English

Automating Sized Type Inference for Complexity Analysis (Technical Report)

Logic in Computer Science 2017-06-29 v1 Computational Complexity

Abstract

This paper introduces a new methodology for the complexity analysis of higher-order functional programs, which is based on three ingredients: a powerful type system for size analysis and a sound type inference procedure for it, a ticking monadic transformation, and 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 the choice of adopting an abstract index language and index polymorphism at higher ranks. A prototype implementation is available.

Keywords

Cite

@article{arxiv.1706.09169,
  title  = {Automating Sized Type Inference for Complexity Analysis (Technical Report)},
  author = {Martin Avanzini and Ugo Dal Lago},
  journal= {arXiv preprint arXiv:1706.09169},
  year   = {2017}
}

Comments

Technical report of http://dx.doi.org/10.1145/3110287

R2 v1 2026-06-22T20:31:54.984Z