Debugging for Model Expansion

Wittocx, Johan; Vlaeminck, Hanne; Denecker, Marc

doi:10.1007/978-3-642-02846-5_26

Cited by 12 publications

(13 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, the authors provide an implementation that is based on computing a graph that reflects the execution of a query. Wittocx et al (2009) show how a calculus can be used for debugging first-order theories with inductive definitions (Denecker 2000;Denecker and Ternovska 2008) in the context of model expansion problems, i.e., problems of finding models of a given theory that expand some given interpretation. The idea is to trace the proof of inconsistency of such an unsatisfiable model expansion problem.…”

Section: Related Workmentioning

confidence: 99%

“…The previous meta-programming-based debugging technique (Pührer 2007;Gebser et al 2008) and follow-up works (Oetsch et al 2010a;Polleres et al 2013) deal with a single intended but non-actual answer set of the debugged program. In the approach of Wittocx et al (2009), the user can specify a class of intended semantic structures that are not preferred models of the theory at hand (corresponding to actual answer sets of the program to be debugged in ASP terminology). Syrjänen's diagnosis technique (Syrjänen 2006) is limited to the setting when a program has no answer set at all.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Stepwise debugging of answer-set programs

Oetsch¹,

Pührer²,

Tompits³

2017

Theory and Practice of Logic Programming

View full text Add to dashboard 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.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Stepwise debugging of answer-set programs

Oetsch¹,

Pührer²,

Tompits³

2017

Theory and Practice of Logic Programming

View full text Add to dashboard Cite

show abstract

“…Implementations of Definition 4.15 have been described in (Lynce and Silva 2004) and (Zhang et al 2006). In our experiment, we have an implementation of Definition 4.14 (Wittocx et al 2009), where we do however do not calculate the entire set of subset minimal theories. We only calculate one, which gives one explanation of the inconsistency.…”

Section: Subtask 7: Explanationmentioning

confidence: 99%

The KB paradigm and its application to interactive configuration

Hertum

Dasseville

Janssens

et al. 2016

Theory and Practice of Logic Programming

Self Cite

View full text Add to dashboard Cite

The knowledge base paradigm aims to express domain knowledge in a rich formal language, and to use this domain knowledge as a knowledge base to solve various problems and tasks that arise in the domain by applying multiple forms of inference. As such, the paradigm applies a strict separation of concerns between information and problem solving. In this paper, we analyze the principles and feasibility of the knowledge base paradigm in the context of an important class of applications: interactive configuration problems. In interactive configuration problems, a configuration of interrelated objects under constraints is searched, where the system assists the user in reaching an intended configuration. It is widely recognized in industry that good software solutions for these problems are very difficult to develop. We investigate such problems from the perspective of the KB paradigm. We show that multiple functionalities in this domain can be achieved by applying different forms of logical inferences on a formal specification of the configuration domain. We report on a proof of concept of this approach in a real-life application with a banking company. To appear in Theory and Practice of Logic Programming (TPLP).Comment: To appear in Theory and Practice of Logic Programming (TPLP

show abstract

“…In [Wittocx et al 2009] a model expansion algorithm is described based on the aforementioned approximation method. This algorithm has the advantage that it can be traced.…”

Section: Explaining Errorsmentioning

confidence: 99%

A logical framework for configuration software

Vlaeminck

Vennekens

Denecker

2009

Proceedings of the 11th ACM SIGPLAN Conference on Principles and Practice of Declarative Programming

Self Cite

View full text Add to dashboard Cite

There are many reasons why software can be hard to implement. For important classes of applications, the main source of complexity is the domain knowledge that is involved. One such class is that of configuration software, which serves to assist a user in making choices in accordance with certain constraints. For instance, consider an application that helps students compose a study program that complies with all relevant university regulations. The reason why this may be difficult to implement is that these regulations can get quite complicated, making them hard to handle, at least for imperative programming methods. A better approach might be to follow the paradigm of a knowledge base system: explicitly represent the domain knowledge in a declarative way, and implement the behavior of the application by performing various logical inference methods on it. Doing this well, however, requires that a number of different components be got right. Most importantly, we need an expressive and purely declarative knowledge representation language, together with a set of useful inference methods. In this paper, we present a framework for implementing this kind of software, based on a rich extension of first-order logic.

show abstract

Debugging for Model Expansion

Cited by 12 publications

References 14 publications

Stepwise debugging of answer-set programs

Stepwise debugging of answer-set programs

The KB paradigm and its application to interactive configuration

A logical framework for configuration software

Contact Info

Product

Resources

About