26,864 research outputs found
Automated analysis of feature models: Quo vadis?
Feature models have been used since the 90's to describe software product lines as a way of reusing common parts in a family of software systems. In 2010, a systematic literature review was published summarizing the advances and settling the basis of the area of Automated Analysis of Feature Models (AAFM). From then on, different studies have applied the AAFM in different domains. In this paper, we provide an overview of the evolution of this field since 2010 by performing a systematic mapping study considering 423 primary sources. We found six different variability facets where the AAFM is being applied that define the tendencies: product configuration and derivation; testing and evolution; reverse engineering; multi-model variability-analysis; variability modelling and variability-intensive systems. We also confirmed that there is a lack of industrial evidence in most of the cases. Finally, we present where and when the papers have been published and who are the authors and institutions that are contributing to the field. We observed that the maturity is proven by the increment in the number of journals published along the years as well as the diversity of conferences and workshops where papers are published. We also suggest some synergies with other areas such as cloud or mobile computing among others that can motivate further research in the future.Ministerio de Economía y Competitividad TIN2015-70560-RJunta de Andalucía TIC-186
Adventures in Invariant Theory
We provide an introduction to enumerating and constructing invariants of
group representations via character methods. The problem is contextualised via
two case studies arising from our recent work: entanglement measures, for
characterising the structure of state spaces for composite quantum systems; and
Markov invariants, a robust alternative to parameter-estimation intensive
methods of statistical inference in molecular phylogenetics.Comment: 12 pp, includes supplementary discussion of example
Noisy continuous--opinion dynamics
We study the Deffuant et al. model for continuous--opinion dynamics under the
influence of noise. In the original version of this model, individuals meet in
random pairwise encounters after which they compromise or not depending of a
confidence parameter. Free will is introduced in the form of noisy
perturbations: individuals are given the opportunity to change their opinion,
with a given probability, to a randomly selected opinion inside the whole
opinion space. We derive the master equation of this process. One of the main
effects of noise is to induce an order-disorder transition. In the disordered
state the opinion distribution tends to be uniform, while for the ordered state
a set of well defined opinion groups are formed, although with some opinion
spread inside them. Using a linear stability analysis we can derive approximate
conditions for the transition between opinion groups and the disordered state.
The master equation analysis is compared with direct Monte-Carlo simulations.
We find that the master equation and the Monte-Carlo simulations do not always
agree due to finite-size induced fluctuations that we analyze in some detail
The role of noise and initial conditions in the asymptotic solution of a bounded confidence, continuous-opinion model
We study a model for continuous-opinion dynamics under bounded confidence. In
particular, we analyze the importance of the initial distribution of opinions
in determining the asymptotic configuration. Thus, we sketch the structure of
attractors of the dynamical system, by means of the numerical computation of
the time evolution of the agents density. We show that, for a given bound of
confidence, a consensus can be encouraged or prevented by certain initial
conditions. Furthermore, a noisy perturbation is added to the system with the
purpose of modeling the free will of the agents. As a consequence, the
importance of the initial condition is partially replaced by that of the
statistical distribution of the noise. Nevertheless, we still find evidence of
the influence of the initial state upon the final configuration for a short
range of the bound of confidence parameter
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