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10.8.2006 SAT-based methods for proving properties in Reynolds/O'Hearn Separation Logic Daniel Kröning (currently visiting CBL) Joint work with B. Cook and J. Berdine

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10.8.2006 Daniel Kroening 2 Program Verification Goal: Editor that highlights programming errors Not syntax, but semantics

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10.8.2006 Daniel Kroening 3 Like what?

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10.8.2006 Daniel Kroening 4 Verification Engines UnwindingAbstraction Bounded Model Checking (BMC) No invariant discovery One very large constraint problem A lot of case-splitting Abstract interpretation Predicate abstraction Attempting invariant discovery Many small constraint problems Little case-splitting

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10.8.2006 Daniel Kroening 5 Program Analysis: BMC BMC Progra m C ONSTRAINT S OLVER VC Model SAT solver, CVC-Lite, Math-SAT, … CBMC, …

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10.8.2006 Daniel Kroening 6 BMC Overview ANSI-C Program unwind parsing + * = Parse tree + * = Constraint Problem CNF SAT Solver

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10.8.2006 Daniel Kroening 7 ANSI-C Transformation 1.Preparation Side effect removal continue, break replaced by goto for, do while replaced by while 2.Unwinding Loops are unwound Same for backward goto jumps and recursive functions

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10.8.2006 Daniel Kroening 8 Implementation 3.Transformation into Equation After unwinding: Transform into SSA Example: Generate constraints by simply conjoining equations resulting from assignments For arrays, use simple lambda notation

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10.8.2006 Daniel Kroening 9 Example

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10.8.2006 Daniel Kroening 10 Required Theories Bit vector Arrays Pointers (pair of object/offset) Floating Point If contained in assertion: Quantifiers Data type predicates (lists, trees, …)

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10.8.2006 Daniel Kroening 11 int *p, x, y; int main() { int z; y=z; p=&y; x=*p; assert(x==z); } cbmc test.c –cvc –outfile test Example

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10.8.2006 Daniel Kroening 12 p0: [# object: INT, offset: BITVECTOR(32) #] = (# object:=0, offset:=0bin00000000000000000000000000000000 #); x0: BITVECTOR(32) = 0bin00000000000000000000000000000000; y0: BITVECTOR(32) = 0bin00000000000000000000000000000000; z1: BITVECTOR(32); z0: BITVECTOR(32); y1: BITVECTOR(32) = z0; p1: [# object: INT, offset: BITVECTOR(32) #] = (# object:=3, offset:=0bin00000000000000000000000000000000 #); x1: BITVECTOR(32) = y1; l1: BOOLEAN; ASSERT l1 (x1=z0); ASSERT (NOT l1); QUERY FALSE; Download me! We have ~300 MB of benchmark files available Soon: SMT-Lib format

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10.8.2006 Daniel Kroening 13 Program Analysis: Abstraction P ROGRAM A NALYSIS E NGINE Progra m C ONSTRAINT S OLVER VCs Model W IDENING T Simplify, Zapato, Cogent, CPLEX, … Pre-, Post-, Proof-based, … SLAM, …

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10.8.2006 Daniel Kroening 14 Existing Tools Implement Fragments of linear arithmetic, Maybe arrays, maybe pointers Sometimes float

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10.8.2006 Daniel Kroening 15 Extending the Assertion Logic P ROGRAM A NALYSIS E NGINE Progra m C ONSTRAINT S OLVER VCCs Model W IDENING T Linear Arithmetic, Arrays, Float, …

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10.8.2006 Daniel Kroening 16 Existing Tools Biggest challenge for mass-market: dynamic data structures Fix with choice of assertion logic, e.g., Reynolds Separation Logic E.g., add separating conjunction and predicates for linked list

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10.8.2006 Daniel Kroening 17 Separation Logic A logic for heap data structures NOT the same as the fragment of linear arithmetic called difference logic Due to Reynolds/OHearn

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10.8.2006 Daniel Kroening 18 Separation Logic.. Payload next pointer ….. … Main problem: Need to specify that all heap cells are disjoint

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10.8.2006 Daniel Kroening 19 Separation Logic In general, one needs to express constraints that a data structure does not share cells with any other data structure Key idea: new logical operator P * Q Separating Conjunction

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10.8.2006 Daniel Kroening 20 Separation Logic Semantics of expressions defined over valuations of heaps (maps from addresses to values) Obvious meaning for StateHeapPointerValue

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10.8.2006 Daniel Kroening 21 Separation Logic Define disjoint heaps: Separating conjunction:

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10.8.2006 Daniel Kroening 22 Separation Logic: Lists Notation for sequences : empty sequence x ¢ : concatenation Define list:

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10.8.2006 Daniel Kroening 23 Extending the Assertion Logic P ROGRAM A NALYSIS E NGINE Progra m C ONSTRAINT S OLVER VCCs Model W IDENING T Linear Arithmetic, Arrays, Float, … +Separation Logic

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10.8.2006 Daniel Kroening 24 Who does the assertions? Manual annotations Automatic discovery Standard Template Library Data in containers is implicitly in separate heap cells typedef std::hash_map symbolst;... typedef std::vector nodest;

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10.8.2006 Daniel Kroening 25 Requirements for Constraint Solvers Constraint solver must support very rich logic Data types might even be application-specific But most queries are simple! Extending custom-made constraint solver is tedious

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10.8.2006 Daniel Kroening 26 Proposed Solution Assumption: we have a (partial) axiomatization of all logics Goal: high performance constraint solver 1 st step: define language for axioms

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10.8.2006 Daniel Kroening 27 Example: Equality Logic equality_transitivity: A "=" B, B "=" C -> A "=" C; emp: rewrite h"|=""emp" h"="["semp""**""semp"]; equality_commutativity: A "=" B B "=" A; equality: A "=" A; disequality: A "!=" B NOT A "=" B;

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10.8.2006 Daniel Kroening 28 Build a Compiler! 2 nd step: build a compiler Axioms g++ codegen C++ code Binary VCC SAT/UNSAT

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10.8.2006 Daniel Kroening 29 Multiple Theories Note that one can combine multiple theories Interfacing through arbitrary propositions, not just equalities Convexity requirement?

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10.8.2006 Daniel Kroening 30 What about OR? We could build case-splitting into the generated code However, we will never be able to implement Proper decision heuristics Non-chronological back-tracking Learning

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10.8.2006 Daniel Kroening 31 What about OR? Alternative: produce reduction to propositional logic Generate CNF, and pass formula to SAT solver The formula is unsatisfiable iff there exists a deduction that shows a contradiction

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10.8.2006 Daniel Kroening 32 What about OR? 3 nd step: add SAT solver Axioms g++ codegen C++ code Binary VCC CNF SAT Solver This is the eager version – lazy version straight-forward.

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10.8.2006 Daniel Kroening 33 What about OR? emp: rewrite h"|=""emp" h"="["semp""**""semp"]; 1.Maintain truth value with each fact: 2.Set new facts to unknown 3.Assign a literal to each fact that has truth value unknown 4.For each deduction step, generate constraint

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10.8.2006 Daniel Kroening 34 Separation Logic disjoint_not_self: h != emp -> not [h "# h]; not: h "|=" ["!" P] not [h "|=" P]; and: h "|=" [P "^" Q] h "|=" P, h "|=" Q; conditional: h "|=" [P "?" Q ":" R] (h "|=" P -> h "|=" Q), (h "|=" "!" P -> h "|=" R);

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10.8.2006 Daniel Kroening 35 Separation Logic emp: rewrite h"|=""emp" h"="["semp""**""semp"]; star: h "|=" [P "*" Q] NEW h0 "|=" P, NEW h1 "|=" Q, h "=" [NEW h0 "**" NEW h1], NEW h0 "#" NEW h1;

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10.8.2006 Daniel Kroening 36 Obtaining Invariants Again, could be custom-made Instead: inspect proofs of failed refutation-attempts Paper available on doing this for bit-vectors E.g., for constructing interpolants

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10.8.2006 Daniel Kroening 37 Conclusion Generic constraint solver with propositional SAT as backend Especially for complicated logics Extensions of logic are easy All case-splitting is pushed into propositional SAT solver

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10.8.2006 Daniel Kroening 38 Cross-Advertising TACAS: this can be used for –quantification over predicates CAV: Predicate abstraction for deep loops PDPAR: Completeness How to tell for sure that no proof exists?

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