presented by: hagit cohen april 2006

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Presented by:Hagit Cohen

April 2006

Tree-Like Counterexamples in Model Checking

Edmund Clarke Somesh Jha

Yuan Lu Helmut Veith

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Outline

Introduction and linear counterexamples. Tree-like Kripke structures. Tree-like counterexamples for ACTL. Tree-like counterexamples for AΩ. Applications.

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Counterexamples - motivation

A tool for detecting bugs.

Major importance in verification of large systems.

Automatic generation.

Abstraction refinement methodology for model checking.

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What are counterexamples?

Given a property φ claimed to hold for each element of a given set S:

φ can be disproved by choosing a single element s ∈ S such that φ does not hold for s.

φS:

φS:

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What are counterexamples? (cont.)

Existential properties can not be disproved by counterexamples.

For temporal logics counterexamples are expected for universal fragments.

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Universal logics

A logic L is universal if the simulation theorem holds for L:

Let ψ be an ACTL formula. If K ≽ C and K ⊨ ψ then C ⊨ ψ.

ACTL(*)

AΩ

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Linear counterexamples

Simple non-branching structures. Finite or infinite paths. Limitation of most model checkers.

Example: AF¬x

x

x

x

x

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Linear counterexamples (cont.)

Insufficient for ACTL – only properties in ACTL ∩ LTL have linear counterexamples.

AFAXp – a counterexample has to show that there exists an infinite path π such that from every state of π, a state with property ¬p is reachable in one step. ⇒ Branching by definition.

Recognizing ACTL formulas with linear counterexamples is PSPACE-hard.

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From Linear to Tree-Like

Desired attributes of a counterexample class:

Completeness

Effectiveness

Intelligibility

Viability

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Counterexamples for ACTL

K ⊭ φ, C - a counterexample. What do we expect of C ?

C violates φ:C ⊭ φ ,or:C ⊨ ¬φ.Where ¬φ is an ECTL formula.C is a witness of ¬φ.

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Counterexamples for ACTL (cont.)

What do we expect of C ?

Violation on C “explains” the Violation on K:By the relation K ≽ C.

C is viable:Demand that C is tree-like.

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Tree-like graphs and Kripke structures

A graph is tree-like, if:(i) All SCCs are cycles.(ii) The component graph is a directed

tree.

A Kripke structure K = (S, R, L, {sinit}) is tree-like if the graph (S, R) is a finite tree-like graph whose root is the initial state sinit of K.

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Tree-like Kripke structure - example

S1

S3

S2

S4

S6

S5

S7

S1

S3

S2

S4

S6

S5

S7

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Tree-like CE for ACTL - Example φ = AG¬x ⋁ AF¬y

A counterexample for φ shows existence of:

(i) A finite path leading to a state satisfying x.

AND(i) An infinite path along which y is

always true.

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Tree-like CE for ACTL - Example (cont.) Counterexample for the ACTL formula

φ = AG¬x ⋁ AF¬y is a model of the ECTL formula φ’ = EFx ⋀ EGy

y

y

y

xy

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Duality of ACTL and ECTL

Counterexamples for ACTL are closely related to finite models for ECTL.

ECTL has the tree-like model property.

¬φ - an ECTL formula

A tree-like model of ¬φ

A possible counterexample of the formula φ

Duality of ACTL & ECTL Tree-like model

property of ECTL

One of all possible counterexamples over all different Kripke structures

φ - an ACTL formula

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Weakness of ACTL(*)

Weakness of the path formulas. Example: no ACTL formula to express

the property “φ holds at all even time points“:

2 3 4 5 6 …1

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Monotonicity of linear time operators

Example: φ = Fp π ⊨ Fp

……

For every ϭ such that π ⊆p ϭ, ϭ ⊨ Fp:

……

Results from the monotonicity of the operator F.

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From ACTL(*) to AΩ (cont.)

AΩ – an extension of ACTL byω-regular linear time operators.

More expression power.

Retains the monotonicity of the linear time operators.

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LTL operators as patterns

View LTL operators as patterns on the time line.

Can be observed on paths.

Example: Fφ describes the following path patterns:M1, ⊥M1, ⊥ ⊥ M1, ⊥ ⊥ ⊥ M1, …

M1- marker - the position where φ holds.

⊥ - “don’t care”.

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LTL operators as regular expressions

F (⊥)*M1

X ⊥M1

G (M1(ω

U (M1)*M2

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Temporal operators as regular expressions – formal definition

A temporal operator O with n input formulas is defined over the set of words over the alphabet Σ = P({M1....Mn}).

Abbreviations: ⊥ for Φ M1 for the singleton {M1}

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Temporal operators as regular expressions- terminology

If O is defined by an ω-regular expression, we say that O is:

Buchi operator regular computable

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Semantics of regular temporal operators

Let O – a regular temporal operator. π = s0, s1,… a path in in a Kripke

structure K. φ1,…, φn – formulas.

Then K,π ⊨ O(φ1,…, φn) if there exists a pattern o ∈ O such that for all positions i < |o|, and for all Mk ∈ o(i), it holds that K,πi ⊨ φk.

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Regular temporal operators – example 1

Define a new operator – Oeven(φ):

φ holds at all even time points.

An ω-regular expression for Oeven:

(⊥ M1)ω

2 3 4 5 6 …1

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Regular temporal operators – example 1 (cont.)

K,π ⊨ Oeven(φ) ? The marker M1 denotes that φ1 holds. A single possible pattern o ∈ O:

o = ⊥ M1⊥ M1⊥ M1⊥ M1⊥ M1 …

For a path π such that K,π ⊨ Oeven(φ):

∀i: even(i) πi ⊨ φ1, since M1 ∈ o(i).

⇒ φ1 holds at all even time points.

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Regular temporal operators – example 1 (cont.)

¬even(i) ?

πi ⊨ φ1 √

…2 3 4 5 61

πi ⊭ φ1 √

…2 3 4 5 61

Monotonicity of Oeven.

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Regular temporal operators – example 2

Define a new operator – Omax4gap(φ):

There should be no more than four time units between two occurrences of φ.

……

An ω-regular expression for Omax4gap:

(M1| ⊥M1 | ⊥⊥M1 | ⊥⊥⊥M1 | ⊥⊥⊥⊥M1)ω

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Regular temporal operators – example 2 (cont.)

K,π ⊨ Omax4gap(φ) ? The marker M1 denotes that φ1 holds. Many (infinity) possible patterns o ∈ O,

constructed of the 5 building blocks.

Any path π with more than four time units between two occurrences of φ1 will not match any of the patterns, and thus will not satisfy O(φ1).

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Preservation of monotonicity

No enforcement of negation of a sub-formula as a marker.

Therefore all operators we define are monotonic.

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Monotonicity – formal definition

Given a path π and a formula φ, φπ denotes the set of states in π where φ holds.

For a sequence of formulas {φ1,.., φn}, we define π ⊆φ1,.., φn ϭ iff ⋀i=1 φi

π ⊆ φi ϭ.

Lemma - Monotonicity:If K,π ⊨ O(φ1,.., φn) and π ⊆φ1,.., φn ϭ, then K,ϭ ⊨ O(φ1,.., φn).

n

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Monotonicity and counterexamples

We conclude that if K,π ⊭ O(φ1,.., φn) and π ⊆φ1,.., φn ϭ, then K,ϭ ⊭ O(φ1,.., φn).

The refutation of O(φ1,.., φn) on π does not depend on satisfied sub-formulas, but only on violated sub-formulas.

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Monotonicity and counterexamples (cont.)

Example: if K,π ⊭ Oevenφ, then

K,π ⊨ Oevenφ can be disproved by finding an even position j such that K, πj ⊭ φ.

In general: disprove O(φ1,.., φn) by identifying all violations of φ1,.., φn on π.

Counterexample

For O(φ1,.., φn)

CE For φnCE For φ1 …

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The logic AΩ

Given: Ω - a set of temporal regular operators. AP – a set of atomic proposition.

AΩ consists of the following formulas:

I. Every p ∈ AP is in AΩ.

II. For each p ∈ AP, ¬p is in AΩ.

III. If O ∈ Ω is an n-ary operator, and φ1,.., φn ∈ AΩ, then AO(φ1,.., φn) ∈ AΩ.

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The logic AΩ (cont.)

IV. If φ1, φ2 are in AΩ, then φ1⋀φ2 ∈ AΩ and φ1⋁φ2 ∈ AΩ.

V. If φ1,φ2… ∈ AΩ, then ⋀i≥1φi ∈ AΩ.

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Semantics of AΩ K,s ⊨ φ ?

I. If φ is atomic then K,s ⊨ φ iff φ ∈ L(s).

II. K,s ⊨ ¬φ iff K,s ⊭ φ.

III. K,s ⊨ AO(φ1,.., φn) iff for all paths π starting at s it holds that K,s ⊨ O(φ1,.., φn).

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Semantics of AΩ (cont.)

IV. K,s ⊨ φ1⋁φ2 iff K,s ⊨ φ1 or K,s ⊨ φ2.

V. K,s ⊨ φ1⋀φ2 iff K,s ⊨ φ1 and K,s ⊨ φ2.

VI. K,s ⊨ ⋀i≥1φi iff K,s ⊨ φi for all i≥1.

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The logic AΩ (cont.)

AΩ is universal.

ACTL and ACTL* can be definedas subsets of AΩ with finite conjunction.

Any prove of the tree-like counterexample property for AΩ is also valid for ACTL(*).

EΩ is defined similarly by replacing: A ⇒ E ⋀i≥1φi ⇒ ⋁i≥1φi

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Counterexample theorem

Let Ω be a set of temporal Buchi operators. Then AΩ has tree-like counterexamples.

Furthermore, the tree-like counterexamples are effectively computable.

Corollary: EΩ has the tree-like model property.

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Constructing counterexamples

Lemma:Let O be a Buchi operator, K a Kripke structure, and s0 a state such that

K, s0 ⊭ AO(Ψ1,..Ψk).

Then there exists a path ϭ=s0,... such that:

I. K,ϭ ⊭ O(Ψ1,..Ψk).

II. ϭ has the form: s0,…,sN, sN,…,sN+M, sN,… sN+M,…

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Proof sketch for the lemma

The idea:Construct a Buchi automaton for the patterns of ¬O, and use an accepting run of the automaton to obtain a path ϭ with the required property.

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Proof sketch for the lemma (cont.)

O – a set of patterns over the alphabet Σk = P({M1,…,Mk}).

Patterns for ¬O cannot be obtained by using the set-theoretic complement of O, Example:The pattern (⊥)*M1 for the operator F. it’s complement contains the pattern M1M1, although a path where the constraint M1M1 holds will satisfy F.

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Proof sketch for the lemma (cont.)

Therefore, the complement should be calculated for the set O’, where O’ is the “monotonic hull” of O.

Denoting: R - the regular expression for O. R’ - the regular expression for O’. ϭ’ - the set of all symbols of the alphabet

which are supersets of ϭ ∊ Σk.

R’ is obtained from R by replacing all occurrences of ϭ by ϭ’.

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Proof sketch for the lemma (cont.)

What is O’ = L(R’)?If a pattern o is in O, then all patterns obtained from o by adding zero or more additional markers are in O’.

⇒ ¬O’ is the set of all patterns which violate the operator.

Due to monotonicity, in the context of AΩ the operators O and O’ are identical!

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Proof sketch for the lemma (cont.)

Let A be the Buchi automata accepting ¬O’, and π a path such that K,π ⊭ O(Ψ1,..Ψk).

Construct a word sπ such that sπ is accepted by A: sπ(i) = {Mj : K,πi ⊭ Ψj} for all i≥0.

Let q be an accepting state of A which appears infinitely in an accepting run of A for sπ, for the indices a1<a2<…, and the corresponding states in K: π(a1), π(a2)...

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Proof sketch for the lemma (cont.)

K has a finite number of states.⇒ There are 2 indices J<J’ such that π(J)=π(J’).

Choosing the minimal such J<J’, the path ϭ given by:π(0),…, π(aJ), π(aJ),…, π(aJ’-1), π(aJ),… π(aJ’-1),…

matches a word excepted by A.

⇒ A path as stated by the lemma.

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The tree-like property of the path

ϭ = s0,…,sN, sN,…,sN+M, sN,… sN+M,…

If all states are different, then ϭ describes a simple tree-like substructure of K containing the path s0,…,sN, leading to the loop sN,…,sN+M.

Otherwise, a tree-like structure is obtained by un-raveling the path using the indexed Kripke structure.

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The indexed Kripke structure - Kω

K=(S,I,R,L) ⇒ Kω=(Sω,Iω,Rω,Lω): Sω=S x ℕ Iω=I x ℕ (s1

i,s2j) ∈ Rω ⇔ (s1,s2) ∈ R

Lω(si)=L(si)

π = s0,s1,s2… a path on K.

⇒ unravel (C,π) = s0C,s1

C+1,s2C+2…

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The algorithm CEX

Given K, s, φ such that K,s ⊭ φ, CEX(K,s0,φ) computes a tree-like counterexample for K,s ⊨ φ.

The tree-like counterexample is constructed as a substructure of Kω (the index of states is denoted by a global constant C, initialized to 0).

Assumptions: K,s ⊭ φ A model checking procedure for AΩ.

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Algorithm CEX - output format

Description, constructed of:I. Path descriptors <s0,…,sn>

II. Loop descriptors<s0,…,sn,s0 > or <s0,…, sn >ω

S1

S3

S2

S4

S5

S6

<s1,s2>

<s1,s5,s6>

<s6,s6>

<s2,s3,s4>ω

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Algorithm CEX

CEX(K,s0i,φ)

case φ of φ1 ⋁ φ2: CEX(K,s0

i,φ1)

CEX(K,s0i,φ2)

⋀i≥1 φi:

φ1 ⋀ φ2: select j such that K,s ⊭ φj,

CEX(K,s0i,φj)

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Algorithm CEX (cont.)

AO(Ψ1,..Ψk):

determine s0,……,sN,……,sN+M

desc1=<s0i, unravel (C, s1,…sN)>

desc2=<unravel (C+N, sN,…sN+M)>ω

output desc1, desc2.

for all states p in {desc1,desc2}for j ∈ {1,…,k}

if K,p ⊭ Ψj then CEX(K,p,Ψj)

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CEX – correctness

I. Monotonicity – enables reduction of counterexample computation for a formula φ to counterexample computation for the sub-formulas of φ.

II. The indexed Kripke structure allows us to refer to logically independent parts of the counterexample separately.

Monotonicity Kω ω-regularity

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CEX – correctness (cont.)

III. The ω-regularity of the Buchi operators allows us to build the global counterexample from small counterexamples of the form<s0,…,X>,<X,…>ω, using the lemma.

Monotonicity Kω ω-regularity

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Application I :Symbolic counterexample generation

By constructing witnesses for the dual logic ECTL.

Based on: SAT(φ). Symbolic fixpoint computations.

EX EF,EU EG

Singlesymbolic

step

Greatestfixpoint

Leastfixpoint

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Constructing witnesses for ECTL

Algorithm print witness(φ, si)case φ of:

EXΨ: print_witnessEX (Ψ, si)

EFΨ: print_witnessEF (Ψ, si)

EGΨ: print_witnessEG (Ψ, si)

EUΨ: print_witnessEU (Ψ, si)

Ψ1⋀Ψ2: print_witness (Ψ1, si) print_witness (Ψ2, si)

Ψ1⋁Ψ2 : if si ∈ SAT(Ψ1) then print_witness (Ψ1, si) else print witness (Ψ2, si)

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Constructing a witness for EF

The model checker computes the least fixpoint of the operator τ:τ(X) = SAT(φ) ⋃ Img-1(X).

The sets S1 ⊆ S2 ⊆,… ,⊆ Sn, the stages of the fixpoint computation, are then used for computation of a witness.

Obtain a finite path s0,…,sj ,j<n, and unravel it in the same way as in CEX.

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Constructing a witness for EF (cont.)

Algorithm print_witnessEF(φ, s0i)

Determine the stages (S1,…,Sn) of computing EFφ.j := 0repeat

j := j + 1S := Img(sj-1) ⋂ Sn-j

choose sj ∈ Suntil sj ∈ S1

desc := <s0i; unravel(C, s1,…,sj)>

output descC := C + jprint witness(φ, sj

C)

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Constructing a witness for EG

Uses only the last stage, Sn, of the greatest fixpoint computation.

Algorithm print_witnessEG(φ, s0i)

Sn = SAT(EGφ) T = {s0}j = 0repeat

j = j + 1S = Img(sj-1) ⋂ Sn

choose sj ∈ ST = T ∪ {sj}Q = Img(sj) ⋂ T

until Q ≠ Ø…

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Constructing a witness for EG (cont.)

…choose N where sN ∈ Qdesc1 = <s0

i, unravel (C, s1,…,sN)>desc2 = <unravel (C+N, sN,…,sj)>ω

output desc1 and desc2

C = C + j +1for all states p in ⋃{desc1,desc2}

if K,p ⊨ φ then print witness(φ, p)

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Application II : Counterexample-guided refinement

A method for handling the state explosion problem.

When a model is too big for direct model checking, the model checking is applied to an abstraction of the original model.

Given a counterexample for the abstraction, if it is spurious a refinement of the abstraction is done.

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Counterexample-guided refinement – implementation in the system aSMV

Implementation for the ACTL fragment with linear counterexamples.

Given a descriptor of a linear counterexample, symbolic procedures – CheckPATH/CheckLOOP check if the counterexample is spurious.

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Completeness for ACTL

Generalization of spurious check for a descriptor to spurious check of a description.

Finding a set of concrete states from which a linear counterexample

consistent with the descriptor exists.

Finding a set of concrete states from which tree-like counterexamples

consistent with the description exist.

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Completeness for ACTL (cont.)

Algorithm CheckRefine(a0,Q)T = h-1( a0) for each q ∈ Q

if q(0) = a0 thenl = |q|

S1 = h-1(a0)for (i=2 to l)

Si = CheckRefine(q(i-1), Q)if q is a path descriptor then

T = T ⋂ CheckPATH(q, S1,S2,…,Sl)if q is a loop descriptor then

T = T ⋂ CheckLOOP(q, S1,S2,…,Sl)return T

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Summery

Linear counterexamples. Tree-like Kripke structures. Tree-like counterexamples for AΩ (⇒

ACTL). Algorithm CEX for AΩ. Efficient ECTL witnesses construction. Generalization of spurious check for tree-

like counterexamples in aSMV.