A … Framework for Verifying Concurrent C Programs Sagar Chaki Thesis Defense Talk.

A … Framework for Verifying Concurrent C Programs

Sagar Chaki

Thesis Defense Talk

2

Motivation

Requirements SpecificationSpecification

Validation

CodeCode

Validation

Conformance

CheckConformance

Check

Distributed Programswith Message-Passing

Communicating

Distributed Programswith Message-Passing

Communicating

3

Related Work

Model Checking Symbolic model checking (SMV,MURPHI,MOCHA) Partial order reduction (SPIN,COSPAN)

Compositional reasoning Assume-guarantee

Abstraction Abstract interpretation, existential abstraction

Message-passing systems CCS, -Calculus Simulation, bisimulation, …

4

Iterative Refinement

Yes

System OK

AbstractionAbstractionModel

CounterexampleValid?


System

AbstractionGuidance No

Counterexample

AbstractionRefinementAbstractionRefinement

ImprovedAbstractionGuidance

No

SpuriousCounterexample

Yes

VerificationVerification

Spec

5

Related Work

Iterative Refinement (Kurshan)Hardware

Yuan Lu ) Ph.D. thesis

SLAM (device drivers)BLAST (lazy abstraction, thread modular safety)

Concurrent SoftwareSPIN, Behave!, ZING

Own modeling language No iterative refinement

Safety properties

6

Contributions

Compositional Iterative Refinement (IR)concurrent message-passing programssimulation conformance

Combining predicate abstraction with existential abstraction

Predicate MinimizationCompositional IR for Liveness propertiesCompositional IR for Deadlock detection

7

Basic Concepts

Var : set of variablesExpr : expressions over VarStore : set of stores

Var ! AddressesAddresses ! Values

AP : set of atomic propositionsConc : AP $ Expr

8

Extended FSM

Transitions labeled with guarded commandsGuards are expressionsCommand are actions or assignments

x == 0 ? x++

x != 0 ?

true ?

9

Control Flow Graph

x=x+y

lib()

Component

1

2

x == 0 ? x++

x != 0 ?

true ?

EFSM(lib)

10

Control Flow Graphx=x+y

1

2

x == 0 ? x++

x != 0 ?

true ?

Control Flow Graph

11

Labeled Kripke StructureM = ( Q , I , , T , AP, L)

Q ´ non-empty set of statesI 2 Q ´ initial state ´ set of actions ´ alphabetT µ Q £ £ Q ´ transition relationAP µ AP ´ set of atomic propositionsL : Q ! 2AP ´ propositional labeling

p

q

r

= { ,,,,,}

p,q

p,rAP = { p,q,r,s }

12

Concurrent C Program

Set of components P = hC1 ,…, Cn i

Each Ci is a single C procedurePossibly calling library routinesLibrary routines are specified via EFSMs

Semantics of C is an LKSDepends on the library specificationss

14

Concrete Semantics of C

Context = (Init, EFSM, , , AP)SCFG ´ States of CFGICFG ´ Initial state of CFG

MC = ( Q , I , [ , T , AP, L)

Q = SCFG £ Store

I = { (s,) j s = ICFG and ² Init }

L(s,) = { p j ² Conc(p) }

17

Concrete Semantics

x=x+y

1

2

x == 0 ? x++

x != 0 ?

true ?

x=1,y=-3

x=-2,y=-3

x=-2,y=-3

p ´ x = 0

x=5,y=-5

x=1,y=-5

x=0,y=-5

x=1,y=-5

p

18

Predicate Abstraction

Pred µ ExprSet of expressions (predicates) associated with each

state of the CFG

Pred ¶ { Conc(p) j p 2 AP }Predicate corresponding to every atomic proposition

must be associated with each state of the CFG

In practice each CFG state has a different set of associated predicates

19

Valuation : Two Views

Valuation ´ minterm PredSet of all valuations ´ 2Pred

Pred = { x = 0, y = 0 }

x 0 Æ y 0 , {} x = 0 Æ y 0 , {x = 0} x 0 Æ y = 0 , {y = 0} x = 0 Æ y = 0 , {x = 0, y=0}

Expression Subset of Pred

21

Abstract Semantics of C

Context = (Init, EFSM, , , AP, Pred)SCFG ´ States of CFGICFG ´ Initial state of CFG

M[C] = ( Q , I , [ , T , AP, L)

Q = SCFG £ 2Pred

I = { (s,v) j s = ICFG and v ° Init }

L(s,v) = { p j Conc(p) 2 v }

24

Abstract Semantics

x=x+y

1

2

x == 0 ? x++

x != 0 ?

true ?

x0,y=0

x0,y=0

x0,y=0

p ´ x = 0

x=0,y=0

x0,y=0

x=0,y=0

X0,y=0

p

p

25

Simulation

M1 = ( Q1 , I1 , , T1 , AP, L1)M2 = ( Q2 , I2 , , T2 , AP, L2)

R µ Q1 £ Q2 is a simulation relation ifs1 R s2 )

L1(s1) = L2(s2)8 (s1, , s’1) 2 T1 ¦ 9 s’2 ¦ (s2, , s’2) 2 T2 Æ s’

1 R s’

2

M1 4 M

2 ´

9 R µ Q1 £ Q2 ¦ 8 s1 2 I1 ¦ 9 s2 2 I2 ¦ s1 R s2

27

MC 4 M[C]

(e) ´ evaluation of e under ² e ´ (e) 0

Define relation R µ QC £ Q[C]

(s,m) R (s,v) , m ² vR is a simulation relation 8 s 2 IC ¦ 9 [s] 2 I[C] ¦ s R [s]

28

Parallel Composition

M1 = ( Q1 , I1 , , T1 , AP2, L1)

M2 = ( Q2 , I2 , 2, T2 , AP1, L2)

M1||M2 = ( Q1 £ Q2 , I1 £ I2 , 1 [ 2, T , AP1 [ AP2 , L)

L(s1,s2) = L1(s1) [ L2(s2)

((s1, s2), , (s’1, s’2)) 2 T iff for i 2 {1,2} i Æ (si, , s’i) 2 Ti

i Æ si = s’i

29

Program Semantics

P = h C , C’ i

MP = MC || MC’

M[P] = M[C] || M[C’]

Abstraction is done modularly

444

30

Program Semantics

P = C || C’

[P] = [C] || [C’]

444

31

Verification

Specification is an LKS Spec Given P and Spec, check if P 4 Spec

1. Construct [P]2. Check if [P] 4 Spec

1. P 4 [P] Æ [P] 4 Spec ) P 4 Spec2. Otherwise …

32

Counterexample

: ([P] 4 Spec) )9 CE ¦ CE 4 [P] Æ : (CE 4 Spec)CE has a tree structure

Look at Chapter 5 for the procedure to check [P] 4 Spec and construct CE if necessary

33

Counterexample Validation

Check if CE 4 P

: (CE 4 Spec) Æ CE 4 P

) : (P 4 Spec)

Real

P = C || C’

34

Problems

CE 4 C || C’

Infinite StatesStatespace Explosion

Symbolic Representation Compositional Reasoning

35

LKS Projection

p

q

r

= { ,,,,,}

p,q

p,rAP = { p,q,r,s }

M

’ = { ,,} AP’ = { p,r,t } [ ’

36

LKS Projection

p r

Å ’ [ {}

p

rAP Å AP’

M ¼ { ’,AP’ }

’ = { ,,} AP’ = { p,r,t } [ ’

M’ = ( …, ’ , AP’ , …) ) M ¼ M’ ´ M ¼ { ’, AP’ }

37

Weak Simulation

M1 = ( Q1 , I1 , [ { }, T1 , AP, L1)M2 = ( Q2 , I2 , , T2 , AP, L2)

R µ Q1 £ Q2 is a weak simulation relation ifs1 R s2 )

L1(s1) = L2(s2)8 (s1, , s’1) 2 T1 ¦ 9 s’2 ¦ (s2, , s’2) 2 T2 Æ s’

1 R s’

28 (s1, , s’1) 2 T1 ¦ s’

1 R s

2

M1 - M

2 ´

9 R µ Q1 £ Q2 ¦ 8 s1 2 I1 ¦ 9 s2 2 I2 ¦ s1 R s2

38

Compositional Validation

CE 4 C || C’

,CE ¼ C - C Æ CE ¼ C’ - C’

39

Compositional Validation

CE 4 C || C’

,CE ¼ - C Æ CE ¼ - C’

Infinite States

Symbolic Representation

40

Symbolic Representation

MC = ( Q , I , , T , AP, L)

There exists a class R µ 2Q

Each r 2 R has a finite representation Q 2 RR closed under intersection and pre-imageGiven r 2 R can check if r = ;

41

CE ¼ - C

CE ¼ C

Q

Q Q)

Q

Q

Q

Q)

Q

42

CE ¼ - C

Q

Q Q)

Q Q

Q Å Q)

Q

Q Å Q))Q)Q)

CE ¼ C

43

CE ¼ - C

Q

Q Q)

Q Q

Q Å Q)

Q

Q) Å (Q) Å Q Å Q))

= ; ?

CE ¼ C

44

Abstraction Refinement

Check if CE 4 P

CE 4 P ) Real

Update the set Pred such that for the new [P] we have :(CE 4 [P])Chapter 6

Minimize number of predicates to be addedChapter 7

45

Case Study: SSL Handshake

Verify that OpenSSL correctly implements the SSL handshakeServer and client codeEach about 2500 LOC400 LOC after abstracting

away library routine calls

Analyzed client and server separately and together

46

SSL ResultsNAME

LINES OF CODE

NO. OF ITER

AVG. MODEL SIZE

AVG. MODEL TIME (SEC)

SPEC SIZE (ST/TR)

AVG. HORN VAR NUM

AVG. HORN CLAUSE NUM

VERIF TIME

TOTAL TIME (SEC)

MEMORY (MB)

SERVER

2483

64

8984

40.2

32 / 67

287472

352150

1636

8639

743

CLIENT

2484

71

6747

28.7

29 / 60

195635

238296

1217

7437

185

SRVR-CLNT

4967

175

77474

3.3

6 / 5

387375

1386980

13786

21134

1105

47

SSL ResultsNAME

LINES OF CODE

NO. OF ITER

AVG. MODEL SIZE

AVG. MODEL TIME (SEC)

SPEC SIZE (ST/TR)

AVG. HORN VAR NUM

AVG. HORN CLAUSE NUM

VERIF TIME

TOTAL TIME (SEC)

MEMORY (MB)

SERVER

2483

64

8984

40.2

32 / 67

287472

352150

1636

8639

743

CLIENT

2484

71

6747

28.7

29 / 60

195635

238296

1217

7437

185

SRVR-CLNT

4967

175

77474

3.3

6 / 5

387375

1386980

13786

21134

1105

48

Thoughts

Predicate abstraction alone inadequate for concurrent systemsStates from different control locations are

always kept distinctThey might be merged

How do we combine other kinds of abstractions with predicate abstraction

49

Iterative Refinement

System OK




System

No



No

VerificationVerification

Spec

50

IR ´ Model Checking

System OKAbstraction

Model


System

No

AbstractionRefinement


No

Verification

Spec

51

Verification ´ IR

System OK




System

No



No

IterativeRefinement

IterativeRefinement

Spec

52

Existential Abstraction

M = ( Q , I , , T , AP, L)

Equivalence R µ Q £ QCompatible with propositional labelings R s’ ) L(s) = L(s’)[s] ´ equivalence class of s

Induces a quotient LKS MR

54

Example

1

2 3

4 6

a b

b e

M

TheoremM ¹ MR

Proof(s R [s]) is a

simulation relation

5 7

ac

d

MR

eb

[2,3]

[4,5] [6,7]

[1]

a b

c a

dq

p

55

Verification

Given [P] = [C] || [C’] and Spec

1. Use equivalence relations R and R’ Initially R and R’ are maximal

2. Construct [P]RR’ = [C]R || [C’]R’

[P] 4 [P]RR’

3. Check if [P]RR’ 4 Spec1. [P] 4 [P]RR’ Æ [P]RR’ 4 Spec ) [P] 4 Spec2. Otherwise …

58

Splitting R

CE ¼ [C]R

[C]R -

[C] 4

59

Splitting R

Repeated Splitting )

CR converges tobisimulation quotient

of C

CE ¼ [C]R [C]R

-

60

Two Level IRC1 Spec4

[C1] 4 Spec

Predicate

Abstraction

[C2] [C3] [C4]

C2 C3 C4

Existential

Abstraction

4 SpecA1 A2 A3 A4

61

Two Level IRC1 Spec4

[C1] Spec

Predicate

Abstraction

Existential

Abstraction

[C2] [C3] [C4]

C2 C3 C4

SpecA1 A2 A3 A4

A1

Existential

Refinement

4

4

62

Two Level IRC1 Spec

[C1] Spec

Predicate

Abstraction

Existential

Abstraction

[C2] [C3] [C4]

C2 C3 C4

SpecA1 A2 A4

A1

Existential

Refinement

A3

A3

4

4

4

63

Two Level IRC1 Spec

[C1] Spec

Predicate

Abstraction

Existential

Abstraction

[C2] [C3] [C4]

C2 C3 C4

SpecA1 A2 A4

A1

Existential

Refinement

A3

A3

A1

4

4

4

64

Two Level IRC1 Spec

[C1] Spec

Predicate

Abstraction

Existential

Abstraction

[C2] [C3] [C4]

C2 C3 C4

SpecA1 A4

A1

Existential

Refinement

A3

A3

A1

4

4

4

A2

A2

65

Two Level IRC1 Spec

[C1] Spec

Predicate

Abstraction

Existential

Abstraction

[C2] [C3] [C4]

C2 C3 C4

SpecA1 A2 A4Existential

Refinement

A3

A3

[C2]

A1

A1

4

4

4

No bugs or real

66

Test

Name

One Level Two Level Gain

S1 M1 T1 S2 M2 T2 T1/T2 M1/M2

SSL-1

SSL-2

SSL-3

SSL-4

SSL-5

SSL-6

SSL-7

SSL-8

SSL-9

SSL-10

SSL-11

SSL-12

SSL-13

Results

67

Test

Name


S1 M1 T1 S2 M2 T2 T1/T2 M1/M2

SSL-1 157266 1023 886 15840 122 1081 0.82 8.39

SSL-2 201940 1070 1645 6072 64 500 3.29 16.72

SSL-3 203728 1003 1069 20172 130 1805 0.59 7.72

SSL-4 201940 640 1184 7808 69 482 2.46 9.28

SSL-5 184060 780 1355 6240 64 407 3.33 12.19

SSL-6 158898 426 695 2310 56 219 3.17 7.61

SSL-7 103566 250 447 7743 74 472 0.95 3.38

SSL-8 161580 945 1071 4617 64 387 2.77 14.77

SSL-9 214989 1475 1515 13800 106 716 2.12 13.92

SSL-10 118353 663 628 3024 60 402 1.56 11.05

SSL-11 204708 1131 794 8820 79 446 1.78 14.32

SSL-12 121170 373 303 2079 56 204 1.49 6.66

SSL-13 152796 361 579 3780 60 349 1.66 6.02

Results

68

Test

Name


S1 M1 T1 S2 M2 T2 T1/T2 M1/M2

SSL-1 157266 1023 886 15840 122 1081 0.82 8.39

SSL-2 201940 1070 1645 6072 64 500 3.29 16.72

SSL-3 203728 1003 1069 20172 130 1805 0.59 7.72

SSL-4 201940 640 1184 7808 69 482 2.46 9.28

SSL-5 184060 780 1355 6240 64 407 3.33 12.19

SSL-6 158898 426 695 2310 56 219 3.17 7.61

SSL-7 103566 250 447 7743 74 472 0.95 3.38

SSL-8 161580 945 1071 4617 64 387 2.77 14.77

SSL-9 214989 1475 1515 13800 106 716 2.12 13.92

SSL-10 118353 663 628 3024 60 402 1.56 11.05

SSL-11 204708 1131 794 8820 79 446 1.78 14.32

SSL-12 121170 373 303 2079 56 204 1.49 6.66

SSL-13 152796 361 579 3780 60 349 1.66 6.02

Results

69

Summary

Compositional IR for concurrent programs Message-passing communicationSimulation conformance

Combine predicate abstraction and existential abstraction in a two-level compositional IR algorithmExperimental validation

70

Thank you!

Edmund ClarkeExemplary advisor

Alex Groce, Somesh Jha, Helmut VeithThe original magicians

Tom Ball, Sriram Rajamani, Jakob RehofSuperb summer job mentors

Orna Grumberg, Joel Ouaknine, Natalia Sharygina, Ofer Strichman, Karen YoravAwesome guides

Randal Bryant, David GarlanExcellent thesis committee members

71

Questions?Questions?

A … Framework for Verifying Concurrent C Programs Sagar Chaki Thesis Defense Talk.

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