K-fold cross-validation is a widely used tool for assessing classifier performance. The reproducibility crisis faced by artificial intelligence partly results from the irreproducibility of reported k-fold cross-validation-based performance scores. Recently, we introduced numerical techniques to test the consistency of claimed performance scores and experimental setups. In a crucial use case, the method relies on the combinatorial enumeration of all k-fold configurations, for which we proposed an algorithm in the binary classification case.

A Dung argumentation framework (AF) is a pair (A,R): A is a set of abstract arguments and R ⊆ A×A is a binary relation, so-called the attack relation, for capturing the conflicting arguments. Labeling based algorithms for enumerating extensions (i.e. sets of acceptable arguments) have been set out such that arguments (i.e. elements of A) are the only subject for labeling. In this paper we present implemented algorithms for listing extensions by labeling attacks (i.e. elements of R) along with arguments. Specifically, these algorithms are concerned with enumerating all extensions of an AF under a number of argumentation semantics: preferred, stable, complete, semi stable, stage, ideal and grounded. Our algorithms have impact, in particular, on enumerating extensions of AF-extended models that allow attacks on attacks. To demonstrate this impact, we instantiate our algorithms for an example of such models: namely argumentation frameworks with recursive attacks (AFRA), thereby we end up with unified algorithms that enumerate extensions of any AF/AFRA.

In this paper, we address the problem of enumerating all models of a Boolean formula in conjunctive normal form (CNF). We propose an extension of CDCL-based SAT solvers to deal with this fundamental problem. Then, we provide an experimental evaluation of our proposed SAT model enumeration algorithms on both satisfiable SAT instances taken from the last SAT challenge and on instances from the SAT-based encoding of sequence mining problems.