Type-Based Flow Analysis: From Polymorphic Subtyping to CFL-Reachability Jakob Rehof and Manuel Fähndrich Microsoft Research
Type-Based Program Analysis Common vocabulary Data access paths Function summary Context-sensitivity Directional flow Type-based Type structure ( ) Function type (->) Type instantiation, polymorphism ( ) Subtyping ( )
+CS -DI ( ,=) +CS +DI GOAL: Scaleable Flow Analysis of H.O. Programs w. Polymorphic Subtyping -CS +DI (=, ) +CS +DI ( , ) Precision and Cost -CS -DI (=,=) Type-based Higher-order Context-sensitive (CS) Directional (DI)
Outline Goals Problems and Results Current Flow Analysis w. + Our Solution Summary
Current Method ( ) Polymorphism by copying types ( ) Subtyping by constrained types ( + ) constraint copying
Problems w. Current Method Constraint copying is expensive (memory) Constraint simplification is hard Previous algorithm (Mossin) No on-demand algorithms (n = size of type-annotated program)
Results No constraint copying On-demand queries All flow in
Outline Goals Problems and Results Current Flow Analysis w. + Our Solution Summary
Current Flow Analysis w. + (Mossin) max(s,t) = if s<=t then t else s real * real -> real standard type
Current Flow Analysis w. + max(s:a,t:b) = (if s<=t then t else s) :c {a c, b c} => real:a * real:b -> real:c analysis type subtyping constraints flow label
Current Flow Analysis w. + max(s:a,t:b) = (if s<=t then t else s) :c {a c, b c} => real:a * real:b -> real:c
max(s:a,t:b) : {a c, b c} => real:a * real:b -> real:c max(x0,y0) max(x1,y1) Current Flow Analysis w. +
max(s:a,t:b) : {a c, b c} => real:a * real:b -> real:c max(x0:a0,y0:b0):c0 max(x1:a1,y1:b1):c1 {a0 c0,b0 c0}=>c0
max(s:a,t:b) : {a c, b c} => real:a * real:b -> real:c max(x0:a0,y0:b0):c0 max(x1:a1,y1:b1):c1 {a0 c0,b0 c0}=>c0 {a1 c1,b1 c1}=>c1 Current Flow Analysis w. +
with and
Without Subtyping: norm(x,y ) = let m = max(x,y) in scale(x,y,m) end; scale(z,w,n) = (z/n,w/n) max(s:a,t:a) = if s<=t then t else s real:a * real:a -> real:a :a’
Without Subtyping: norm(x:a’,y:a’) = let m = max(x,y) in scale(x,y,m) end; scale(z,w,n) = (z/n,w/n) max(s:a,t:a) = if s<=t then t else s real:a * real:a -> real:a
Outline Goals Problems and Results Current Flow Analysis w. + Our Solution Summary
Flow Analysis Overview Source Code Type Instantiation Graph Flow Graph A B Type Inference
Flow Analysis Overview Source Code Type Instantiation Graph Flow Graph A B Type Inference CFL- Reachability Polymorphic Subtyping
Eliminating constraint copies max(s:a,t:b) : {a c, b c} => real:a * real:b -> real:c max(x0:a0,y0:b0):c0 max(x1:a1,y1:b1):c1 {a0 c0, b0 c0} => real:a0 * real:b0 -> real:c0 {a1 c1, b1 c1} => real:a1 * real:b1 -> real:c1
1. Get a graph max(s:a,t:b) : real:a * real:b -> real:c max(x0:a0,y0:b0):c0 max(x1:a1,y1:b1):c1 real:a0 * real:b0 -> real:c0 real:a1 * real:b1 -> real:c1
2. Label instantiation sites max(s:a,t:b) : real:a * real:b -> real:c i: max(x0:a0,y0:b0):c0 j: max(x1:a1,y1:b1):c1 real:a0 * real:b0 -> real:c0 real:a1 * real:b1 -> real:c1
3. Represent substitutions max(s:a,t:b) : real:a * real:b -> real:c a a0 a a1 b b0 b b1 c c0 c c1 i: max(x0:a0,y0:b0):c0 j: max(x1:a1,y1:b1):c1 real:a0 * real:b0 -> real:c0 real:a1 * real:b1 -> real:c1
3.a. … as a graph max(s:a,t:b) : real:a * real:b -> real:c i: max(x0:a0,y0:b0):c0 j: max(x1:a1,y1:b1):c1 real:a0 * real:b0 -> real:c0 real:a1 * real:b1 -> real:c1 i i i
3.a. … as a graph max(s:a,t:b) : real:a * real:b -> real:c i: max(x0:a0,y0:b0):c0 j: max(x1:a1,y1:b1):c1 real:a0 * real:b0 -> real:c0 real:a1 * real:b1 -> real:c1 i i i j j j
4. Eliminate constraint copies ! max(s:a,t:b) : real:a * real:b -> real:c i: max(x0:a0,y0:b0):c0 j: max(x1:a1,y1:b1):c1 real:a0 * real:b0 -> real:c0 real:a1 * real:b1 -> real:c1 i i i j j j
? ? ? max(s:a,t:b) : real:a * real:b -> real:c i: max(x0:a0,y0:b0):c0 j: max(x1:a1,y1:b1):c1 real:a0 * real:b0 -> real:c0 real:a1 * real:b1 -> real:c1 i i i j j j
Type Theory to the Rescue ! Polarity (+,-) ->
5. Polarities (+,-) max(s:a,t:b) : real:a * real:b -> real:c i: max(x0:a0,y0:b0):c0 j: max(x1:a1,y1:b1):c1 real:a0 * real:b0 -> real:c0 real:a1 * real:b1 -> real:c1 i i i j j j
6. Reverse negative edges max(s:a,t:b) : real:a * real:b -> real:c i: max(x0:a0,y0:b0):c0 j: max(x1:a1,y1:b1):c1 real:a0 * real:b0 -> real:c0 real:a1 * real:b1 -> real:c1 i i i j j j
7. Recover flow max(s:a,t:b) : real:a * real:b -> real:c i: max(x0:a0,y0:b0):c0 j: max(x1:a1,y1:b1):c1 real:a0 * real:b0 -> real:c0 real:a1 * real:b1 -> real:c1 i i i j j j
7. Recover flow max(s:a,t:b) : real:a * real:b -> real:c i: max(x0:a0,y0:b0):c0 j: max(x1:a1,y1:b1):c1 real:a0 * real:b0 -> real:c0 real:a1 * real:b1 -> real:c1 i i i j j j
7. Recover flow max(s:a,t:b) : real:a * real:b -> real:c i: max(x0:a0,y0:b0):c0 j: max(x1:a1,y1:b1):c1 real:a0 * real:b0 -> real:c0 real:a1 * real:b1 -> real:c1 i i i j j j
8. Be careful ! max(s:a,t:b) : real:a * real:b -> real:c i: max(x0:a0,y0:b0):c0 j: max(x1:a1,y1:b1):c1 real:a0 * real:b0 -> real:c0 real:a1 * real:b1 -> real:c1 i i i j j j Spurious !
9. Do CFL-reachability max(s:a,t:b) : real:a * real:b -> real:c i: max(x0:a0,y0:b0):c0 j: max(x1:a1,y1:b1):c1 real:a0 * real:b0 -> real:c0 real:a1 * real:b1 -> real:c1 [i ]i [j ]j M [k M ]k d d CFG
Further Issues Polymorphic type structure Recursive type structure –context-sensitive data-dependence analysis is uncomputable [Reps 00] –our techniques require finite types –regular unbounded data types handled via finite approximations: recursive type expressions
One-level implementation GOLF analysis system for C by Manuvir Das (MSR) and Ben Liblit (Berkeley) Exhaustive points-to sets for MS Word 97, 1.4 Mloc, in 2 minutes
Outline Goals Problems and Results Current Flow Analysis w. + Our Solution Summary
Elimination of constraint copying Reformulation of polymorphic subtyping with instantiation constraints Transfer of CFL-reachability techniques to type-based flow analysis
Scaleable Program Analysis Project (MSR, spt ) +CS -DI ( ,=) -CS +DI (=, ) +CS +DI ( , ) -CS -DI (=,=) [ RF, POPL 01 ] [ Das, PLDI 00 ] [ FRD, PLDI 00 ] research.microsoft.com/spa
Summary Type-based flow analysis –all flow in, n = typed pgm size –context-sensitive (polymorphism) –directional (subtyping) –demand-driven algorithm –incorporates label-polymorphic recursion –works directly on H.O. programs –structured data of finite type –unbounded data structures via approx.
CFL Formulation S P N P M P | [ P | N M N | ] N | M [k M ]k | M M | d |
Type System e = let max(s:a,t:b) = … in (max(x0:a0,y0:b0), max(x1:a1,y1:b1)) end a a0, b b0, c c0, a a1, b b1, c c1 a cb ca cb c |-; ; e : c0*c1
Type System e = let max(s:a,t:b) = … in (max(x0:a0,y0:b0), max(x1:a1,y1:b1)) end a a0, b b0, c c0, a a1, b b1, c c1 a cb ca cb c |-; ; e : c0*c1 instantiation constraints subtyping constraints type environment