  The k-sat problem is a prototypical constraint satisfaction problem. There
are many algorithms to study k-sat problem, BP algorithm is famous one of them.
But BP algorithm does not converge when $\alpha$(constraint density)is bigger
than some threshold value. In this paper we use CCCP (Concave Convex Procedure)
algorithm to study 3-sat problem and we get better results than BP algorithm
that CCCP algorithm still converges when BP algorithm does not converge. Our
work almost builds on recent results by Yuille \cite{Yuille2002} who apply the
CCCP algorithm to Bethe and Kikuchi free energies and obtained two algorithms
on 2D and 3D spin glasses. Our implementation of CCCP algorithm on 3-sat
problem is some different from his implementation and we have some different
views about CCCP algorithm's some properties. Some difference of these maybe
because of CCCP algorithm have different properties and implementation process
on different problem and some others of these are related to the CCCP algorithm
itself. Our work indicates that CCCP algorithm has more learning and inference
applications.
