Constraint answer set programming or CASP, for short, is a hybrid approach in automated reasoningputting together the advances of distinct research areas such as answer set programming,constraint processing, and satisfiability modulo theories. CASP demonstrates promising results,including the development of a multitude of solvers: acsolver, clingcon, ezcsp, idp, inca,dingo, mingo, aspmt2smt, clingol,dl, and ezsmt. It opens new horizons for declarativeprogramming applications such as solving complex train scheduling problems. Systems designedto find solutions to constraint answer set programs can be grouped according to their constructioninto, what we call, integrational or translational approaches. The focus of this paper is anoverview of the key ingredients of the design of constraint answer set solvers drawing distinctionsand parallels between integrational and translational approaches. The paper also providesa glimpse at the kind of programs its users develop by utilizing a CASP encoding of TravelingSalesman problem for illustration. In addition, we place the CASP technology on the mapamong its automated reasoning peers as well as discuss future possibilities for the developmentof CASP.
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