Skip to Main content Skip to Navigation
Conference papers

Uniform Random Expressions Lack Expressivity

Abstract : In this article, we question the relevance of uniform random models for algorithms that use expressions as inputs. Using a general framework to describe expressions, we prove that if there is a subexpression that is absorbing for a given operator, then, after repeatedly applying the induced simplification to a uniform random expression of size n, we obtain an equivalent expression of constant expected size. This proves that uniform random expressions lack expressivity, as soon as there is an absorbing pattern. For instance, (a + b) is absorbing for the union for regular expressions on {a, b}, hence random regular expressions can be drastically reduced using the induced simplification.
Document type :
Conference papers
Complete list of metadata
Contributor : Admin Upem Connect in order to contact the contributor
Submitted on : Thursday, February 18, 2021 - 4:54:36 PM
Last modification on : Saturday, January 15, 2022 - 3:58:40 AM
Long-term archiving on: : Wednesday, May 19, 2021 - 7:30:33 PM


Publisher files allowed on an open archive


Distributed under a Creative Commons Attribution 4.0 International License




Florent Koechlin, Cyril Nicaud, Pablo Rotondo. Uniform Random Expressions Lack Expressivity. MFCS 2019, Aug 2019, Aachen, Germany. pp.51:1-51:14, ⟨10.4230/LIPIcs.MFCS.2019.51⟩. ⟨hal-03145930⟩



Record views


Files downloads