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CMSC 430 Introduction to Compilers Fall 2018 Data Flow Analysis Applications and Implementations Data Flow Analysis A framework for proving facts about programs Reasons about lots of little facts Little or no interaction between


  1. CMSC 430 Introduction to Compilers Fall 2018 Data Flow Analysis Applications and Implementations

  2. Data Flow Analysis • A framework for proving facts about programs • Reasons about lots of little facts • Little or no interaction between facts ■ Works best on properties about how program computes • Based on all paths through program ■ Including infeasible paths • Operates on control-flow graphs, typically 2

  3. Space of Data Flow Analyses May Must Reaching Available Forward definitions expressions Live Very busy Backward variables expressions • Most data flow analyses can be classified this way ■ A few don’t fit: bidirectional analysis • Lots of literature on data flow analysis 3

  4. 
 Applications: Reaching Defs. • Constant propagation : if all definitions of a given variable’s use are the same constant value, just assign the constant directly. 
 • Loop invariant code motion : if an expression is computed in a loop, but all of the components are defined outside the loop, the code can move. 4

  5. 
 Applications: Liveness • Register allocation : variables that are not live in a given basic block (or subgraph) do not need to be in registers. More on this later. 
 • Dead code elimination : variables that are assigned but not live after the assignment don’t need to be computed at all. 5

  6. Applications: Available Exprs. • Common sub-expression elimination: create a new variable containing the result of an expression. Replace subsequent uses of the expression with a read from the variable. 6

  7. Applications: Very Busy Exprs. • Code motion , e.g., move the computation of an expression to before a loop or branch. • If the same expression will be computed on every branch of a conditional, or every time through the loop, it can be pre-computed. t = a - b if (a < b) { if (a < b) { x = a - b 
 x = t 
 } else { 
 } else { 
 y = a - b 
 y = t 
 } } 7

  8. Implementations • Optimizing compilers implement data-flow analysis 
 • GCC: https://www.airs.com/dnovillo/200711-GCC-Internals/200711-GCC- ■ Internals-4-cfg-cg-df.pdf https://github.com/gcc-mirror/gcc/blob/master/gcc/df-core.c ■ https://github.com/gcc-mirror/gcc/blob/master/gcc/df-problems.c ■ • Clang: https://clang.llvm.org/doxygen/LiveVariables_8cpp_source.html ■ https://github.com/llvm-mirror/clang/blob/master/lib/Analysis/LiveVariables.cpp ■ https://github.com/llvm-mirror/clang/blob/master/lib/Analysis/UninitializedValues.cpp ■ 8

  9. Implementations (cont.) • Static analysis and bug-finding tools also use DFA 
 • Haskell package for LLVM: 
 http://hackage.haskell.org/package/llvm- analysis-0.3.0/docs/LLVM-Analysis-Dataflow.html • C Intermediate Language (CIL) ■ https://github.com/cil-project/cil 
 http://cil-project.github.io/cil/doc/html/cil/ ■ Written in OCaml! ■ Stable but no longer directly maintained ■ Used in Frama-C: http://frama-c.com/ 9

  10. Using CIL on Grace $ ssh grace.umd.edu 
 $ source /afs/glue.umd.edu/class/fall2018/cmsc/430/0201/public/.opam/opam-init/init.csh 
 $ git clone https://github.com/cil-project/cil 
 $ cd cil 
 $ ./configure && make $ ./bin/cilly —help | less $ ./bin/cilly \ —-save-temps \ 
 —-doLiveness \ --live_func=main \ 
 -—live_debug \ 
 /afs/glue.umd.edu/class/fall2018/cmsc/430/0201/public/src/ex1/ex1.c 10

  11. ex1.c int main(int argc, char *argv[]) { int x, y, z, w, a; x = 10; w = 20; a = 100; y = x + 3; z = y + w; w = 42; while (z < a) { z = z + y; a = a - 1; x = x + 1; if (z > 5) { y = x + 3; } } return x; } 11

  12. main() CFG 1 x = 10 w = 20 1: 2: x(int ),y(int ),z(int ),a(int ), a = 100 3: x(int ),y(int ),z(int ),a(int ), y = x + 3 4: x(int ), 5: x(int ),y(int ),z(int ),a(int ), z = y + w 6: x(int ),y(int ),z(int ),a(int ), w = 42 7: x(int ),z(int ),a(int ), 8: x(int ), 2 loop 3 z < a z = z + y 4 5 break a = a - 1 x = x + 1 6 8 z > 5 return x 7 y = x + 3 12

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