• Journal of KIISE:Software and Applications
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• v.35 no.2
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• pp.81-90
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• 2008

BCC(Boolean Cardinality Constraint) is to select one boolean variable from n different variables. It is widely used in many areas including software engineering. Thus, many efficient encoding techniques of BCC into CNF have been studied extensively In this paper we analyze some representative encodings with respect to flexibility as well as efficiency. In addition we use a visualization tool to draw the CNF clauses generated from each encodings. Visualizing the clauses exposes a hidden structure in encodings and makes to compare each encodings on the structure level, which is one of the prominent achievement in our work compared to other works. And we apply our analysis on the pigeon-hole problems to have confidence. In our experimental settings, the commander encoding shows the best performance.

• The KIPS Transactions:PartD
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• v.15D no.6
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• pp.777-784
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• 2008

Recently in the field of model checking, to overcome the state explosion problem, the method of using a SAT-solver is mainly researched. To use a SAT-solver, the system to be verified is translated into CNF and the Boolean cardinality constraint is widely used in translating the system into CNF. In BCC it is dealt with set of boolean variables, but there is no translating method of the sequence among Boolean variables. In this paper, we propose methods for translating the problem, which is extracting a subsequence with length k from a sequence of Boolean variables, into CNF formulas. Through experimental results, we show that our method is more efficient than using only BCC.

• Journal of KIISE:Software and Applications
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• v.35 no.11
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• pp.661-670
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• 2008

In some applications of software engineering such as the verification of software model or embedded program, SAT solver is used. To practical use a SAT solver, a problem is encoded to a CNF formula, but because the formula has lower expressiveness than software models or source codes, optimal CNF encoding is required. In this paper, we propose optimal encoding techniques for the problem of "Selecting adjacent $k{\leq}n$ among n objects," Through experimental results we show the proposed constraint is efficient and correct to solve Japanese puzzle. As we know, this paper is the first study about CNF encoding for adjacency in BCC.