Although Boolean satisfiability (abbreviated as SAT) is a sub-field of constraint programming (CP), the former states and solves problems as a black-box approach, whereas the latter aims at being tunable and programmable. Although many researches bridging SAT and CP have been provided, surprisingly, only few researchers have compared the SAT and CP approaches on a particular problem. This paper studies how to solve the all-interval series problem through both approaches. We will show that by using a state-of-theart SAT solver and an appropriate SAT encoding the SAT approach obtains a significantly higher performance over the CP approach. Furthermore, we also provide the state-of-theart result for several all-interval series instances.

In this paper, we introduce a new method, called EWAT + , for finding discords in time series databases. The proposed method takes full advantages of WAT, the discord discovery algorithm proposed by Fu et al., with major improvements based on new discord measure functions which help to set up a range of alternative good orderings for the outer loop of the discord discovery algorithm. In addition, we employ a branch-and-bound search mechanism on augmented trie that is carried out in the inner loop of the algorithm. Our experiments show that EWAT + is highly effective in terms of running time.

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