Automating Sized Type Inference for Complexity Analysis (Technical Report)
Martin Avanzini, Ugo Dal Lago · arXiv (Cornell University) · 2017
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.