We study algorithms for computing stable models of logic programs and derive estimates on their worst-case performance that are asymptotically better than the trivial bound of $O(m 2^n)$, where $m$ is the size of an input program and $n$ is the number of its atoms. For instance, for programs whose clauses consist of at most two literals (counting the head) we design an algorithm to compute stable models that works in time $O(m\times 1.44225^n)$. We present similar results for several broader classes of programs. Finally, we study the applicability of the techniques developed in the paper to the analysis of the performance of smodels.

We propose an alternative way to represent graphs via OBDDs based on the observation that a partition of the graph nodes allows sharing among the employed OBDDs. In the second part of the paper we present a method to compute at the same time the quotient w.r.t. the maximum bisimulation and the OBDD representation of a given graph. The proposed computation is based on an OBDD-rewriting of the notion of Ackermann encoding of hereditarily finite sets into natural numbers.

We present a new approach to termination analysis of numerical computations in logic programs. Traditional approaches fail to analyse them due to non well-foundedness of the integers. We present a technique that allows overcoming these difficulties. Our approach is based on transforming a program in a way that allows integrating and extending techniques originally developed for analysis of numerical computations in the framework of query-mapping pairs with the well-known framework of acceptability. Such an integration not only contributes to the understanding of termination behaviour of numerical computations, but also allows us to perform a correct analysis of such computations automatically, by extending previous work on a constraint-based approach to termination. Finally, we discuss possible extensions of the technique, including incorporating general term orderings.