AMUSE a minimally-unsatisfiable subformula extractor

This paper describes a new algorithm for extracting unsatisfiable subformulas from a given unsatisfiable CNF formula. Such unsatisfiable "cores" can be very helpful in diagnosing the causes of infeasibility in large systems. Our algorithm is unique in that it adapts the "learning proc...

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Bibliographic Details
Published in:2004 41st Conference Design Automation pp. 518 - 523
Main Authors: Oh, Yoonna, Mneimneh, Maher N., Andraus, Zaher S., Sakallah, Karem A., Markov, Igor L.
Format: Conference Proceeding
Language:English
Published: New York, NY, USA ACM 07.06.2004
IEEE
Association for Computing Machinery
Series:ACM Conferences
Subjects:
Applied sciences
Automotive engineering
Boolean functions
Combinatorial mathematics
Computer bugs
Design. Technologies. Operation analysis. Testing
Electronic design automation and methodology
Electronics
Exact sciences and technology
Field programmable gate arrays
Hardware
Integrated circuits
Mathematics of computing > Discrete mathematics > Combinatorics > Combinatorial algorithms
Polynomials
Routing
Semiconductor electronics. Microelectronics. Optoelectronics. Solid state devices
Wires
diagnosis
boolean satisfiability (SAT)
minimally-unsatisfiable subformula (MUS)
conjunctive normal form (CNF)
Learning
Circuit design
Algorithm performance
Algorithm
Computer aided design
Large scale system
ISBN:1581138288, 9781581138283, 1511838288
ISSN:0738-100X
Online Access:Get full text
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Summary:This paper describes a new algorithm for extracting unsatisfiable subformulas from a given unsatisfiable CNF formula. Such unsatisfiable "cores" can be very helpful in diagnosing the causes of infeasibility in large systems. Our algorithm is unique in that it adapts the "learning process" of a modern SAT solver to identify unsatisfiable subformulas rather than search for satisfying assignments. Compared to existing approaches, this method can be viewed as a bottom-up core extraction procedure which can be very competitive when the core sizes are much smaller than the original formula size. Repeated runs of the algorithm with different branching orders yield different cores. We present experimental results on a suite of large automotive benchmarks showing the performance of the algorithm and highlighting its ability to locate not just one but several cores.
Bibliography:SourceType-Conference Papers & Proceedings-1
ObjectType-Conference Paper-1
content type line 25
ISBN:1581138288
9781581138283
1511838288
ISSN:0738-100X
DOI:10.1145/996566.996710