Sequentialization targeted to Bounded Model-Checkers Salvatore La - - PowerPoint PPT Presentation

sequentialization targeted to bounded model checkers
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Sequentialization targeted to Bounded Model-Checkers Salvatore La - - PowerPoint PPT Presentation

Sequentialization targeted to Bounded Model-Checkers Salvatore La Torre Dipartimento di Informatica Universit degli Studi di Salerno Sequentialization Code-to-code translation from a multithreaded program to an equivalent


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SLIDE 1

Sequentialization targeted to Bounded Model-Checkers

Salvatore La Torre

Dipartimento di Informatica Università degli Studi di Salerno

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SLIDE 2
  • Code-to-code translation from a multithreaded program to an

“equivalent” sequential one

Conc. program

Sequentialization

T1 T2 Tm

shared vars

loc loc loc

  • Re-use of existing tools (delegate the analysis to the

backend tool)

  • Fast prototyping (designers can concentrate only

concurrency features)

  • Can work with different backends

Seq. Verifier

Seq. progam

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SLIDE 3

Sequentialization

  • alters the original program structure by

injecting control code (which is an overhead for the backend)

  • requires careful attention to the details of

the translation for well-performing tools

  • replaces concurrency with nondeterminism
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SLIDE 4

Backend: Bounded Model Checkers

  • Reduce program verification to SAT/SMT solvers
  • Very effective technique to discover bugs in seq. programs
  • Performance relies on the performance of underlying

solvers

  • Impressive improvement of

SAT solvers in last years

1 10 100 1000 10000 100000 1960 1970 1980 1990 2000 2010 Year Vars

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SLIDE 5

Implementations with BMC backend

  • LR seq. [Lal-Reps, CAV’08]: eager, bounded round-robin
  • LMP seq. [La Torre-Madhusudan-Parlato]: lazy, any scheduling
  • With BMC, LR works better than LMP

[Ghafari-Hu-Rakamaric, SPIN’10]

  • Implementations of LR:

– CSeq: Pthreads C programs [Fischer-Inverso-Parlato, ASE’13] – STORM: also dynamic memory allocation [Lahiri-Qadeer-Rakamaric, CAV’09] – Corral [Lal-Qadeer-Lahiri, CAV’12] – Delay bounded-scheduling [Emmi-Qadeer-Rakamaric, POPL’11]

– Real-time systems [Chaki, Gurfinkel, Strichman – FMCAD’11]

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SLIDE 6

Lal/Reps Sequentialization

  • considers only round-robin schedules

with k rounds – thread → function, run to completion

  • global memory copy for each round

– scalar → array

  • context switch → round counter++
  • first thread starts with

nondeterministic memory contents – other threads continue with content left by predecessor

T0 T1

S2,1 S0,1 S1,1 Sk,1

Tn

... ... ... ... ... ...

S2,0 S0,0 S1,0 Sk,0 S2,n S0,n S1,n Sk,n

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SLIDE 7

Lal/Reps Sequentialization

  • considers only round-robin schedules

with k rounds – thread → function, run to completion

  • global memory copy for each round

– scalar → array

  • context switch → round counter++
  • first thread starts with

nondeterministic memory contents – other threads continue with content left by predecessor

  • checker prunes away inconsistent simulations

– assume(Si+1,0 == S i,n); – requires second set of memory copies – errors can only be checked at end of simulation

  • requires explicit error checks

T0 T1

S2,1 S0,1 S1,1 Sk,1

Tn

... ... ... ... ... ...

S2,0 S0,0 S1,0 Sk,0 S2,n S0,n S1,n Sk,n

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SLIDE 8

CSeq Tool Architecture

[Fischer-Inverso-Parlato, ASE’13]

  • pycparser, AST traversal with unparsing

– insert new type declarations, modify memory accesses – insert context switch simulation code at each sequence point – insert explicit error checks – insert checker and code for pthread functions

sequential non-deterministic C program

P'

concurrent C program

P SAFE UNSAFE CSeq sequential tool k, N

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SLIDE 9

Can we improve this?

  • Eager sequentializations

– cannot rely on error checks built into the backend – also requires specific techniques to handle programs with heap-allocated memory

  • LR (but also LMP) uses additional copies of

shared variables – BMC will make more copies with loop/recursion unwinding – can seriously affect the formula size

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SLIDE 10

Two new sequentializations

[Inverso-Tomasco-Fischer-LaTorre-Parlato]

  • Lazy-CSeq [CAV’14-TACAS/SVCOMP’14]

– lazy – light-weight: few additional variables and code

  • MU-CSeq [TACAS/SVCOMP’14]

– Bound on memory unwindings – Extension message-passing programs

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SLIDE 11

Outline

  • Bounded Model-checking for programs
  • Lazy sequentialization: Lazy-CSeq
  • Memory unwindings: MU-CSeq
  • Experiments
  • Conclusions
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SLIDE 12

How does it work

Transform a programs into a set of equations

  • Simplify control flow
  • Unwind all of the loops
  • Convert into Static Single Assignment (SSA)
  • Convert into equations
  • Bit-blast
  • Solve with a SAT Solver
  • Convert SAT assignment into a counterexample
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SLIDE 13

Control Flow Simplifications

  • All side effect are removed

– e.g., j=i++ becomes

j=i; i=i+1

  • Control Flow is made explicit

– continue, break

replaced by goto

  • All loops are simplified into one form

– for, do, while replaced by while

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SLIDE 14

Loop Unwinding

while() loops are unwound iteratively Break / continue replaced by goto void f(...) { void f(...) { ... while(cond) { Body; } Remainder; }

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SLIDE 15

Loop Unwinding

while() loops are unwound iteratively Break / continue replaced by goto void f(...) { void f(...) { ... if(cond) { Body; while(cond) { Body; } } Remainder; }

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SLIDE 16

Loop Unwinding

while() loops are unwound iteratively Break / continue replaced by goto void f(...) { void f(...) { ... if(cond) { Body; if(cond) { Body; while(cond) { Body; } } } Remainder; }

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SLIDE 17

Unwinding assertion

while() loops are unwound iteratively Break / continue replaced by goto Assume statements inserted after last iteration: block execution if program runs longer than bound permits void f(...) { void f(...) { ... if(cond) { Body; if(cond) { Body; if(cond) { Body; while(cond) { Body; } } } } Remainder; }

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SLIDE 18

Unwinding assertion

while() loops are unwound iteratively Break / continue replaced by goto Assume statements inserted after last iteration: block execution if program runs longer than bound permits void f(...) { void f(...) { ... if(cond) { Body; if(cond) { Body; if(cond) { Body; assume(!cond); } } } } Remainder; }

Unwinding assume

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SLIDE 19

Transforming Loop-Free Programs Into Equations (1)

  • Easy to transform when every variable is only

assigned once!

x = a; y = x + 1; z = y – 1; Program Constraints x = a && y = x + 1 && z = y – 1 &&

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SLIDE 20

Transforming Loop-Free Programs Into Equations (2)

  • When a variable is assigned multiple times,
  • use a new variable for the RHS of each

assignment

Program SSA Program

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SLIDE 21

What about conditionals?

Program SSA Program if (v) x = y; else x = z; w = x; if (v0) x0 = y0; else x1 = z0; w1 = x??; What should ‘x’ be?

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SLIDE 22

What about conditionals?

For each join point, add new variables with selectors

Program SSA Program if (v) x = y; else x = z; w = x; if (v0) x0 = y0; else x1 = z0; x2 = v0 ? x0 : x1; w1 = x2

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SLIDE 23

Example

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SLIDE 24

CBMC: Bounded Model Checker for C

A tool by D. Kroening/Oxford and Ed Clarke/CMU

Parser Static Analysis CNF-gen SAT solver CEX-gen

CBMC

C Program SAFE UNSAFE + CEX

SAT UNSAT CNF goto- program equations

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SLIDE 25

BMC: from sequential to concurrent

  • BMC for sequential programs has been used to discover subtle

errors in applications

  • robust BMC tools exist for C programs (e.g. CBMC, LLBMC,

ESBMC)

  • attempts to apply BMC to multi-threaded programs face

problems number of interleavings grows exponentially with #threads and #statements Recent solutions for multi-threaded programs

  • partial orders
  • sequentializations
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SLIDE 26

Outline

Bounded Model-checking for programs

  • Lazy sequentialization: Lazy-CSeq
  • Memory unwindings: MU-CSeq
  • Experiments
  • Conclusions
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SLIDE 27

Lazy-CSeq schema

  • P' simulates all computations (up to K rounds) of P
  • lazy: avoid exploring unfeasible runs

T₁ ∥ T₂ ∥ … ∥ Tn ↝ (T'1 ; T'2 ; … ; T'n)K

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SLIDE 28

Lazy-CSeq Sequentialization

Translation P ↝ P':

– unwinding, inlining (bounded program) – thread T ↝ function T' – main driver: For each round in [1..K] for each thread in [1..N] T'thread ();

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SLIDE 29

Main driver

K: rounds ct: thread count active[j]: true iff thread j is active cs: guessed context-switch position for coming simulation pc[j]: position when context- switched out of thread j size[j]: last position for context-switches void main(void) { for(r=1; r<=K; r++) { ct=1; // thread 1 if(active[ct]) { //only active theads cs=pc[ct]+nondet uint(); // guess cs assume(cs<=size[ct]); // legal? fseq_1(arg[ct]); // simulate thread pc[ct]=cs; // store cs } : : : : : : : : : ct=n; // thread n if(active[ct]) { : : : : : : : : : } }}

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SLIDE 30

Thread T ↝ function T'

Translation P ↝ P': – unwinding, inlining – thread T ↝ function T' – main driver:

  • for round in [1..K]
  • for thread in [1..N]
  • T'thread ();

Thread T ↝ function T'

  • var x; ↝ static var x;
  • stmt; ↝ guard; stmt;

T'

guard; stmt;

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SLIDE 31

...

Thread T ↝ function T'

T'

Thread simulation: round 1

  • guess context-switch point cs1 (in main)
  • execute stmts before cs1
  • jump in multiple hops to the end

and return

Thread T ↝ function T'

  • var x; ↝ static var x;
  • stmt; ↝ guard; stmt;

context-switch cs1

...

simulation round 1

exec skip

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SLIDE 32

...

Thread T ↝ function T'

Thread simulation: round i

  • guess context-switch point csi (in main)
  • jump in multiple hops to pci-1
  • execute stmts from pci-1 to csi
  • jump in multiple hops to the end

and return

Thread T ↝ function T'

  • var x; ↝ static var x;
  • stmt; ↝ guard; stmt;

simulation round i >1

T' context-switch csi

...

exec skip skip

resume from pci-1

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SLIDE 33

Instrumenting jumping in and out of thread executions

(stmt; ↝ guard; stmt;)

Multiple hops: #define J(A,B) if ( pc[ct] > A || A >= cs ) goto B;

  • Ex. At position 5,

J(5,6) jumps to 6 (next position) when not in [ pc[ct], cs [

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SLIDE 34

Branching stmts

Use macro:

#define G(L) assume(cs >= L);

  • Rules out spurious thread executions

when context-switch position is inside the not picked branch

Thread T ↝ function T'

  • var x; ↝ static var x;
  • stmt; ↝ guard; stmt;

if cond { body1 ↝ }else{ body2 } if cond { body1 }else{ G(A) body2 } G(B)

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SLIDE 35

Example

2:J(2,3) if(c>0) 3:J(3,4) c++; else { 4:J(4,5) c=0; if(!(tmp>0)) goto l1; 5:J(5,6) c++; tmp--; if(!(tmp>0)) goto l1; 6:J(6,7) c++; tmp--; assume(!(tmp>0)); l1: G(7); } G(7) 7:J(7,8) pthread mutex unlock(&m);

Assume pc=2 and cs=3 (only 2: must be executed) Additionally suppose c<=0 holds Execution jumps to the else stmt and exits In main pc is then set to 3 (cs) When resumed, the tread will start from 3: executing c++!!!!! Adding guard G(4) right after the else stmt rules out this unfeasible computation

G(4)

Note this is not ruling out any good exectutions The sketched one is captured by guessing cs=4 instead of cs=3

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SLIDE 36

Outline

Bounded Model-checking for programs Lazy sequentialization: Lazy-CSeq

  • Memory unwindings: MU-CSeq
  • Experiments
  • Conclusions
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SLIDE 37

Main idea

  • Guess a memory unwinding of the shared memory

– sequence of writes into the shared memory of an execution

  • Execute each thread s.t. its local computation is

consistent with the memory unwinding – any scheduling that fits it is considered

  • Crucial notion: all the shared memory operations

are done through a memory object

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SLIDE 38

Memory object

  • Stores a sequence of writes

–Each write is a triple (thread, variable, value)

  • Is used through an interface
  • Several implementations are possible
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SLIDE 39

Memory object interface

int mem_init(uint V, uint W, uint T);

  • instantiate a memory object
  • V = number of variables
  • W = number of writes
  • T = max number of threads
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SLIDE 40

Memory object interface

int read(uint th_id, uint var); void write(uint th_id, uint var, int value); int mem_thread_create(uint parent_id);

  • returns id for created thread

void terminate(uint th_id);

  • checks that all writes of th_id have been

executed ……………

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SLIDE 41

MU-Cseq sequentialization

– A funciton for each thread thread T ↝ function T' – main driver:

void proc main(void) call memory_init(V, W, T); // instantiate memory ct := mem_thread_create(0); // register main thread call mainW

;T(x1,..., xk);

call terminate(ct); // all writes are executed assert(_error != 1) // error check

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SLIDE 42

Basic Idea:

  • uses auxiliary variables

– pos (current index into memory object) – ct (id of currently simulated thread)

  • every thread is translated into a function

– simulation starts from main thread

  • each thread creation interrupts simulation of current thread

– new thread is called with current value of pos

  • terminated threads must have completed their memory writes

– terminate(ct) must hold

  • old thread resumed with old memory position (in the activation

record)

Simulation

simulate all executions compatible with guessed memory unwinding

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SLIDE 43

Basic Idea:

  • every read / write is translated into a function

– simulates valid access into unwound memory (similarly for pthread functions)

Simulation

simulate all executions compatible with guessed memory unwinding

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SLIDE 44

Implementation I: Explicit Read

x y ... z

“memory”

Guess and store sequence of individual write operations:

  • add N copies of shared variables (“memory”)

_memory[i,j] is value of j-th variable after i-th write

  • add array to record writes (“writes”)

i-th write is by _thr[i], which has written to _var[i]

  • add array to record validity of writes (“barrier”)

next write (after i) by thread t is at _next[i,t]

4 4 2 4 3 4 3 42 ... ... ... ... 3 42 1 2 3 4 ... W pos ... ... ... ... ... 1 x 1 y 2 y 1 z ... ... 2 x var thr

“writes”

... ... next[1]

“barrier”

N+1 2 4 4 ... 1 ... 3 next[T] N+1 N+1 N+1 N+1 N+1 N+1 N+1 N+1 N 3 3 N ... ... ... ... ... ... N+1

...

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SLIDE 45

Simulating reads and writes

4 4 2 4 3 4 3 42 ... ... ... ... 3 42 x y

...

z 1 x 1 y 2 y 1 z ... ... 2 x var 1 2 3 4 ... W thr

int read(uint th, uint var) { uint th_pos; if is_terminated(th) then return; th_pos = Jump(th_id); return (mem[th_pos][var]); } “memory” “writes”

pos ... ... ... ... ... ... ... next[1]

“barrier”

N+1 2 4 4 ... 1 ... 3 next[T]

...

N+1 N+1 N+1 N+1 N+1 N+1 N+1 N+1 N 3 3 N ... ... ... ... ... ... N+1

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SLIDE 46

Simulating reads and writes

int write(uint th, uint var, int val) { uint jump; if is_terminated(th) then return; jump=next[pos][th_id]; assume ( (jump<=last_write_pos) && (var[jump]==var) && (value[jump]==val) ); pos=jump; }

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SLIDE 47

Other implementations

  • Implementation II: (Implicit Read)

– mem WxV-array is replaced with W-array

var_next_write[ i ] is smallest j>i s.t. var[ i ]=var[ j ] –saves memory but causes more complex Read implementation (larger formula)

  • Implementation III:

– mixed I and II

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SLIDE 48

Outline

Bounded Model-checking for programs Lazy sequentialization: Lazy-CSeq Memory unwindings: MU-CSeq

  • Experiments
  • Conclusions
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SLIDE 49

Lazy-CSeq won the Gold Medal and MU-CSeq I won the Silver Medal in the Concurrency category

– 76 concurrent C programs

  • UNSAFE instances: 20 programs containing a bug
  • SAFE instances: all the others

– 4,500 l.o.c.

1) CSeq-Lazy: 1,000s, 136pts 2) CSeq-MU I: 1,200s, 136pts 3) CBMC: 29,000s, 128pts Results:

– small verification times – small memory footprint – no missed bugs!

Evaluation: SV-COMP2014

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SLIDE 50

Lazy-Cseq vs Native Concurrency Handling (UNSAFE instances)

_1: timeout (750s) _2: internal error _3: manual translation not done _4: test case rejected _5: unknown failure

Evaluation: bug-hunting

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SLIDE 51

Evaluation: state space coverage

Lazy-CSeq + CBMC vs CBMC (SAFE instances)

How far is it possible to push the unwind bound with the two different methods and still finish the analysis within the given time and space requirements (10GB, 750s)?

  • bounding the rounds

allows deeper exploration of loops

  • alternative coverage
  • f the state space
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SLIDE 52

Evaluation: formula size

Lazy-CSeq + CBMC vs CBMC (v4.7)

(on SV-COMP14 SAFE instances)

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SLIDE 53

MU-CSeq

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SLIDE 54

Outline

Bounded Model-checking for programs Lazy sequentialization: Lazy-CSeq Memory unwindings: MU-CSeq Experiments

  • Conclusions
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SLIDE 55

Conclusions

  • LR and LMP sequentializations

– complete analysis of concurrent programs up to a given number of context-switches (context- bounded analysis [Qadeer-Rehof, CAV’05] – unbounded analysis within each context

  • Lazy-CSeq and MU-CSeq use additional bounding

criteria – backend tool will bound the computations anyway – this can be exploited to induce simplifications of the generated formula

  • Effective for bug-hunting

– many concurrency errors show up within few context-switches

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SLIDE 56

Lazy-CSeq

  • Lightweight sequentialization

– designed to take advantage of modern sequ. BMC tools – small BMC formulae for small number of rounds – reduced memory footprint and verification times

  • Laziness:

– avoid handling spurious errors typical of eager exploration – inherit from the backend tool all checks for sequential C: array-bounds-check, division-by-zero, pointer- checks,

  • verflow-checks, reachability of error labels and

assertion failures, etc. – no need to handle dynamic memory allocation

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SLIDE 57

MU-CSeq

  • Ongoing research
  • Preliminary experiments show it is competitive with state-
  • f-the-art model-checkers
  • II improves on I on some benchmarks
  • III

– performs better than both I and II in general and – when it is outperfomed it stays close to the best of the two

  • NEXT: memory unwinding can be used to sequentialize

message-passing programs

– send/receive instead of read/write

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SLIDE 58

Ermenegildo Tomasco Omar Inverso Gennaro Parlato UK

Lazy-CSeq and MU-CSeq joint work with

Bernd Fischer South Africa