Sparse conditional constant propagation

In computer science, sparse conditional constant propagation (SCCP) is an optimization frequently applied in compilers after conversion to static single assignment form (SSA). It propagates constants, which is the calculation of static values which can be calculated at compile time. Moreover, it can find more constant values, and thus more opportunities for improvement, than separately applying dead code elimination and constant propagation in any order or any number of repetitions.^[1]^[2]

The algorithm operates by performing abstract interpretation of the code in SSA form. During abstract interpretation, it typically uses a flat lattice of constants for values and a global environment mapping SSA variables to values in this lattice. The crux of the algorithm comes in how it handles the interpretation of branch instructions. When encountered, the condition for a branch is evaluated as best possible given the precision of the abstract values bound to variables in the condition. It may be the case that the values are perfectly precise (neither top nor bottom) and hence, abstract execution can decide in which direction to branch. If the values are not constant, or a variable in the condition is undefined, then both branch directions must be taken to remain conservative.

Upon completion of the abstract interpretation, instructions which were never reached are marked as dead code. SSA variables found to have constant values may then be inlined at (propagated to) their point of use.^{[example needed]}

Notes

^ Wegman, Mark N. and Zadeck, F. Kenneth. "Constant Propagation with Conditional Branches." ACM Transactions on Programming Languages and Systems, 13(2), April 1991, pages 181-210.
^ Click, Clifford and Cooper, Keith. "Combining Analyses, Combining Optimizations", ACM Transactions on Programming Languages and Systems, 17(2), March 1995, pages 181-196

References

Cooper, Keith D. and Torczon, Linda. Engineering a Compiler. Morgan Kaufmann. 2005.

[1] Wegman, Mark N. and Zadeck, F. Kenneth. "Constant Propagation with Conditional Branches." ACM Transactions on Programming Languages and Systems, 13(2), April 1991, pages 181-210.

[2] Click, Clifford and Cooper, Keith. "Combining Analyses, Combining Optimizations", ACM Transactions on Programming Languages and Systems, 17(2), March 1995, pages 181-196

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v t e Compiler optimizations
Basic block	Peephole optimization Local value numbering
Loop	Automatic parallelization Automatic vectorization Induction variable Loop fusion Loop-invariant code motion Loop inversion Loop interchange Loop nest optimization Loop splitting Loop unrolling Loop unswitching Software pipelining Strength reduction
Data-flow analysis	Available expression Common subexpression elimination Constant folding Dead store elimination Induction variable recognition and elimination Live-variable analysis Upwards exposed uses Use-define chain Reaching definitions
SSA-based	Global value numbering Sparse conditional constant propagation
Code generation	Instruction scheduling Instruction selection Register allocation Rematerialization
Functional	Deforestation Tail-call elimination
Global	Interprocedural optimization
Other	Bounds-checking elimination Compile-time function execution Dead-code elimination Expression templates Inline expansion Jump threading Partial evaluation Profile-guided optimization
Static analysis	Alias analysis Array-access analysis Control-flow analysis Data-flow analysis Dependence analysis Escape analysis Pointer analysis Shape analysis Value range analysis