1,246 research outputs found
Improved Answer-Set Programming Encodings for Abstract Argumentation
The design of efficient solutions for abstract argumentation problems is a
crucial step towards advanced argumentation systems. One of the most prominent
approaches in the literature is to use Answer-Set Programming (ASP) for this
endeavor. In this paper, we present new encodings for three prominent
argumentation semantics using the concept of conditional literals in
disjunctions as provided by the ASP-system clingo. Our new encodings are not
only more succinct than previous versions, but also outperform them on standard
benchmarks.Comment: To appear in Theory and Practice of Logic Programming (TPLP),
Proceedings of ICLP 201
Analysis of Feature Models Using Alloy: A Survey
Feature Models (FMs) are a mechanism to model variability among a family of
closely related software products, i.e. a software product line (SPL). Analysis
of FMs using formal methods can reveal defects in the specification such as
inconsistencies that cause the product line to have no valid products. A
popular framework used in research for FM analysis is Alloy, a light-weight
formal modeling notation equipped with an efficient model finder. Several works
in the literature have proposed different strategies to encode and analyze FMs
using Alloy. However, there is little discussion on the relative merits of each
proposal, making it difficult to select the most suitable encoding for a
specific analysis need. In this paper, we describe and compare those strategies
according to various criteria such as the expressivity of the FM notation or
the efficiency of the analysis. This survey is the first comparative study of
research targeted towards using Alloy for FM analysis. This review aims to
identify all the best practices on the use of Alloy, as a part of a framework
for the automated extraction and analysis of rich FMs from natural language
requirement specifications.Comment: In Proceedings FMSPLE 2016, arXiv:1603.0857
CONJURE: automatic generation of constraint models from problem specifications
Funding: Engineering and Physical Sciences Research Council (EP/V027182/1, EP/P015638/1), Royal Society (URF/R/180015).When solving a combinatorial problem, the formulation or model of the problem is critical tothe efficiency of the solver. Automating the modelling process has long been of interest because of the expertise and time required to produce an effective model of a given problem. We describe a method to automatically produce constraint models from a problem specification written in the abstract constraint specification language Essence. Our approach is to incrementally refine the specification into a concrete model by applying a chosen refinement rule at each step. Any nontrivial specification may be refined in multiple ways, creating a space of models to choose from. The handling of symmetries is a particularly important aspect of automated modelling. Many combinatorial optimisation problems contain symmetry, which can lead to redundant search. If a partial assignment is shown to be invalid, we are wasting time if we ever consider a symmetric equivalent of it. A particularly important class of symmetries are those introduced by the constraint modelling process: modelling symmetries. We show how modelling symmetries may be broken automatically as they enter a model during refinement, obviating the need for an expensive symmetry detection step following model formulation. Our approach is implemented in a system called Conjure. We compare the models producedby Conjure to constraint models from the literature that are known to be effective. Our empirical results confirm that Conjure can reproduce successfully the kernels of the constraint models of 42 benchmark problems found in the literature.Publisher PDFPeer reviewe
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