Compressing Binary Decision Diagrams

TL;DR

The paper presents a new linear-time compression technique for Binary Decision Diagrams that significantly reduces their size when random access isn't needed, outperforming previous methods.

Contribution

A novel compression method for BDDs that achieves near-optimal size reduction with linear time complexity, surpassing existing techniques.

Findings

Compression reduces BDD size to 1-2 bits per node

Technique dominates previous methods on tested instances

Compression and decompression are linear in BDD size

Abstract

The paper introduces a new technique for compressing Binary Decision Diagrams in those cases where random access is not required. Using this technique, compression and decompression can be done in linear time in the size of the BDD and compression will in many cases reduce the size of the BDD to 1-2 bits per node. Empirical results for our compression technique are presented, including comparisons with previously introduced techniques, showing that the new technique dominate on all tested instances.