This paper presents a method to detect and recognize symmetries in Boolean functions. The idea is to use information theoretic measures of Boolean functions to detect sub-space of possible symmetric variables. Coupled with the new techniques of efficient estimations of information measures on Binary Decision Diagrams (BDDs) we obtain promised results in symmetries detection for large-scale functions.
@article{arxiv.cs/0207019,
title = {Information Measures in Detecting and Recognizing Symmetries},
author = {Denis V. Popel},
journal= {arXiv preprint arXiv:cs/0207019},
year = {2007}
}