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Classification Schemes to Aid in the Analysis of Real-Time Systems Paul Z. Kolano Trusted Systems Laboratories trustedsyslabs.com Richard.

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Presentation on theme: "Classification Schemes to Aid in the Analysis of Real-Time Systems Paul Z. Kolano Trusted Systems Laboratories trustedsyslabs.com Richard."— Presentation transcript:

1 Classification Schemes to Aid in the Analysis of Real-Time Systems Paul Z. Kolano Trusted Systems Laboratories paul.kolano@ trustedsyslabs.com Richard A. Kemmerer University of California, Santa Barbara kemm@cs.ucsb.edu

2 Outline of Presentation Introduction Brief ASTRAL overview Property classifications Process classifications Transition classifications Conclusion

3 Real-Time Systems Untimed + Concurrency + Asynchrony + Time + Nondeterminism + Reactivity = Difficult to analyze

4 Proof Assistance Is Needed Model checkers Automatically check state space for violations Theorem provers Keep reasoning sound, finish off proof details Need simplifications and manual abstractions Need human guidance and intuition Systematic analysis guidance How analysis can be performed based on previous experience How each approach can be used most effectively How results from different approaches can be combined

5 How Can Analysis Be Systematized? Identify distinct proof patterns Identify distinguishing features of system specifications that result in each pattern Divide and conquer Separate specifications with different patterns Separate individual proofs into simpler pieces

6 Testbed Systems Bakery algorithm Cruise control Elevator control system Olympic boxing scoring system Phone system Production cell Railroad crossing Stoplight control system Small/Large Simple/Complex Open/Closed Deterministic/ Nondeterministic Assumptions not needed/ Assumptions needed

7 Classification Schemes Distinct proof styles Statically recognizable ASTRAL classifications Property classifications Process classifications Transition classifications

8 Outline of Presentation Introduction Brief ASTRAL overview Property classifications Process classifications Transition classifications Conclusion

9 Railroad Crossing

10 ASTRAL Specification One or more process type specifications Each defines an abstract state machine A global specification Defines types, constants, etc. shared among process types Defines number of statically generated instances of each process type in the system Example: Railroad Crossing specification Process types Process instances Gate 1 Gate instance Sensor N_Tracks Sensor instances

11 Process Type Specification Types Variables Define state of process Initialization Defines initial values Transitions Define changes to variable values TYPE gate_position: (raised, raising, lowered, lowering) VARIABLE position: gate_position INITIAL position = raised TRANSITION lower ENTRY [TIME: lower_dur] ~ ( position = lowering | position = lowered ) & EXISTS s: sensor_id (s.train_in_R) EXIT position = lowering

12 Process Interactions

13 Specification of Properties INVARIANT Change(train_in_R, now) & ~train_in_R  FORALL t: time ( now - ((dist_R_to_I + dist_I_to_out) / max_speed - response_time)  t & t < now  past(train_in_R, t)) ENVIRONMENT Call(enter_R, now) & EXISTS t: time ( 0  t & t  now & Call 2 (enter_R, t))  Call(enter_R) - Call 2 (enter_R) > (dist_R_to_I + dist_I_to_out) / min_speed Requirements Invariants Schedules Assumptions Environment Imported variable

14 Outline of Presentation Introduction Brief ASTRAL overview Property classifications Process classifications Transition classifications Conclusion

15 Property Classifications Untimed properties Timed liveness properties Forward Backward Timed safety properties Forward Backward

16 Context and Requirement Times General form of a property context  requirement Context times are times referenced in the timed operator expressions of the context Requirement times are times referenced in the timed operator expressions of the requirement

17 Example of Context and Requirement Times FORALL t: time, s: sensor_id ( Change(s.train_in_R, now - dist_R_to_I / max_speed + response_time) & past(s.train_in_R, now - dist_R_to_I / max_speed + response_time)  EXISTS t: time ( now - dist_R_to_I / max_speed + response_time  t & t  now & past(position, t) = lowered)) Context times = {now - dist_R_to_I / max_speed + response_time} Requirement times = {t}

18 Untimed Properties Context times and requirement times can only be the current time With only local state variables FORALL d: direction ( Circle(d) = green  Arrow(opp(d)) = red) With timed operators/imported variables Change(number, now) & Number = 0  ~In_critical

19 Untimed Properties With Only Local State Variables State variables only change when transitions end These properties hold if the exit assertion of each transition preserves the property maintaining_speed  cruise_on TRANSITION maintain_speed ENTRY [TIME: input_dur] cruise_on & ~maintaining_speed EXIT cruise_throttle = throttle & desired_speed = speedometer.speed & maintaining_speed

20 Forward vs. Backward Forward EXISTS ct: context time FORALL rt: requirement time ct  rt Backward EXISTS rt: requirement time FORALL ct: context time rt  ct FORALL t: time, s: sensor_id ( Change(s.train_in_R, now - dist_R_to_I / max_speed + response_time) & past(s.train_in_R, now - dist_R_to_I / max_speed + response_time)  EXISTS t: time ( now - dist_R_to_I / max_speed + response_time  t & t  now & past(position, t) = lowered)) Change(train_in_R, now) & ~train_in_R  FORALL t: time ( now - ((dist_R_to_I + dist_I_to_out) / max_speed - response_time)  t & t < now  past(train_in_R, t))

21 Forward vs. Backward The execution tree of a process

22 Safety vs. Liveness Safety properties Must hold at all times in an interval Liveness properties Must hold at least once in an interval Can abstract away details of execution Must derive exact executions

23 Safety Properties Change(train_in_R, now) & ~train_in_R  FORALL t: time ( now - ((dist_R_to_I + dist_I_to_out) / max_speed - response_time)  t & t < now  past(train_in_R, t)) TRANSITION exit_I ENTRY [TIME: exit_dur] train_in_R & now - Start(enter_R)  (dist_R_to_I + dist_I_to_out) / min_speed - exit_dur EXIT ~train_in_R

24 Liveness Properties FORALL t: time, s: sensor_id ( Change(s.train_in_R, now - dist_R_to_I / max_speed + response_time) & past(s.train_in_R, now - dist_R_to_I / max_speed + response_time)  EXISTS t: time ( now - dist_R_to_I / max_speed + response_time  t & t  now & past(position, t) = lowered))

25 Property Classifications of Testbed Systems

26 Outline of Presentation Introduction Brief ASTRAL overview Property classifications Process classifications Transition classifications Conclusion

27 Process Classifications Multi-threaded process Iterative single-threaded process Simple single-threaded process

28 Multi-Threaded Process Multiple independent threads interleaved on a single process

29 Liveness Properties in a Multi-Threaded Process Must take scheduling policy into account Example: fixed priority scheduling

30 Iterative Single-Threaded Process Cyclic behavior with stored iteration count

31 Liveness Properties in an Iterative Single-Threaded Process Properties may need to be proved between arbitrary values of the iteration count

32 Simple Single-Threaded Process May have cyclic behavior, but iteration count not stored Properties usually need to be proved over only a single full cycle

33 Process Classifications of Testbed Systems Multi-threaded processes (2/25) Central_Control (phone system) Controller (stoplight control system) Iterative single-threaded processes (4/25) Elevator (elevator control system) Proc (bakery algorithm) Timer and Tabulate (Olympic boxing system) Simple single-threaded processes (19/25)

34 Outline of Presentation Introduction Brief ASTRAL overview Property classifications Process classifications Transition classifications Conclusion

35 Transition Classifications Transition enablement Local state (L) External environment (E) Imported state (O) Current time (T) Eight classifications based on these factors L, E, O, T, EO, ET, OT, EOT TRANSITION lower ENTRY [TIME: lower_dur] ~ ( position = lowering | position = lowered ) & EXISTS s: sensor_id (s.train_in_R) EXIT position = lowering

36 Determining Transition Delays e.g., L transitions Local state only changes when transitions end Must immediately follow previous transition e.g., T transitions Delayed from some local state/event e.g., now – End(trans1)  delay1 Other transition types Examine relevant clauses

37 Transition Classifications of Testbed Systems SystemLEOTEOETOTEOTTotal Bakery Algorithm 4 0 1 1 0 0 0 0 6 Cruise Control 2 9 2 1 0 0 0 0 14 Elevator 0 3 4 3 0 0 2 0 12 Olympic Boxing 0 0 2 2 0 0 1 1 6 Phone 0 2 16 0 7 0 5 0 30 Production Cell 14 0 11 20 0 0 10 1 56 Railroad Crossing 0 1 2 3 0 0 0 0 6 Stoplight 0 2 4 0 0 0 18 0 24 Total 20 17 42 30 7 0 36 2 154

38 Outline of Presentation Introduction Brief ASTRAL overview Property classifications Process classifications Transition classifications Conclusion

39 Conclusions Three classification schemes were developed from existing specifications Property classifications Process classifications Transition classifications Statically recognizable Each aids in the proof process

40 Future Work Examine more real-time systems Are there additional classification schemes that are useful? Examine other specification languages Are the existing classification schemes applicable to many specification languages?

41 The End For complete details, see dissertation... http://www.cs.ucsb.edu/~kolano


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