902 research outputs found
AuRUS: explaining the validation of UML/OCL conceptual schemas
The validation and the verification of conceptual schemas have attracted a lot of interest during the last years, and several tools have been developed to automate this process as much as possible. This is achieved, in general, by assessing whether the schema satisfies different kinds of desirable properties which ensure that the schema is correct. In this paper we describe AuRUS, a tool we have developed to analyze UML/OCL conceptual schemas and to explain their (in)correctness. When a property is satisfied, AuRUS provides a sample instantiation of the schema showing a particular situation where the property holds. When it is not, AuRUS provides an explanation for such unsatisfiability, i.e., a set of integrity constraints which is in contradiction with the property.Peer ReviewedPostprint (author’s final draft
A cognitive exploration of the “non-visual” nature of geometric proofs
Why are Geometric Proofs (Usually) “Non-Visual”? We asked this question as
a way to explore the similarities and differences between diagrams and text (visual
thinking versus language thinking). Traditional text-based proofs are considered
(by many to be) more rigorous than diagrams alone. In this paper we focus on
human perceptual-cognitive characteristics that may encourage textual modes for
proofs because of the ergonomic affordances of text relative to diagrams. We suggest
that visual-spatial perception of physical objects, where an object is perceived
with greater acuity through foveal vision rather than peripheral vision, is similar
to attention navigating a conceptual visual-spatial structure. We suggest that attention
has foveal-like and peripheral-like characteristics and that textual modes
appeal to what we refer to here as foveal-focal attention, an extension of prior
work in focused attention
A cookbook for temporal conceptual data modelling with description logic
We design temporal description logics suitable for reasoning about temporal conceptual data models and investigate their computational complexity. Our formalisms are based on DL-Lite logics with three types of concept inclusions (ranging from atomic concept inclusions and disjointness to the full Booleans), as well as cardinality constraints and role inclusions. In the temporal dimension, they capture future and past temporal operators on concepts, flexible and rigid roles, the operators `always' and `some time' on roles, data assertions for particular moments of time and global concept inclusions. The logics are interpreted over the Cartesian products of object domains and the flow of time (Z,<), satisfying the constant domain assumption. We prove that the most expressive of our temporal description logics (which can capture lifespan cardinalities and either qualitative or quantitative evolution constraints) turn out to be undecidable. However, by omitting some of the temporal operators on concepts/roles or by restricting the form of concept inclusions we obtain logics whose complexity ranges between PSpace and NLogSpace. These positive results were obtained by reduction to various clausal fragments of propositional temporal logic, which opens a way to employ propositional or first-order temporal provers for reasoning about temporal data models
Automated analysis of feature models 20 years later: a literature review
Software product line engineering is about producing a set of related products that share more commonalities than
variabilities. Feature models are widely used for variability and commonality management in software product
lines. Feature models are information models where a set of products are represented as a set of features in a
single model. The automated analysis of feature models deals with the computer–aided extraction of information
from feature models. The literature on this topic has contributed with a set of operations, techniques, tools and
empirical results which have not been surveyed until now. This paper provides a comprehensive literature review
on the automated analysis of feature models 20 years after of their invention. This paper contributes by bringing
together previously-disparate streams of work to help shed light on this thriving area. We also present a conceptual
framework to understand the different proposals as well as categorise future contributions. We finally discuss the
different studies and propose some challenges to be faced in the future.CICYT TIN2009-07366CICYT TIN2006-00472Junta de Andalucía TIC-253
Clafer: Lightweight Modeling of Structure, Behaviour, and Variability
Embedded software is growing fast in size and complexity, leading to intimate
mixture of complex architectures and complex control. Consequently, software
specification requires modeling both structures and behaviour of systems.
Unfortunately, existing languages do not integrate these aspects well, usually
prioritizing one of them. It is common to develop a separate language for each
of these facets. In this paper, we contribute Clafer: a small language that
attempts to tackle this challenge. It combines rich structural modeling with
state of the art behavioural formalisms. We are not aware of any other modeling
language that seamlessly combines these facets common to system and software
modeling. We show how Clafer, in a single unified syntax and semantics, allows
capturing feature models (variability), component models, discrete control
models (automata) and variability encompassing all these aspects. The language
is built on top of first order logic with quantifiers over basic entities (for
modeling structures) combined with linear temporal logic (for modeling
behaviour). On top of this semantic foundation we build a simple but expressive
syntax, enriched with carefully selected syntactic expansions that cover
hierarchical modeling, associations, automata, scenarios, and Dwyer's property
patterns. We evaluate Clafer using a power window case study, and comparing it
against other notations that substantially overlap with its scope (SysML, AADL,
Temporal OCL and Live Sequence Charts), discussing benefits and perils of using
a single notation for the purpose
Derivation and consistency checking of models in early software product line engineering
Dissertação para obtenção do Grau de Doutor em
Engenharia InformáticaSoftware Product Line Engineering (SPLE) should offer the ability to express the derivation of product-specific assets, while checking for their consistency. The derivation of product-specific assets is possible using general-purpose programming languages in combination with techniques
such as conditional compilation and code generation. On the other hand, consistency checking can be achieved through consistency rules in the form of architectural and design guidelines, programming conventions and well-formedness rules. Current approaches present four shortcomings: (1)
focus on code derivation only, (2) ignore consistency problems between the variability model and other complementary specification models used in early SPLE, (3) force developers to learn new, difficult to master, languages to encode the derivation of assets, and (4) offer no tool support.
This dissertation presents solutions that contribute to tackle these four shortcomings. These solutions are integrated in the approach Derivation and Consistency Checking of models in early SPLE (DCC4SPL) and its corresponding tool support.
The two main components of our approach are the Variability Modelling Language for Requirements(VML4RE), a domain-specific language and derivation infrastructure, and the Variability Consistency Checker (VCC), a verification technique and tool. We validate DCC4SPL demonstrating that it is appropriate to find inconsistencies in early SPL model-based specifications and to specify the derivation of product-specific models.European Project AMPLE, contract IST-33710; Fundação para a Ciência e Tecnologia - SFRH/BD/46194/2008
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