Beyond the Worst-Case Analysis of Algorithms (Introduction)
Abstract
One of the primary goals of the mathematical analysis of algorithms is to provide guidance about which algorithm is the "best" for solving a given computational problem. Worst-case analysis summarizes the performance profile of an algorithm by its worst performance on any input of a given size, implicitly advocating for the algorithm with the best-possible worst-case performance. Strong worst-case guarantees are the holy grail of algorithm design, providing an application-agnostic certification of an algorithm's robustly good performance. However, for many fundamental problems and performance measures, such guarantees are impossible and a more nuanced analysis approach is called for. This chapter surveys several alternatives to worst-case analysis that are discussed in detail later in the book.
Cite
@article{arxiv.2007.13241,
title = {Beyond the Worst-Case Analysis of Algorithms (Introduction)},
author = {Tim Roughgarden},
journal= {arXiv preprint arXiv:2007.13241},
year = {2020}
}
Comments
Chapter 1 of the book Beyond the Worst-Case Analysis of Algorithms, edited by Tim Roughgarden and published by Cambridge University Press (2020)