1. Automatically Validating Temporal Safety Properties of Interfaces Thomas Ball and Sriram K. Rajamani Software Productivity Tools, Microsoft Research Presented for CMSC631 by Iulian Neamtiu

2. 2 Goal: Validate temporal safety properties using model checking SLAM Project, Microsoft Research http://research.microsoft.com/slam/

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4. 4 Motivation Large-scale software – many components, many programmers Integration testing Impossible Ineffective at best Fuzzy requirements -> inconsistent implementation Consistent requirements -> inconsistent implementation (Jim Larus)

5. 5 SLAM Approach Modules interact properly… If program observes temporal safety properties of interfaces it uses temporal safety = properties whose violation is witnessed by a finite execution trace, i.e. path to ERROR state State temporal safety properties formally Automatic verification Interface compliance checked statically (catch bugs early)

6. 6 SLAM Process prog. P’ prog. P SLIC rule boolean program path predicates slic C2BP BEBOP NEWTON Language for specifying safety properties Generate abstract boolean program from C code Model checker Predicate discoverer

7. 7 SLAM - formally 1. P’ a C program, E i ={e 1,e 2,…,e n } a set of predicates, apply C2BP to create a boolean program BP(P’,E i ) 2. Apply BEBOP to check whether exists a path p i in BP(P’,E i ) that reaches ERROR state if p i not found, terminate with SUCCESS if p i found go to 3 3. Use NEWTON to check p i feasible If p i feasible, terminate with FAILURE If p i not feasible find set F i of predicates that explains infeasibility 4. E i+1 = E i UF i+1, i=i+1, go to 1

8. 8 Example – device driver do { KeAcquireSpinLock(); nPacketsOld = nPackets; if(request){ request = request->Next; KeReleaseSpinLock(); nPackets++; } } while (nPackets != nPacketsOld); KeReleaseSpinLock(); Prove safety – “something bad does not happen” (lock acquired/released twice)

9. 9 Step 0 – Property Specification typedef {Locked, Unlocked} STATETYPE; typedef {Acq, Rel} MTYPE; STATETYPE state = Unlocked; FSM(m : MTYPE){ if ((state==Unlocked) && (m==Acq)) A: state = Locked; else if ((state==Locked) && (m==Rel)) B: state = Unlocked; else ERROR: ; } SLIC Specification = FSM Global state State transitions (events)

10. 10 Instrumented Program P’ Step 1 - Instrumentation do { KeAcquireSpinLock(); C: FSM(Acq); nPacketsOld = nPackets; if(request){ request = request->Next; KeReleaseSpinLock(); D: FSM(Rel); nPackets++; } E:E: } while (nPackets != nPacketsOld); KeReleaseSpinLock(); F: FSM(Rel); typedef {Locked, Unlocked} STATETYPE; typedef {Acq, Rel} MTYPE; STATETYPE state = Unlocked; FSM(m : MTYPE){ if ((state==Unlocked) && (m==Acq)) A: state = Locked; else if ((state==Locked) && (m==Rel)) B: state = Unlocked; else ERROR: ; } Program PSLIC Specification

11. 11 Step 0 - Specification Step 1 - Instrumentation Step 2 - Abstraction Step 3 - Model Checking Step 4 - Theorem Proving Step 5 – Predicate discovery Outline manual automated

12. 12 Abstraction Abstract Interpretation In C program P set of predicates E={e 1,e 2,…,e n } Out abstract boolean program BP(P,E) with n boolean variables V={b 1,b 2,…,b n } Boolean program (C-like) all vars have type bool control nondeterminism (*) only call by value

13. 13 Step 2 – Abstraction (C2BP) typedef {Locked, Unlocked} STATETYPE; typedef {Acq, Rel} MTYPE; STATETYPE state = Unlocked; FSM(m : MTYPE){ if ((state==Unlocked) && (m==Acq)) A: state = Locked; else if ((state==Locked) && (m==Rel)) B: state = Unlocked; else ERROR: ; } decl {state==Locked, state==Unlocked}; void FSM({m==Acq,m==Rel}){ if ({state==Unlocked} & {m==Acq}) A: {state==Locked, state==Unlocked }:=1,0 ; else if ({state==Locked} & {m==Rel}) B: {state==Locked, state==Unlocked }:=0,1; else ERROR: ; }

14. 14 Instrumented Program P’ Step 2 – Abstraction (C2BP) do { KeAcquireSpinLock(); C: FSM(Acq); nPacketsOld = nPackets; if(request){ request = request->Next; KeReleaseSpinLock(); D: FSM(Rel); nPackets++; } E: } while (nPackets != nPacketsOld); KeReleaseSpinLock(); F: FSM(Rel); Boolean Program BP(P’,E 0 ) do { skip; C: FSM(1,0); skip; if(*){ skip; D: FSM(0,1); skip; } E: } while (*); skip; F: FSM(0,1);

15. 15 Step 3 - Model Checking (BEBOP) Boolean Program BP(P’,E 0 ) do { skip; C: FSM(1,0); skip; if(*){ skip; D: FSM(0,1); skip; } E: } while (*); skip; F: FSM(0,1); decl {state==Locked, state==Unlocked}; void FSM({m==Acq,m==Rel}){ if ({state==Unlocked} & {m==Acq}) A: {state==Locked, state==Unlocked }:=1,0 ; else if ({state==Locked} & {m==Rel}) B: {state==Locked, state==Unlocked }:=0,1; else ERROR: ; } Is there a path that leads to ERROR ?YES [C,A,E,C,ERROR ] 1 2 3 4

16. 16 do { KeAcquireSpinLock(); C: FSM(Acq); nPacketsOld = nPackets; if(request){ request = request->Next; KeReleaseSpinLock(); D: FSM(Rel); nPackets++; } E: } while (nPackets != nPacketsOld); KeReleaseSpinLock(); F: FSM(Rel); Step 4 – Theorem Proving (NEWTON) typedef {Locked, Unlocked} STATETYPE; typedef {Acq, Rel} MTYPE; STATETYPE state = Unlocked; FSM(m : MTYPE){ if ((state==Unlocked) && (m==Acq)) A: state = Locked; else if ((state==Locked) && (m==Rel)) B: state = Unlocked; else ERROR: ; } Is path [C,A,E,C] feasible ?NO // nPacketsOld==nPackets, nPacketsOld != nPackets

17. 17 Step 5 – Predicate Discovery (NEWTON) b: {nPackets == nPacketsOld}; do { skip; b:=1; C: FSM(1,0); skip; if(*){ skip; D: FSM(0,1); skip; b:=0; } E: } while (!b); skip; F: FSM(0,1); do { skip; C: FSM(1,0); skip; if(*){ skip; D: FSM(0,1); skip; } E: } while (*); skip; F: FSM(0,1); Boolean Program BP(P’,E 0 )Boolean Program BP(P’,E 1 )

18. 18 Step 3 - Model Checking (BEBOP) do { skip; b:=1; C: FSM(1,0); skip; if(*){ skip; D: FSM(0,1); skip; b:=0; } E: } while (!b); skip; F: FSM(0,1); decl {state==Locked, state==Unlocked}; decl b: {nPackets==nPacketsOld}; void FSM({m==Acq,m==Rel}){ if ({state==Unlocked} & {m==Acq}) A: {state==Locked, state==Unlocked }:=1,0 ; else if ({state==Locked} & {m==Rel}) B: {state==Locked, state==Unlocked }:=0,1; else ERROR: ; } Is there a path that leads to ERROR ?NO

19. 19 C2BP From a C program P and a set of predicates E={e 1,e 2,…,e n } create an abstract boolean program BP(P,E) which has n boolean variables V={b 1,b 2,…,b n } Determine for each statement s in P and predicate e i in E how the execution of s can affect the truth value of e i if it doesn’t, s->skip

20. 20 C2BP cont’d Static analysis alias logical model: p, p+i same object interprocedural side-effects (conservative)

21. 21 BEBOP Essentially a model checker Interprocedural dataflow analysis -> reachable states Uses BDDs to represent state/transfer functions ERROR state reachability reduces to vertex reachability on the CFG of the boolean program BP which is decidable

22. 22 NEWTON Predicate discoverer / Theorem prover walk error path p found by BEBOP compute conditions (predicate values) along p if algorithm terminates inconsistence detected (  =!  ), add  to list of predicates, repeat whole process else report p as witness

23. 23 Results NT device drivers Max 60000 LOC <10 user-supplied predicates, tens-hundreds inferred < 20-30 iterations 672 runs daily, 607 terminate within 20 minutes

24. 24 SLAM vs Metacompilation (Engler et al.) SLAMMetacompilation SpecificationSLICmetal Sound Complete Scalability (LOC)10,0001,000,000 Refinement Spurious errorsVery FewMany

25. 25 Conclusions SLAM = process for checking temporal safety properties Formally state safety properties that interface clients must observe Fully automated validation (iterative refinement) Sound; if process terminates either SUCCESS or FAILURE (w/counterexample) reported Accurate (few false positives) - Poor scalability

26. Thank You Questions ?

27. 27 Complexity O(|P| x 2 |E| ) worst case In practice O(|E| 3 )

28. 28 SLAM = A collection of tools SLIC Language for specifying safety properties C2BP Generate abstract boolean program from C code BEBOP Model checking boolean programs NEWTON Theorem prover Refine boolean program

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