aliasanalysisdriven

Aliasanalysisdriven is a design approach in compiler technology in which optimizations and analyses are guided directly by the results of alias analysis. Alias analysis determines whether two pointers or memory references may refer to the same memory location. An aliasanalysisdriven workflow uses these determinations to constrain or permit transformations, with correctness guaranteed by the underlying alias information.

Key aspects include precision versus performance trade-offs, and the use of various alias analyses such as flow-insensitive, flow-sensitive, context-insensitive, intraprocedural and interprocedural analyses. The approach informs optimizations such as reorderings of memory operations, elimination of redundant loads and stores, scalar replacement of aggregates, and more aggressive vectorization when aliasing is unlikely. It also supports interprocedural optimizations by resolving potential aliasing across function boundaries.

In practice, aliasanalysisdriven strategies are integral to many modern compilers. The concept underpins common optimization passes in systems like LLVM and GCC, even if the exact term is not always used. Transformations driven by alias information may be inhibited by uncertain results to preserve correctness, and the analysis itself is typically an approximation. The term captures a design philosophy rather than a single tool, emphasizing that safe and effective optimization depends on reliable alias information.