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Automated Soundness Proofs for Dataflow Analyses and Transformations via Local Rules. Sorin Lerner* Todd Millstein** Erika Rice* Craig Chambers* * University of Washington ** UCLA. [graduating this year!]. A traditional compiler. Compiler. Opt. Opt. Opt. Parser. Code Gen.
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Automated Soundness Proofs for Dataflow Analyses and Transformations via Local Rules Sorin Lerner* Todd Millstein** Erika Rice* Craig Chambers* * University of Washington ** UCLA [graduating this year!]
A traditional compiler Compiler Opt Opt Opt Parser Code Gen
Using a domain specific language Compiler DSL Opt DSL Opt DSL Opt Parser Code Gen
Using a domain specific language Compiler DSL Execution engine Parser Code Gen DSL Opt DSL Opt DSL Opt
Checking correctness automatically Compiler DSL Execution engine Parser Code Gen DSL Opt DSL Opt DSL Opt
DSL Opt DSL Opt DSL Opt Checker Checker Checker Checking correctness automatically Compiler DSL Execution engine Parser Code Gen
Compiler DSL Execution engine Parser Code Gen DSL Opt DSL Opt DSL Opt Checker Checker Checking correctness automatically Checker
Compiler DSL Execution engine Parser Code Gen DSL Opt DSL Opt Checker Checker Checking correctness automatically DSL Opt Checker
Checker Checker Checking correctness automatically DSL Opt
Checker Automatic Theorem Prover Checking correctness automatically DSL Opt Checker VCGen Verification Condition (VC)
Automatic Theorem Prover Checking correctness automatically DSL Opt Checker VCGen Verification Condition (VC)
DSL Opt VCGen opt- specific opt- independent Automatic Theorem Prover Checking correctness automatically Lemma: VC implies correctness Checker VC
Cobalt [PLDI 03] • The Cobalt DSL is an instantiation of this architecture • An opt written in Cobalt is a rewrite rule triggered by a declarative global condition over the CFG • Expressed and automatically proved the correctness of a variety of intraprocedural optimizations, including: • const prop and folding, branch folding, CSE, PRE, DAE, partial DAE
In this talk: the Rhodium DSL • Increased expressiveness • New model for expressing opts: local propagation rules with explicit dataflow facts • Heap summaries • Infinite analysis domains • Flow-sensitive and -insensitive • Intraprocedural and interprocedural • Some Rhodium opts not expressible in Cobalt: • Arithmetic invariant detection, integer range analysis, loop-induction-variable strength reduction, Andersen's may-point-to analysis with allocation-site summaries
Outline • Overview • Rhodium by example • Checking correctness automatically • Future work, related work and conclusion
c d a b a b c d c MustPointTo analysis a := &b c := a *c := d
mustPointTo(a, b) mustPointTo(a, b) mustPointTo(c, b) mustPointTo(c, d) c d a b a b c d c mustPointTo(c, d) MustPointTo info in Rhodium a := &b c := a *c := d
mustPointTo(a, b) mustPointTo(a, b) mustPointTo(a, b) mustPointTo(a, b) mustPointTo(c, b) mustPointTo(c, d) mustPointTo(c, b) mustPointTo(c, d) c c d d a a b b a a b b c c d d c c mustPointTo(c, d) mustPointTo(c, d) MustPointTo info in Rhodium a := &b a := &b c := a c := a *c := d *c := d
mustPointTo(a, b) mustPointTo(a, b) mustPointTo(c, b) mustPointTo(c, d) c d a b a b c d c mustPointTo(c, d) MustPointTo info in Rhodium define fact mustPointTo(X:Var,Y:Var) a := &b c := a *c := d
mustPointTo(a, b) mustPointTo(a, b) mustPointTo(c, d) mustPointTo(c, b) c d a b a b c d c mustPointTo(c, d) Propagating facts define fact mustPointTo(X:Var,Y:Var) a := &b c := a *c := d
mustPointTo(a, b) mustPointTo(c, b) c d a b a b c d c mustPointTo(c, d) Propagating facts define fact mustPointTo(X:Var,Y:Var) a := &b a := &b if currStmt = [X := &Y] then mustPointTo(X,Y)@out if currStmt = [X := &Y] then mustPointTo(X,Y)@out mustPointTo(a, b) mustPointTo(a, b) mustPointTo(c, d) c := a *c := d
mustPointTo(a, b) mustPointTo(a, b) mustPointTo(c, b) mustPointTo(c, d) c d a b a b c d c mustPointTo(c, d) Propagating facts define fact mustPointTo(X:Var,Y:Var) a := &b if currStmt = [X := &Y] then mustPointTo(X,Y)@out c := a *c := d
mustPointTo(a, b) mustPointTo(c, b) c d a b a b c d c Propagating facts define fact mustPointTo(X:Var,Y:Var) mustPointTo(c, d) mustPointTo(c, d) a := &b a := &b if currStmt = [X := &Y] then mustPointTo(X,Y)@out mustPointTo(a, b) if mustPointTo(X,Y)@in Æ currStmt = [Z := &W]Æ X Z then mustPointTo(X,Y)@out if mustPointTo(X,Y)@in Æ currStmt = [Z := &W]Æ X Z then mustPointTo(X,Y)@out mustPointTo(c, d) mustPointTo(c, d) c := a *c := d
c d a b a b c d c mustPointTo(c, d) Propagating facts define fact mustPointTo(X:Var,Y:Var) a := &b if currStmt = [X := &Y] then mustPointTo(X,Y)@out mustPointTo(a, b) mustPointTo(a, b) if mustPointTo(X,Y)@in Æ currStmt = [Z := &W]Æ X Z then mustPointTo(X,Y)@out mustPointTo(c, d) c := a c := a mustPointTo(a, b) mustPointTo(c, b) mustPointTo(c, b) if mustPointTo(X,Y)@inÆ currStmt = [Z := X] then mustPointTo(Z,Y)@out *c := d
mustPointTo(a, b) mustPointTo(a, b) mustPointTo(c, b) mustPointTo(c, d) c d a b a b c d c mustPointTo(c, d) Propagating facts define fact mustPointTo(X:Var,Y:Var) a := &b if currStmt = [X := &Y] then mustPointTo(X,Y)@out if mustPointTo(X,Y)@in Æ currStmt = [Z := &W]Æ X Z then mustPointTo(X,Y)@out c := a if mustPointTo(X,Y)@inÆ currStmt = [Z := X] then mustPointTo(Z,Y)@out *c := d
mustPointTo(a, b) mustPointTo(a, b) mustPointTo(c, d) mustPointTo(c, b) c d a b a b c d c if mustPointTo(X,Y)@inÆ currStmt = [Z := X] then mustPointTo(Z,Y)@out mustPointTo(c, d) Transformations define fact mustPointTo(X:Var,Y:Var) a := &b if currStmt = [X := &Y] then mustPointTo(X,Y)@out if mustPointTo(X,Y)@in Æ currStmt = [Z := &W]Æ X Z then mustPointTo(X,Y)@out c := a *c := d
mustPointTo(a, b) mustPointTo(c, d) c d a b a b c d c mustPointTo(c, d) Transformations define fact mustPointTo(X:Var,Y:Var) a := &b if mustPointTo(X,Y)@inÆ currStmt = [*X := Z] then transform to [Y := Z] c := a mustPointTo(a, b) mustPointTo(c, b) mustPointTo(c, b) *c := d *c := d b := d
Semantics of a Rhodium opt • Run all the propagations rules using optimistic iterative analysis starting with complete set of facts until the best fixed point is reached • Then run all transformation rules • For better precision, combine analyses and transformations using our previous composition framework [POPL 02]
More in Rhodium (see paper for details) • Mixing facts • Heap summaries • MayPointTo analysis via MustNotPointTo • Infinite domains • Flow-sensitive and -insensitive • Intraprocedural and interprocedural
Outline • Overview • Rhodium by example • Checking correctness automatically • Future work, related work and conclusion
Rhodium correctness checker Rhodium optimization Checker Lemma: VC ) correctness VCGen VC opt- independent Automatic theorem prover
Rhodium correctness checker Rhodium optimization define fact … if … then … if … then transform … Checker Lemma: VC ) correctness VCGen VC opt- independent Automatic theorem prover
IL semantics axioms Rhodium correctness checker Rhodium optimization define fact … if … then … if … then transform … Checker Lemma: VC ) correctness Lemma: Local VCs ) correctness VCGen Local VC Local VC opt- independent Automatic theorem prover
mustPointTo(X, Y) mustPointTo(Z, Y) Local correctness of prop. rules define fact mustPointTo(X:Var,Y:Var) if mustPointTo(X,Y)@in Æ currStmt = [Z := X] then mustPointTo(Z,Y)@out Z := X
define fact mustPointTo(X:Var,Y:Var) with meaning «X == &Y¬ if «X == &Y¬(in) Æ in out then «Z == &Y¬(out) Z := X X Z Y Y mustPointTo(X, Y) mustPointTo(Z, Y) ? Local correctness of prop. rules define fact mustPointTo(X:Var,Y:Var) Local VC sent to ATP: if mustPointTo(X,Y)@in Æ currStmt = [Z := X] then mustPointTo(Z,Y)@out in Z := X Z := X out
in in X X Y Y mustPointTo(X, Y) Local correctness of trans. rules define fact mustPointTo(X:Var,Y:Var) with meaning «X == &Y¬ Local VC sent to ATP: if mustPointTo(X,Y)@in Æ if «X == &Y¬(in) Æ *X := Z in out currStmt = [*X := Z] Y := Z in out then transform to [Y := Z] then *X := Z *X := Z Y := Z Y := Z out out ?
More on correctness (see paper for details) • Heap summaries • Separating profitability from correctness • Theorem stating soundness of the framework for creating interprocedural and flow-insensitive analyses
Outline • Overview • Rhodium by example • Checking correctness automatically • Future work, related work and conclusion
Current and future work • Backward optimizations • Infer rules from just the dataflow fact declarations and their meanings • Debugging • Efficient execution engine
Some related work • Proving correctness by hand • Abstract interpretation [Cousot and Cousot 77, 79] • Partial equivalence relations [Benton 04] • Temporal logic [Lacey et al. 02] • Proving correctness with interactive theorem prover • Using Coq proof assistant [Cachera et al. 04] • Testing correctness one compilation at a time • Translation validation [Pnueli et al. 98, Necula 00] • Credible compilation [Rinard 99] • Execution engines • Incremental execution of transformations [Sittampalam et al. 04] • Running opts specified with temporal logic [Steffen 91]
Conclusion • Local rules in Rhodium are more expressive than Cobalt’s global condition • The correctness checker found subtle bugs in our Rhodium opts • Good step towards pushing more of the burden of writing compilers on to the computer