Electronic Proceedings in Theoretical Computer Science (Apr 2017)

Automated Sized-Type Inference and Complexity Analysis

  • Martin Avanzini,
  • Ugo Dal Lago

DOI
https://doi.org/10.4204/EPTCS.248.5
Journal volume & issue
Vol. 248, no. Proc. DICE-FOPARA 2017
pp. 7 – 16

Abstract

Read online

This paper introduces a new methodology for the complexity analysis of higher-order functional programs, which is based on three components: a powerful type system for size analysis and a sound type inference procedure for it, a ticking monadic transformation and a concrete tool for constraint solving. Noticeably, the presented methodology can be fully automated, and is able to analyse a series of examples which cannot be handled by most competitor methodologies. This is possible due to various key ingredients, and in particular an abstract index language and index polymorphism at higher ranks. A prototype implementation is available.