Synopsis
Unlocking faster code with proven data-flow techniques for program optimization.
This work presents general-purpose algorithms that power the SETL optimizer, helping compilers analyze and transform code for better performance.
The authors detail interval analysis and forward/backward data-flow methods designed to improve optimization across languages. The approach works with an intermediate program representation, including interprocedural and intraprocedural analyses, and supports code motion to remove redundant computations. While rooted in SETL, the techniques aim to be broadly applicable to many programming environments.
- How interval analysis identifies and collapses control-flow structures to streamline analysis
- Forward and backward data-flow strategies for bitvector-style properties like availability and liveness
- Interprocedural methods that respect call semantics and enable optimizations across procedures
- Code motion techniques that move computations to earlier points without changing semantics
Ideal for readers of formal optimization methods and compiler design who seek practical, scalable analysis techniques.
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