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Control-Flow Refinement by Partial Evaluation, and its Application to Termination and Cost Analysis

Published online by Cambridge University Press:  20 September 2019

JESÚS J. DOMÉNECH
Affiliation:
Universidad Complutense de Madrid, Spain (e-mail: jdomenech@ucm.es)
JOHN P. GALLAGHER
Affiliation:
Roskilde University, Denmark and IMDEA Software Institute, Spain (e-mail: jpg@ruc.dk)
SAMIR GENAIM
Affiliation:
Universidad Complutense de Madrid, Spain (e-mail: sgenaim@ucm.es)

Abstract

Control-flow refinement refers to program transformations whose purpose is to make implicit control-flow explicit, and is used in the context of program analysis to increase precision. Several techniques have been suggested for different programming models, typically tailored to improving precision for a particular analysis. In this paper we explore the use of partial evaluation of Horn clauses as a general-purpose technique for control-flow refinement for integer transitions systems. These are control-flow graphs where edges are annotated with linear constraints describing transitions between corresponding nodes, and they are used in many program analysis tools. Using partial evaluation for control-flow refinement has the clear advantage over other approaches in that soundness follows from the general properties of partial evaluation; in particular, properties such as termination and complexity are preserved. We use a partial evaluation algorithm incorporating property-based abstraction, and show how the right choice of properties allows us to prove termination and to infer complexity of challenging programs that cannot be handled by state-of-the-art tools. We report on the integration of the technique in a termination analyzer, and its use as a preprocessing step for several cost analyzers.

Type
Original Article
Copyright
© Cambridge University Press 2019 

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Footnotes

*

This work was funded partially by the Spanish MICINN/FEDER, UE project RTI2018-094403-BC31, the MINECO project TIN2015-69175-C4-2-R, the CM project S2018/TCS-4314 and by the predoctoral UCM grant CT27/16-CT28/16.

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