Pieces for Harpsichord

Aldrich, Putnam; Roux, G.; Fuller, Albert

doi:10.2307/893241

Cited by 1 publication

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“…Forward reasoning is o en ineffective for reasoning about these analyses or proving their soundness. Standard presentations of dataflow analysis therefore typically focus on forward analyses, with backward analyses introduced later as a kind of dual of forward analyses [3,4].…”

Section: Introductionmentioning

confidence: 99%

Dataflow Analysis With Prophecy and History Variables

Rinard,

Gadient

2020

Preprint

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Leveraging concepts from state machine refinement proofs, we use prophecy variables, which predict information about the future program execution, to enable forward reasoning for backward dataflow analyses. Drawing prophecy and history variables (concepts from the dynamic execution of the program) from the same la ice as the static program analysis results, we require the analysis results to satisfy both the dataflow equations and the transition relations in the operational semantics of underlying programming language. is approach eliminates explicit abstraction and concretization functions and promotes a more direct connection between the analysis and program executions, with the connection taking the form of a bisimulation relation between concrete executions and an augmented operational semantics over the analysis results. We present several classical dataflow analyses with this approach (live variables, very busy expressions, defined variables, and reaching definitions) along with proofs that highlight how this approach can enable more streamlined reasoning. To the best of our knowledge, we are the first to use prophecy variables for dataflow analysis.

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Section: Introductionmentioning

confidence: 99%