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A partial evaluation methodology for optimizing rewrite theories incrementally.

María Alpuente1, Demis Ballis2, Santiago Escobar1

  • 1VRAIN (Valencian Research Institute for Artificial Intelligence), Universitat Politècnica de València, Camino de Vera s/n, 46020 Valencia, Spain.

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Summary

This study introduces a partial evaluation (PE) method to optimize computer science rewrite theories for concurrent and nondeterministic systems. The technique ensures optimized code while preserving essential system properties and semantic equivalence.

Keywords:
Algebraic specificationCode optimizationConcurrent and non-deterministic system modelingNarrowing-based partial evaluationRewriting logic, MaudeSymbolic reasoning

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Area of Science:

  • Computer Science
  • Software Engineering
  • Formal Methods

Background:

  • Partial evaluation (PE) is a code optimization technique.
  • Rewrite theories are used to model concurrent and nondeterministic systems.
  • Optimizing these theories can be computationally intensive.

Purpose of the Study:

  • To present a novel partial evaluation (PE) methodology for optimizing rewrite theories.
  • To enable the specialization of a broad class of rewrite theories, including those modeling concurrent and nondeterministic systems.
  • To ensure that the optimization process preserves executability and semantic equivalence.

Main Methods:

  • Developed an automatic program optimization technique for rewrite theories using PE.
  • Incorporated several PE criteria to support the specialization of diverse rewrite theories.
  • Introduced an incremental partial evaluation modality for modular specialization.
  • Ensured preservation of executability theory requirements and semantic equivalence.

Main Results:

  • The proposed PE methodology offers an automatic optimization technique for rewrite theories.
  • The method supports the specialization of a wide range of rewrite theories.
  • Incremental PE allows for encapsulated specialization components and progressive refinements.
  • The PE transformation preserves executability and semantic equivalence under mild conditions.

Conclusions:

  • The presented PE methodology provides an effective approach for optimizing rewrite theories.
  • This technique enhances the efficiency of systems modeled by rewrite theories.
  • The approach is robust, maintaining crucial theoretical properties post-optimization.