empty solution set Graph Canonical Dastructures for Zones Difference Bounded Matrices Compact

23. 1<= x <=4 1<= y <=3 1<= x <=4 1<= y <=3 D Future x y x y Future D 0 y x 4 3 Shortest Path Closure Remove upper bounds on clocks 1<=x, 1<=y -2<=x-y<=3 1<=x, 1<=y -2<=x-y<=3 y x 3 2 0 y x 3 2 0 4 3 Canonical Dastructures for Zones Difference Bounded Matrices

24. x y D 1<=x, 1<=y -2<=x-y<=3 1<=x, 1<=y -2<=x-y<=3 y x 3 2 0 Remove all bounds involving y and set y to 0 x y {y}D y=0, 1<=x Reset y x 0 0 0

25. Improved Datastructures Compact Datastructure for Zones x1-x2<=4 x2-x1<=10 x3-x1<=2 x2-x3<=2 x0-x1<=3 x3-x0<=5 x1-x2<=4 x2-x1<=10 x3-x1<=2 x2-x3<=2 x0-x1<=3 x3-x0<=5 x1x2 x3x0 -4 10 2 2 5 3 x1x2 x3x0 -4 4 2 2 5 33 -2 1 Shortest Path Closure O(n^3) RTSS 1997

26. Improved Datastructures Compact Datastructure for Zones x1-x2<=4 x2-x1<=10 x3-x1<=2 x2-x3<=2 x0-x1<=3 x3-x0<=5 x1-x2<=4 x2-x1<=10 x3-x1<=2 x2-x3<=2 x0-x1<=3 x3-x0<=5 x1x2 x3x0 -4 10 2 2 5 3 x1x2 x3x0 -4 4 2 2 5 3 x1x2 x3x0 -4 2 2 3 3 -2 1 Shortest Path Closure O(n^3) Shortest Path Reduction O(n^3) 3 Canonical wrt = Space worst O(n^2) practice O(n) RTSS 1997

27. v and w are both redundant Removal of one depends on presence of other. v and w are both redundant Removal of one depends on presence of other. Shortest Path Reduction 1st attempt Idea Problem w <=w An edge is REDUNDANT if there exists an alternative path of no greater weight THUS Remove all redundant edges! An edge is REDUNDANT if there exists an alternative path of no greater weight THUS Remove all redundant edges! w v Observation: If no zero- or negative cycles then SAFE to remove all redundancies. Observation: If no zero- or negative cycles then SAFE to remove all redundancies.

28. Over-approximation Convex Hull x y Convex Hull 135 1 3 5

29. 29 Hybrid Systems

30. Vending Machine 1 Timed Automata

31. Vending Machine 1 Timed Automata time x 10 20 30 cupdel-cof ord-cof Behaviour

32. Vending Machine 2 Hybrid Automata Maler, Manna, Pnueli’91 Clocks -> Continuous Variables

33. Vending Machine 2 Hybrid Automata t cupdel-coford-cof Behaviour 100 50 T,HT,H Maler, Manna, Pnueli’91 Clocks -> Continuous Variables

34. Vending Machine 3 Linear Hybrid Automata Alur, Courcouretis, Henzinger, Ho’93

35. Vending Machine 3 t cupdel-coford-cof Behaviour 100 50 T,HT,H Linear Hybrid Automata Alur, Courcouretis, Henzinger, Ho’93 HYTECH

36. Symbolic Analysis Polyhedra H T

37. H T

38. H T

39. H T The exploration may lead to generation of infinitely many polyhedra => No guarantee of termination Manipulation of polyhedra inefficient!  

40. TA’s versus LHA’s zTOOLS yUPPAAL, KRONOS,CMC,... zDecidable zEfficient Datastructure yDBM’s, NDD’s, CDD’s,.. zExpressiveness zTOOLS yHYTECH, POLLUX,.. zUndecidability zDatastructures yPlyhedra zExpressiveness    STOPWATCH AUTOMATA x’==0 or x’==1

41. STOPWATCH AUTOMATA zExtension of UPPAAL to SWA yReuse of efficient datastructures yOverapproximation zEvery LHA may be translated into a SWA zAPPLICATIONS yScheduler yGasburner yWater Level Control Cassez, Larsen, CONCUR’00