Debugging ASP using ILP

Declarative programming allows the expression of properties of the desired solution(s), while the computational task is delegated to a general-purpose algorithm. The freedom from explicit controlis counter-balanced by the difficulty in working out what properties are missing or are incorrectly expressed, when the solutions do not meet expectations. This can be particularly problematic in thecase of answer set semantics, because the absence of a key constraint/rule could make the difference between none or thousands of answer sets, rather than the intended one (or handful). The debuggingtask then comprises adding or deleting conditions on the right hand sides of existing rules or, more far-reaching, adding or deleting whole rules. The contribution of this paper is to show how inductivelogic programming (ILP) along with examples of (un)desirable properties of answer sets can be used to revise the original program semi-automatically so that it satisfies the stated properties, in effectproviding debugging-by-example for programs under answer set semantics

Sketched Answer Set Programming

Answer Set Programming (ASP) is a powerful modeling formalism for combinatorial problems. However, writing ASP models is not trivial. We propose a novel method, called Sketched Answer Set Programming (SkASP), aiming at supporting the user in resolving this issue. The user writes an ASP program while marking uncertain parts open with question marks. In addition, the user provides a number of positive and negative examples of the desired program behaviour. The sketched model is rewritten into another ASP program, which is solved by traditional methods. As a result, the user obtains a functional and reusable ASP program modelling her problem. We evaluate our approach on 21 well known puzzles and combinatorial problems inspired by Karp's 21 NP-complete problems and demonstrate a use-case for a database application based on ASP.Comment: 15 pages, 11 figures; to appear in ICTAI 201