A brief history of model checking. Ken McMillan Cadence Berkeley Labs

Transcription

1 A brief history of model checking Ken McMillan Cadence Berkeley Labs

2 Outline Part I -- Introduction to model checking Automatic formal verification of finite-state systems Applications Commercial hardware design Avionics, chemical plant control, automotive, etc. Part II -- A brief history of model checking Influence of many abstract ideas from logic on the development of model checking

3 The Verification Problem Debugging chips by simulation... consumes greater than half of design time, is unreliable Escapes can cost up to $500M, is increasing in cost as chip densities scale up

4 Model Checking G(p F q) MC yes input: temporal logic spec finite-state model output q p p q no yes no + counterexample (look ma, no test vectors!) 2

5 Temporal logic (LTL) A logical notation that allows to: specify relations in time conveniently express finite control properties Temporal operators G p henceforth p F p eventually p X p p at the next time p W q p unless q 5

6 Types of temporal properties Safety (nothing bad happens) G ~(ack1 & ack2) mutual exclusion G (req (req W ack)) req must hold until ack Liveness G (req F ack) (something good happens) if req, eventually ack Fairness GF req GF ack if infinitely often req, infinitely often ack 6

7 Computation tree logic (CTL) Branching time model Path quantifiers A = for all future paths E = for some future path Example: AF p = inevitably p p p AFp p 7

8 CTL model checking algorithm Example: AF p = inevitably p AFp AFp AFp AFp Complexity linear in size of model (FSM) linear in size of specification formula p Note: LTL is exponential in formula size 9

9 Example: traffic light controller S E Guarantee no collisions Guarantee eventual service N 10

10 Safety (no collisions) Liveness Specifications AG (E_Go (N_Go S_Go)); AG ( N_Go N_Sense AF N_Go); AG ( S_Go S_Sense AF S_Go); AG ( E_Go E_Sense AF E_Go); Fairness constraints infinitely often (N_Go N_Sense); infinitely often (S_Go S_Sense); infinitely often (E_Go E_Sense); (assume each sensor off infinitely often) 14

11 Counterexample East and North lights on at same time... E_Go E_Req E_Sense NS_Lock N_Go N_Req N_Sense S_Go S_Req S_Sense N light goes on at same time S light goes off. S takes priority and resets NS_Lock 15

12 State explosion problem What if the state space is too large? too much parallelism data in model Approaches Abstraction/reduction Symbolic methods Exploiting symmetry Partial order methods 20

13 Binary Decision Diagrams Ordered decision tree for f = ab + cd 0 a 1 0 b 1 0 b 1 0 c 1 0 c 1 0 c 1 0 c 1 d d d d d d d d

14 OBDD reduction Reduced (OBDD) form: 0 a 1 0 b 1 c d 0 1 Key idea: combine equivalent subcases 22

15 Symbolic model checking Basic idea: Use BDD s to represent sets and relations Avoid explicitly representing states Transition relations a,b R(a,b,a,b ) a,b 24

16 Image computation EX p = states that can reach p in one step EXp p EX p = v. (R(v,v ) p(v )) Note: a. f = f a=0 + f a=1 25

17 Fixed point iteration EF p = states that can reach p S w... S 1 S 0 = p S i+1 = S i \/ EX S i...model checking without building state graph 26

18 Example: Gigamax cache protocol global bus UIC... cluster bus UIC UIC... M P P... M P P... First commercial application Method scales well with system size Finds very subtle escapes 33

19 Genealogy of model checking Many ideas from logic influence development of model checking... ω-automata S1S ATV LTL MC Logics of Programs CTL Model Checking Temporal/ Modal Logics Tarski µ-calc QBF BDD Symbolic Model Checking

20 Logics of programs Floyd/Hoare/Dijkstra Give precise definitions of programming languages Allows reasoning about programs (proofs/derivations) Pre-post conditions/ weakest precondition example: assignment axioms {true} x :=y {x = y} {P} x := y {P} (no x in P)

21 Concurrent programs Pnueli Concurrent vs. sequential programming sequential concurrent A B A B call ret need to characterize execution sequences proposes use of temporal logic

22 Temporal and modal logics Roots in philosophical logic Tense logic -- formalizing linguistic time If a, then b before c Modal logic -- reasoning about possibility If I had run I would have caught my plane New use in computer science: characterize the interactions of parallel processes G req F ack

23 Genealogy Floyd/Hoare late 60 s Logics of Programs Temporal/ Modal Logics Aristotle 300 sbce Kripke 59 Pnueli, late 70 s

24 CTL Model checking Reasoning about properties of nondeterministic programs branching time properties of programs fixed point characterizations (Tarski) every monotonic function has least/greatest fixed point key idea: apply to finite graphs, not infinite trees can directly calculate Tarski fixed points Applications finite state machines in hardware protocols proved incorrectness of some published designs

25 Genealogy, cont Logics of Programs Temporal/ Modal Logics Tarski 50 s CTL Model Checking Clarke/Emerson Early 80 s Some published circuits are proved incorrect

26 Decidable logics and automata Büchi S1S -- reason about sets of natural numbers Automata on infinite words characterize set of models of formula example: sets that contain the odd numbers 0,1 0 0,1 1 Deep connection between logics and automata

27 LTL model checking Vardi and Wolper Apply Büchi s technique to LTL Automaton construction yields optimal decision algorithm Kurshan Specify properties directly as automata example: infinitely often p (GFp) p p true

28 Genealogy Büchi, 60 ω-automata S1S Logics of Programs Temporal/ Modal Logics Tarski ATV Kurshan mid 80 s LTL MC Vardi/ Wolper CTL Model Checking

29 Symbolic Model Checking State explosion problem graph model guarantees worst-case complexity Characterize sets and relations by Boolean formulas compute Tarski fixed points directly on formulas EXp = v. (R p ) (QBF) Use BDD s to represent formulas efficient canonical form

30 Mu-calculus Park s Mu-Calculus Logic of relations with fixed point operator Can express transitive closure Nicely characterizes what SMC can compute SMC algorithm for Mu-calculus Use to express symbolic algorithms for CTL, LTL model checking AFp = µq. p AX Q Automaton containment, etc... Note: bad specification logic, but good for describing algorithms

31 Genealogy, cont. ω-automata S1S ATV LTL MC Logics of Programs CTL Model Checking Note first commercial application in 1990 Encore Gigamax cache protocols Temporal/ Modal Logics Symbolic Model Checking late 80 s QBF Tarski µ-calc BDD Park 60 s Bryant mid 80 s

32 Applications Hardware Design Encore Gigamax Intel instruction decoder SGI cache protocol chip Other areas Avionics (TCAS) Chemical plant control Nuclear storage facilities (!) Commercial tools Cadence, IBM, Synopsys

33 A convergence of research areas in logic Many areas of logic have shaped the discourse in model checking Logics of programs Temporal/Modal logics Tarski fixed point theory Decidable logics -- S1S/automata Park s mu-calculus Much of this work is quite abstract, but has strongly influenced practical work in model checking