Debugging Answer-Set Programs with Ouroboros – Extending the SeaLion Plugin

Artificial intelligence (AI) approaches to problem-solving and decision-making are becoming more and more complex, leading to a decrease in the understandability of solutions. The European Union’s new General Data Protection Regulation tries to tackle this problem by stipulating a “right to explanation” for decisions made by AI systems. One of the AI paradigms that may be affected by this new regulation is answer set programming (ASP). Thanks to the emergence of efficient solvers, ASP has recently been used for problem-solving in a variety of domains, including medicine, cryptography, and biology. To ensure the successful application of ASP as a problem-solving paradigm in the future, explanations of ASP solutions are crucial. In this survey, we give an overview of approaches that provide an answer to the question ofwhyan answer set is a solution to a given problem, notably off-line justifications, causal graphs, argumentative explanations, and why-not provenance, and highlight their similarities and differences. Moreover, we review methods explaining why a set of literals isnotan answer set or why no solution exists at all.

Section: The Ouroboros System -Debugging Non-ground Programsmentioning

confidence: 99%

Answering the “why” in answer set programming – A survey of explanation approaches

Fandinno¹,

Schulz²

2019

“…The approach has later been extended from propositional to disjunctive logic programs with constraints, integer arithmetic, comparison predicates and strong negation (Oetsch et al 2010a) and also to programs with cardinality constraints (Polleres et al 2013). It has been implemented in the Ouroboros plugin of SeaLion (Frühstück et al 2013). Moreover, Shchekotykhin (2015) developed a method on top of the meta-programming approaches (Gebser et al 2008;Oetsch et al 2010a) that poses questions to the user in order to find a desired problem diagnosis while keeping the amount of required interaction low.…”

Section: Related Workmentioning

confidence: 99%

“…Due to the fully declarative semantics of ASP, it can be quite tedious to detect an error in an answer-set program. In recent years, debugging in ASP has received some attention (Brain and De Vos 2005;Syrjänen 2006;Brain et al 2007b;Pührer 2007;Gebser et al 2008;Gebser et al 2009;Pontelli et al 2009;Oetsch et al 2010a;Oetsch et al 2010b;Oetsch et al 2012b;Frühstück et al 2013;Polleres et al 2013;Shchekotykhin 2015). These previous works are important contributions towards ASP development support, however current approaches come with limitations to their practical applicability.…”

Section: Introductionmentioning

confidence: 99%

Stepwise debugging of answer-set programs

Oetsch¹,

Pührer²,

Tompits³

2017

Self Cite

We introduce astepping methodologyfor answer-set programming (ASP) that allows for debugging answer-set programs and is based on the stepwise application of rules. Similar to debugging in imperative languages, where the behaviour of a program is observed during a step-by-step execution, stepping for ASP allows for observing the effects that rule applications have in the computation of an answer set. While the approach is inspired from debugging in imperative programming, it is conceptually different to stepping in other paradigms due to non-determinism and declarativity that are inherent to ASP. In particular, unlike statements in an imperative program that are executed following a strict control flow, there is no predetermined order in which to consider rules in ASP during a computation. In our approach, the user is free to decide which rule to consider active in the next step following his or her intuition. This way, one can focus on interesting parts of the debugging search space. Bugs are detected during stepping by revealing differences between the actual semantics of the program and the expectations of the user. As a solid formal basis for stepping, we develop a framework of computations for answer-set programs. For fully supporting different solver languages, we build our framework on an abstract ASP language that is sufficiently general to capture different solver languages. To this end, we make use of abstract constraints as an established abstraction for popular language constructs such as aggregates. Stepping has been implemented inSeaLion, an integrated development environment for ASP. We illustrate stepping using an example scenario and discuss the stepping plugin ofSeaLion. Moreover, we elaborate on methodological aspects and the embedding of stepping in the ASP development process.

“…The technique is intuitive and similar in spirit as stepwise debugging in imperative languages but also respects the declarative nature of the answer-set semantics. Another debugging approach Polleres et al 2013) has recently been realised as a SeaLion plugin (Frühstück et al 2013) called Ouroboros. It tackles the question why a given interpretation is not an answer set.…”

Section: Introductionmentioning

confidence: 99%

SeaLion: An eclipse-based IDE for answer-set programming with advanced debugging support

Busoniu

Oetsch

Pührer

et al. 2013

Self Cite

In this paper, we present SeaLion, an integrated development environment (IDE) for answer-set programming (ASP).SeaLionprovides source-code editors for the languages ofGringoandDLVand offers popular amenities like syntax highlighting, syntax checking, code completion, visual program outline, and refactoring functionality. The tool has been realised in the context of a research project whose goal is the development of techniques to support the practical coding process of answer-set programs. In this respect,SeaLionis the first IDE for ASP that provides debugging features that work for real-world answer-set programs and supports the rich languages of modern answer-set solvers. Indeed,SeaLionimplements a stepping-based debugging approach that allows the developer to quickly track down programming errors by simply following his or her intuitions on the intended semantics. Besides that,SeaLionsupports ASP development using model-driven engineering techniques including domain modelling with extended UML class diagrams and visualisation of answer sets in corresponding instance diagrams. Moreover, customised visualisation as well as visual editing of answer sets is realised by the Kara plugin ofSeaLion. Further implemented features are a documentation generator based on the Lana annotation language, support for external solvers, and interoperability with external tools.SeaLioncomes as a plugin of the popular Eclipse platform and provides interfaces for future extensions of the IDE.