  Answer set programming is a declarative programming paradigm oriented towards
difficult combinatorial search problems. A fundamental task in answer set
programming is to compute stable models, i.e., solutions of logic programs.
Answer set solvers are the programs that perform this task. The problem of
deciding whether a disjunctive program has a stable model is
$\Sigma^P_2$-complete. The high complexity of reasoning within disjunctive
logic programming is responsible for few solvers capable of dealing with such
programs, namely DLV, GnT, Cmodels, CLASP and WASP. In this paper we show that
transition systems introduced by Nieuwenhuis, Oliveras, and Tinelli to model
and analyze satisfiability solvers can be adapted for disjunctive answer set
solvers. Transition systems give a unifying perspective and bring clarity in
the description and comparison of solvers. They can be effectively used for
analyzing, comparing and proving correctness of search algorithms as well as
inspiring new ideas in the design of disjunctive answer set solvers. In this
light, we introduce a general template, which accounts for major techniques
implemented in disjunctive solvers. We then illustrate how this general
template captures solvers DLV, GnT and Cmodels. We also show how this framework
provides a convenient tool for designing new solving algorithms by means of
combinations of techniques employed in different solvers.
