Inferring Lower Runtime Bounds for Integer Programs
Abstract
We present a technique to infer lower bounds on the worst-case runtime complexity of integer programs, where in contrast to earlier work, our approach is not restricted to tail-recursion. Our technique constructs symbolic representations of program executions using a framework for iterative, under-approximating program simplification. The core of this simplification is a method for (under-approximating) program acceleration based on recurrence solving and a variation of ranking functions. Afterwards, we deduce asymptotic lower bounds from the resulting simplified programs using a special-purpose calculus and an SMT encoding. We implemented our technique in our tool LoAT and show that it infers non-trivial lower bounds for a large class of examples.
Cite
@article{arxiv.1911.01077,
title = {Inferring Lower Runtime Bounds for Integer Programs},
author = {Florian Frohn and Matthias Naaf and Marc Brockschmidt and Jürgen Giesl},
journal= {arXiv preprint arXiv:1911.01077},
year = {2020}
}