Program Verification by Lazy Abstraction Ranjit Jhala UC San Diego Lecture 1 With: Tom Henzinger, Rupak Majumdar, Ken McMillan, Gregoire Sutre

Software Validation Large scale reliable software is hard to build and test Different groups write different components Integration testing is a nightmare

Property Checking Programmer gives partial specifications Code checked for consistency w/ spec Different from program correctness –Specifications are not complete –Is there a complete spec for Word ? Emacs ?

Interface Usage Rules Rules in documentation –Order of operations & data access –Resource management –Incomplete, unenforced, wordy Violated rules ) bad behavior –System crash or deadlock –Unexpected exceptions –Failed runtime checks

Property 1: Double Locking “An attempt to re-acquire an acquired lock or release a released lock will cause a deadlock.” Calls to lock and unlock must alternate. lock unlock

Property 2: Drop Root Privilege “User applications must not run with root privilege” When execv is called, must have suid  0 [Chen-Dean-Wagner ’02]

Property 3 : IRP Handler [Fahndrich] MPR3 CallDriver MPR completion synch not pending returned SKIP2 IPC CallDriver Skip return child status DC Complete request return not Pend PPC prop completion CallDriver N/A no prop completion CallDriver start NP return Pending NP MPR1 MPR completion SKIP2 IPC CallDriver DC Complete request PPC prop completion CallDriver N/A no prop completion CallDriver start P Mark Pending IRP accessible N/A synch SKIP1 CallDriver SKIP1 Skip MPR2 MPR1 NP MPR3 CallDriver not pending returned MPR2 synch

Does a given usage rule hold? Undecidable! –Equivalent to the halting problem Restricted computable versions are prohibitively expensive (PSPACE) Why bother ? –Just because a problem is undecidable, it doesn’t go away!

Example Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4: } while(new != old); 5: unlock (); return; } Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4: } while(new != old); 5: unlock (); return; } lock unlock

What a program really is… State Transition 3: unlock(); new++; 4:} … 3: unlock(); new++; 4:} … pc lock old new q  3   5  0x133a pc lock old new q  4   5  6  0x133a Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4: } while(new != old); 5: unlock (); return;} Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4: } while(new != old); 5: unlock (); return;}

The Safety Verification Problem Initial Error Is there a path from an initial to an error state ? Problem: Infinite state graph Solution : Set of states ' logical formula Safe

Representing States as Formulas [F] states satisfying F {s | s ² F } F FO fmla over prog. vars [F 1 ] Å [F 2 ]F1 Æ F2F1 Æ F2 [F 1 ] [ [F 2 ]F 1 Ç F 2 [F][F] : F [F 1 ] µ [F 2 ]F 1 implies F 2 i.e. F 1 Æ: F 2 unsatisfiable

Idea 1: Predicate Abstraction Predicates on program state: lock old = new States satisfying same predicates are equivalent –Merged into one abstract state #abstract states is finite

Abstract States and Transitions State 3: unlock(); new++; 4:} … 3: unlock(); new++; 4:} … pc lock old new q  3   5  0x133a pc lock old new q  4   5  6  0x133a lock old=new : lock : old=new Theorem Prover

Abstraction State 3: unlock(); new++; 4:} … 3: unlock(); new++; 4:} … pc lock old new q  3   5  0x133a pc lock old new q  4   5  6  0x133a lock old=new : lock : old=new Theorem Prover Existential Lifting

Abstraction State 3: unlock(); new++; 4:} … 3: unlock(); new++; 4:} … pc lock old new q  3   5  0x133a pc lock old new q  4   5  6  0x133a lock old=new : lock : old=new

Analyze Abstraction Analyze finite graph Over Approximate: Safe ) System Safe No false negatives Problem Spurious counterexamples

Idea 2: Counterex.-Guided Refinement Solution Use spurious counterexamples to refine abstraction !

1. Add predicates to distinguish states across cut 2. Build refined abstraction Solution Use spurious counterexamples to refine abstraction Idea 2: Counterex.-Guided Refinement Imprecision due to merge

Iterative Abstraction-Refinement 1. Add predicates to distinguish states across cut 2. Build refined abstraction -eliminates counterexample 3. Repeat search Till real counterexample or system proved safe Solution Use spurious counterexamples to refine abstraction [Kurshan et al 93] [Clarke et al 00] [Ball-Rajamani 01]

Lazy Abstraction Abstract Refine C Program Safe Trace Yes No Property BLAST

Problem: Abstraction is Expensive Reachable Problem #abstract states = 2 #predicates Exponential Thm. Prover queries Observe Fraction of state space reachable #Preds ~ 100’s, #States ~ 2 100, #Reach ~ 1000’s

Safe Solution Build abstraction during search Problem #abstract states = 2 #predicates Exponential Thm. Prover queries Solution1 : Only Abstract Reachable States

Solution Don’t refine error-free regions Problem #abstract states = 2 #predicates Exponential Thm. Prover queries Solution2: Don’t Refine Error-Free Regions Error Free

Key Idea: Reachability Tree Unroll Abstraction 1. Pick tree-node (=abs. state) 2. Add children (=abs. successors) 3. On re-visiting abs. state, cut-off Find min infeasible suffix - Learn new predicates - Rebuild subtree with new preds. Initial

Key Idea: Reachability Tree Error Free Unroll Abstraction 1. Pick tree-node (=abs. state) 2. Add children (=abs. successors) 3. On re-visiting abs. state, cut-off Find min infeasible suffix - Learn new predicates - Rebuild subtree with new preds. Initial

Key Idea: Reachability Tree Error Free SAFE Unroll 1. Pick tree-node (=abs. state) 2. Add children (=abs. successors) 3. On re-visiting abs. state, cut-off Find min spurious suffix - Learn new predicates - Rebuild subtree with new preds. S1 : Only Abstract Reachable States S2: Don’t refine error-free regions Initial

Build-and-Search Predicates: LOCK : LOCK Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } 1 1 Reachability Tree

Build-and-Search Predicates: LOCK : LOCK Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } 1 1 lock() old = new q=q->next LOCK 2 2 Reachability Tree

Build-and-Search Predicates: LOCK : LOCK Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } 1 1 LOCK 2 2 [q!=NULL] 3 3 Reachability Tree

Build-and-Search Predicates: LOCK : LOCK Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } 1 1 LOCK q ->data = new unlock() new : LOCK Reachability Tree

Build-and-Search Predicates: LOCK : LOCK Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } 1 1 LOCK : LOCK [new==old] 5 5 Reachability Tree

Build-and-Search Predicates: LOCK : LOCK Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } 1 1 LOCK : LOCK 5 5 unlock() : LOCK Reachability Tree

Analyze Counterexample Predicates: LOCK : LOCK Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } 1 1 LOCK : LOCK 5 5 Reachability Tree lock() old = new q=q->next [q!=NULL] q ->data = new unlock() new++ [new==old] unlock()

Analyze Counterexample Predicates: LOCK : LOCK Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } 1 1 LOCK : LOCK 5 5 [new==old] new++ old = new Inconsistent new == old Reachability Tree

Repeat Build-and-Search Predicates: LOCK, new==old : LOCK Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } 1 1 Reachability Tree

Repeat Build-and-Search Predicates: LOCK, new==old : LOCK Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } 1 1 LOCK, new==old 2 2 lock() old = new q=q->next Reachability Tree

Repeat Build-and-Search Predicates: LOCK, new==old : LOCK Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } 1 1 LOCK, new==old q ->data = new unlock() new++ : LOCK, : new = old Reachability Tree

Repeat Build-and-Search Predicates: LOCK, new==old : LOCK Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } 1 1 LOCK, new==old : LOCK, : new = old [new==old] Reachability Tree

Repeat Build-and-Search Predicates: LOCK, new==old : LOCK Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } 1 1 LOCK, new==old : LOCK, : new = old : LOCK, : new == old 1 [new!=old] 4 Reachability Tree

Repeat Build-and-Search Predicates: LOCK, new==old : LOCK Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } LOCK, new=old 4 4 : LOCK, new==old 5 5 SAFE Reachability Tree LOCK, new==old : LOCK, : new = old : LOCK, : new == old

Key Idea: Reachability Tree Error Free SAFE Unroll 1. Pick tree-node (=abs. state) 2. Add children (=abs. successors) 3. On re-visiting abs. state, cut-off Find min spurious suffix - Learn new predicates - Rebuild subtree with new preds. S1 : Only Abstract Reachable States S2: Don’t refine error-free regions Initial

Two handwaves Predicates: LOCK, new==old : LOCK Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } LOCK, new=old 4 4 : LOCK, new==old 5 5 SAFE Reachability Tree LOCK, new==old : LOCK, : new = old : LOCK, : new == old

Two handwaves Predicates: LOCK, new==old : LOCK Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } LOCK, new=old 4 4 : LOCK, new==old 5 5 SAFE Reachability Tree LOCK, new==old : LOCK, : new = old : LOCK, : new == old 3 4 LOCK, new==old : LOCK, : new = old q ->data = new unlock() new++ Q. How to compute “successors” ?

Two handwaves : LOCK Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } LOCK, new=old 4 4 : LOCK, new==old 5 5 SAFE LOCK, new==old : LOCK, : new = old : LOCK, : new == old Q. How to find predicates ? Q. How to compute “successors” ? Predicates: LOCK, new==old Refinement

Predicates: LOCK, new==old Refinement Two handwaves : LOCK Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } LOCK, new=old 4 4 : LOCK, new==old 5 5 SAFE LOCK, new==old : LOCK, : new = old : LOCK, : new == old Q. How to compute “successors” ?

Weakest Preconditions [P][P] OP [WP(P, OP)] WP(P,OP) Weakest formula P’ s.t. if P’ is true before OP then P is true after OP

Weakest Preconditions [P][P] OP [WP(P, OP)] WP(P,OP) Weakest formula P’ s.t. if P’ is true before OP then P is true after OP Assign x = ex = e P P[e/x] new = old new = new+1 new+1 = old

Weakest Preconditions P c ) P new = old new=old ) new=old [c] Branch Assume [new=old] [P][P] OP [WP(P, OP)] WP(P,OP) Weakest formula P’ s.t. if P’ is true before OP then P is true after OP

How to compute successor ? Predicates: LOCK, new==old Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } 3 4 LOCK, new==old : LOCK, : new = old OP For each p Check if p is true (or false) after OP Q: When is p true after OP ? - If WP(p, OP) is true before OP ! - We know F is true before OP - Thm. Pvr. Query: F ) WP(p, OP) F ?

How to compute successor ? Predicates: LOCK, new==old Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } 3 4 LOCK, new==old OP For each p Check if p is true (or false) after OP Q: When is p false after OP ? - If WP( : p, OP) is true before OP ! - We know F is true before OP - Thm. Pvr. Query: F ) WP( : p, OP) F ?

How to compute successor ? Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4:}while(new != old); 5: unlock (); } 3 4 LOCK, new==old : new = old OP For each p Check if p is true (or false) after OP Q: When is p false after OP ? - If WP( : p, OP) is true before OP ! - We know F is true before OP - Thm. Pvr. Query: F ) WP( : p, OP) F ? (LOCK, new==old) ) (new + 1 = old) (LOCK, new==old) ) (new + 1  old) NO YES : LOCK, : new = old Predicate: new==old True ? False ?

Lazy Abstraction Abstract Refine C Program Safe Trace Yes No Property Key Idea: Reachability Tree Solution: 1. Abstract reachable states, 2. Avoid refining error-free regions Problem: Abstraction is Expensive

Property: IRP Handler [Fahndrich] MPR3 CallDriver MPR completion synch not pending returned SKIP2 IPC CallDriver Skip return child status DC Complete request return not Pend PPC prop completion CallDriver N/A no prop completion CallDriver start NP return Pending NP MPR1 MPR completion SKIP2 IPC CallDriver DC Complete request PPC prop completion CallDriver N/A no prop completion CallDriver start P Mark Pending IRP accessible N/A synch SKIP1 CallDriver SKIP1 Skip MPR2 MPR1 NP MPR3 CallDriver not pending returned MPR2 synch

Results Program Lines * Time(mins)Predicates kbfiltr 12k134 floppy 17k793 diskprf 14k571 cdaudio 18k2085 parport 61kDNF parclss 138kDNF Property3: IRP Handler Win NT DDK * Pre-processed

Tracking lock not enough #Predicates grows with program size Problem: p 1,…,p n needed for verification Exponential reachable abstract states while(1){ 1: if (p 1 ) lock() ; if (p 1 ) unlock() ; … 2: if (p 2 ) lock() ; if (p 2 ) unlock() ; … n: if (p n ) lock() ; if (p n ) unlock() ; } while(1){ 1: if (p 1 ) lock() ; if (p 1 ) unlock() ; … 2: if (p 2 ) lock() ; if (p 2 ) unlock() ; … n: if (p n ) lock() ; if (p n ) unlock() ; } TFTTFT

#Predicates grows with program size Problem: p 1,…,p n needed for verification Exponential reachable abstract states while(1){ 1: if (p 1 ) lock() ; if (p 1 ) unlock() ; … 2: if (p 2 ) lock() ; if (p 2 ) unlock() ; … n: if (p n ) lock() ; if (p n ) unlock() ; } while(1){ 1: if (p 1 ) lock() ; if (p 1 ) unlock() ; … 2: if (p 2 ) lock() ; if (p 2 ) unlock() ; … n: if (p n ) lock() ; if (p n ) unlock() ; } : LOCK : LOCK, p 1 p1p2p1p2 p 1 : p 2 : p 1 p 2 : p 1 : p 2 LOCK, p 1 : LOCK, : p 1 2 n Abstract States : LOCK

Predicates useful locally while(1){ 1: if (p 1 ) lock() ; if (p 1 ) unlock() ; … 2: if (p 2 ) lock() ; if (p 2 ) unlock() ; … n: if (p n ) lock() ; if (p n ) unlock() ; } while(1){ 1: if (p 1 ) lock() ; if (p 1 ) unlock() ; … 2: if (p 2 ) lock() ; if (p 2 ) unlock() ; … n: if (p n ) lock() ; if (p n ) unlock() ; } : LOCK : LOCK, p 1 LOCK, p 1 : LOCK, : p 1 2n Abstract States p1p1 p2p2 pnpn : LOCK LOCK, p 2 : LOCK, : p 2 : LOCK Solution: Use predicates only where needed Using Counterexamples: Q1. Find predicates Q2. Find where predicates are needed

Lazy Abstraction Abstract Refine C Program Safe Trace Yes No Property Refine Pred. Map PC  Preds. Ctrex. Trace Solution: Localize pred. use, find where preds. needed Problem: #Preds grows w/ Program Size

Counterexample Traces 1: x = ctr 2: ctr = ctr + 1 3: y = ctr 4: assume(x = i-1) 5: assume(y  i) y = x +1 1: x = ctr; 2: ctr = ctr + 1; 3: y = ctr; 4: if (x = i-1){ 5: if (y != i){ ERROR: } } 1: x = ctr; 2: ctr = ctr + 1; 3: y = ctr; 4: if (x = i-1){ 5: if (y != i){ ERROR: } }

Trace Formulas 1: x = ctr 2: ctr = ctr+1 3: y = ctr 4: assume(x=i-1) 5: assume(y  i) Trace SSA Trace x 1 = ctr 0 Æ ctr 1 = ctr Æ y 1 = ctr 1 Æ x 1 = i Æ y 1  i 0 1: x 1 = ctr 0 2: ctr 1 = ctr : y 1 = ctr 1 4: assume(x 1 =i 0 -1) 5: assume(y 1  i 0 ) Trace Feasibility Formula Thm: Trace is feasible, TF is satisfiable

The Present State… 1: x = ctr 2: ctr = ctr + 1 3: y = ctr 4: assume(x = i-1) 5: assume(y  i) Trace … is all the information the executing program has here 1. … after executing trace past (prefix) 2. … knows present values of variables 3. … makes trace future (suffix) infeasible State… At pc 4, which predicate on present state shows infeasibility of future ?

What Predicate is needed ? Trace 1: x = ctr 2: ctr = ctr + 1 3: y = ctr 4: assume(x = i-1) 5: assume(y  i) Trace Formula (TF) x 1 = ctr 0 Æ ctr 1 = ctr Æ y 1 = ctr 1 Æ x 1 = i Æ y 1  i 0

What Predicate is needed ? Trace 1: x = ctr 2: ctr = ctr + 1 3: y = ctr 4: assume(x = i-1) 5: assume(y  i) Trace Formula (TF) x 1 = ctr 0 Æ ctr 1 = ctr Æ y 1 = ctr 1 Æ x 1 = i Æ y 1  i 0 1. … after executing trace prefix Relevant Information … implied by TF prefix Predicate …

1: x = ctr 2: ctr = ctr + 1 3: y = ctr 4: assume(x = i-1) 5: assume(y  i) 1. … after executing trace prefix 2. … has present values of variables What Predicate is needed ? Trace Trace Formula (TF) x 1 = ctr 0 Æ ctr 1 = ctr Æ y 1 = ctr 1 Æ x 1 = i Æ y 1  i 0 … implied by TF prefix … on common variables Predicate … x1x1 x1x1 Relevant Information

1: x = ctr 2: ctr = ctr + 1 3: y = ctr 4: assume(x = i-1) 5: assume(y  i) 1. … after executing trace prefix 2. … has present values of variables 3. … makes trace suffix infeasible What Predicate is needed ? Trace Trace Formula (TF) x 1 = ctr 0 Æ ctr 1 = ctr Æ y 1 = ctr 1 Æ x 1 = i Æ y 1  i 0 … implied by TF prefix … on common variables … & TF suffix is unsatisfiable Predicate …Relevant Information

1: x = ctr 2: ctr = ctr + 1 3: y = ctr 4: assume(x = i-1) 5: assume(y  i) What Predicate is needed ? Trace Trace Formula (TF) x 1 = ctr 0 Æ ctr 1 = ctr Æ y 1 = ctr 1 Æ x 1 = i Æ y 1  i 0 Predicate … 1. … after executing trace prefix 2. … has present values of variables 3. … makes trace suffix infeasible … implied by TF prefix … on common variables … & TF suffix is unsatisfiable Relevant Information

Interpolant = Predicate ! -- ++ Interpolate  Trace Formula x 1 = ctr 0 Æ ctr 1 = ctr Æ y 1 = ctr 1 Æ x 1 = i Æ y 1  i 0 y 1 = x Predicate … … implied by TF prefix … on common variables … & TF suffix is unsatisfiable Craig Interpolant [Craig 57] Computable from Proof of Unsat [Krajicek 97] [Pudlak 97] 1: x = ctr 2: ctr = ctr + 1 3: y = ctr 4: assume(x = i-1) 5: assume(y  i) Trace Predicate at 4: y= x+1

Another interpretation … -- ++ Interpolate  Trace Formula x 1 = ctr 0 Æ ctr 1 = ctr Æ y 1 = ctr 1 Æ x 1 = i Æ y 1  i 0 y 1 = x Unsat = Empty Intersection = Trace Infeasible Predicate at 4: y= x+1 -- ++ After exec prefix Can exec suffix  Interpolant  = Overapprox. states after prefix that cannot execute suffix

Interpolant = Predicate ! -- ++ Interpolate  Trace Formula x 1 = ctr 0 Æ ctr 1 = ctr Æ y 1 = ctr 1 Æ x 1 = i Æ y 1  i 0 y 1 = x Predicate … … implied by TF prefix … on common variables … & TF suffix is unsatisfiable Craig Interpolant [Craig 57] Computable from Proof of Unsat [Krajicek 97] [Pudlak 97] 1: x = ctr 2: ctr = ctr + 1 3: y = ctr 4: assume(x = i-1) 5: assume(y  i) Trace Predicate at 4: y= x+1

Interpolant = Predicate ! -- ++ Interpolate  Trace Formula x 1 = ctr 0 Æ ctr 1 = ctr Æ y 1 = ctr 1 Æ x 1 = i Æ y 1  i 0 y 1 = x Predicate … … implied by TF prefix … on common variables … & TF suffix is unsatisfiable Craig Interpolant [Craig 57] Computable from Proof of Unsat [Krajicek 97] [Pudlak 97] 1: x = ctr 2: ctr = ctr + 1 3: y = ctr 4: assume(x = i-1) 5: assume(y  i) Trace Predicate at 4: y= x+1 Q. How to compute interpolants ? …

Building Predicate Maps TraceTrace Formula x 1 = ctr 0 Æ ctr 1 = ctr Æ y 1 = ctr 1 Æ x 1 = i Æ y 1  i 0 Cut + Interpolate at each point Pred. Map: pc i  Interpolant from cut i -- ++ x 1 = ctr 0 Predicate Map 2: x= ctr 1: x = ctr 2: ctr = ctr + 1 3: y = ctr 4: assume(x = i-1) 5: assume(y  i) Interpolate

Building Predicate Maps TraceTrace Formula x 1 = ctr 0 Æ ctr 1 = ctr Æ y 1 = ctr 1 Æ x 1 = i Æ y 1  i 0 -- ++ 1: x = ctr 2: ctr = ctr + 1 3: y = ctr 4: assume(x = i-1) 5: assume(y  i) Predicate Map 2: x = ctr 3: x= ctr-1 x 1 = ctr 1 -1 Interpolate Cut + Interpolate at each point Pred. Map: pc i  Interpolant from cut i

Building Predicate Maps TraceTrace Formula x 1 = ctr 0 Æ ctr 1 = ctr Æ y 1 = ctr 1 Æ x 1 = i Æ y 1  i 0 1: x = ctr 2: ctr = ctr + 1 3: y = ctr 4: assume(x = i-1) 5: assume(y  i) Predicate Map 2: x = ctr 3: x= ctr - 1 4: y= x + 1 y 1 = x 1 +1 -- ++ Interpolate Cut + Interpolate at each point Pred. Map: pc i  Interpolant from cut i

Building Predicate Maps TraceTrace Formula x 1 = ctr 0 Æ ctr 1 = ctr Æ y 1 = ctr 1 Æ x 1 = i Æ y 1  i 0 1: x = ctr 2: ctr = ctr + 1 3: y = ctr 4: assume(x = i-1) 5: assume(y  i) Predicate Map 2: x = ctr 3: x= ctr - 1 4: y= x + 1 5: y = i y 1 = i 0 -- ++ Interpolate Cut + Interpolate at each point Pred. Map: pc i  Interpolant from cut i

Local Predicate Use Predicate Map 2: x = ctr 3: x= ctr - 1 4: y= x + 1 5: y = i Use predicates needed at location #Preds. grows with program size #Preds per location small Local Predicate use Ex: 2n states Global Predicate use Ex: 2 n states Verification scales …

Results Program Lines * Previous Time(mins) Time (mins) Predicates Total Average kbfiltr 12k floppy 17k diskprf 14k cdaudio 18k parport 61kDNF parclss 138kDNF * Pre-processed Property3: IRP Handler Win NT DDK

Localizing Program Lines * Previous Time(mins) Time (mins) Predicates Total Average kbfiltr 12k floppy 17k diskprf 14k cdaudio 18k parport 61kDNF parclss 138kDNF * Pre-processed Property3: IRP Handler Win NT DDK

Q. How to compute interpolants ?

Proof of Unsatisfiability Trace Formula x 1 = ctr 0 Æ ctr 1 = ctr Æ y 1 = ctr 1 Æ x 1 = i Æ y 1  i 0 x 1 = ctr 0 x 1 = i 0 -1 ctr 0 = i 0 -1 ctr 1 = ctr 0 +1 ctr 1 = i 0 y 1 = ctr 1 y 1 = i 0 y 1  i 0 ; Proof of Unsatisfiability

Another Proof of Unsatisfiability x 1 – ctr 0 =0 x 1 -i 0 +1=0 ctr 0 -i 0 +1=0 ctr 1 - ctr 0 -1=0 ctr 1 -i 0 =0 y 1 -ctr 1 =0 y 1 -i 0 =0 y 1 -i 0  0 0  0 Rewritten Proof £ 1 £ (-1) £ 1 x 1 = ctr 0 x 1 = i 0 -1 ctr 0 = i 0 -1 ctr 1 = ctr 0 +1 ctr 1 = i 0 y 1 = ctr 1 y 1 = i 0 y 1  i 0 ; Proof of Unsatisfiability

Interpolant from Rewritten Proof ? Trace Formula x 1 = ctr 0 Æ ctr 1 = ctr Æ y 1 = ctr 1 Æ x 1 = i Æ y 1  i 0 x 1 – ctr 0 =0 x 1 -i 0 +1=0 ctr 0 -i 0 +1=0 ctr 1 - ctr 0 -1=0 ctr 1 -i 0 =0 y 1 -ctr 1 =0 y 1 -i 0 =0 y 1 -i 0  0 0  0 Rewritten Proof £ 1 £ (-1) £ 1 Interpolate

Interpolant from Rewritten Proof ? Trace Formula x 1 = ctr 0 Æ ctr 1 = ctr Æ y 1 = ctr 1 Æ x 1 = i Æ y 1  i 0 x 1 – ctr 0 =0 ctr 1 - ctr 0 -1=0 y 1 -ctr 1 =0 Interpolant ! £ (-1) £ 1 Interpolate y 1 -x 1 -1=0 y 1 =x 1 +1

Lazy Abstraction Abstract Refine C Program Safe Trace Yes No Property Refine Trace Feas Formula Thm Pvr Proof of Unsat Pred. Map PC  Preds. Ctrex. Trace Interpolate Solution: Localize pred. use, find where preds. needed Problem: #Preds grows w/ Program Size

Verification by Theorem Proving 1. Loop Invariants 2. Logical formula 3. Check Validity Invariant: lock Æ new = old Ç : lock Æ new  old Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4: } while(new != old); 5: unlock (); return; } Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4: } while(new != old); 5: unlock (); return; }

Verification by Theorem Proving 1. Loop Invariants 2. Logical formula 3. Check Validity - Loop Invariants - Multithreaded Programs + Behaviors encoded in logic + Decision Procedures - Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4: } while(new != old); 5: unlock (); return; } Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4: } while(new != old); 5: unlock (); return; } Precise [ESC]

Verification by Program Analysis 1. Dataflow Facts 2. Constraint System 3. Solve constraints Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4: } while(new != old); 5: unlock (); return; } Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4: } while(new != old); 5: unlock (); return; } - Imprecision due to fixed facts + Abstraction + Type/Flow Analyses Scalable [CQUAL, ESP, MC]

Verification by Model Checking 1. (Finite State) Program 2. State Transition Graph 3. Reachability Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4: } while(new != old); 5: unlock (); return; } Example ( ) { 1: do{ lock(); old = new; q = q->next; 2: if (q != NULL){ 3: q->data = new; unlock(); new ++; } 4: } while(new != old); 5: unlock (); return; } - Pgm ! Finite state model -State explosion + State Exploration + Counterexamples Precise [SPIN, SMV, Bandera,JPF ]

Combining Strengths Theorem Proving - loop invariants + Behaviors encoded in logic Refine + Theorem provers Computing Successors,Refine Program Analysis - Imprecise + Abstraction Shrink state space Model Checking - Finite-state model, state explosion + State Space Exploration Path Sensitive Analysis + Counterexamples Finding Relevant Facts Lazy Abstraction

Lazy Abstraction: Main Ideas Predicates: –Abstract infinite program states Counterexample-guided Refinement: –Find predicates tailored to prog, property 1.Abstraction : Expensive Reachability Tree 2.Refinement : Find predicates, use locations Proof of unsat of TF + Interpolation

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