scholarly journals Linear algorithms for recognizing and parsing superpositional graphs

2011 ◽  
Vol 24 (3) ◽  
pp. 325-339 ◽  
Author(s):  
Ahti Peder ◽  
Härmel Nestra ◽  
Jaan Raik ◽  
Mati Tombak ◽  
Raimund Ubar

Structurally synthesized binary decision diagrams (SSBDD) are a special type of BDDs that are generated by superposition according to the structure of propositional formula. Fast algorithms for simulation, diagnostic reasoning and test generation running on SSBDDs exploit their specific properties. Hence the correctness of SSBDDs should be checked before using those algorithms. The problem of recognizing SSBDDs can be reduced to the problem of recognizing their skeleton, namely superpositional graphs, which are a proper subclass of binary graphs. This paper presents linear time algorithms for testing whether a binary graph is a superpositional graph and for restoring the history of its generating process.

Author(s):  
Masaaki Nishino ◽  
Norihito Yasuda ◽  
Kengo Nakamura

Exact cover refers to the problem of finding subfamily F of a given family of sets S whose universe is D, where F forms a partition of D. Knuth’s Algorithm DLX is a state-of-the-art method for solving exact cover problems. Since DLX’s running time depends on the cardinality of input S, it can be slow if S is large. Our proposal can improve DLX by exploiting a novel data structure, DanceDD, which extends the zero-suppressed binary decision diagram (ZDD) by adding links to enable efficient modifications of the data structure. With DanceDD, we can represent S in a compressed way and perform search in linear time with the size of the structure by using link operations. The experimental results show that our method is an order of magnitude faster when the problem is highly compressed.


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