30,812 research outputs found
Incremental Consistency Checking in Delta-oriented UML-Models for Automation Systems
Automation systems exist in many variants and may evolve over time in order
to deal with different environment contexts or to fulfill changing customer
requirements. This induces an increased complexity during design-time as well
as tedious maintenance efforts. We already proposed a multi-perspective
modeling approach to improve the development of such systems. It operates on
different levels of abstraction by using well-known UML-models with activity,
composite structure and state chart models. Each perspective was enriched with
delta modeling to manage variability and evolution. As an extension, we now
focus on the development of an efficient consistency checking method at several
levels to ensure valid variants of the automation system. Consistency checking
must be provided for each perspective in isolation, in-between the perspectives
as well as after the application of a delta.Comment: In Proceedings FMSPLE 2016, arXiv:1603.0857
Evaluation of Variability Concepts for Simulink in the Automotive Domain
Modeling variability in Matlab/Simulink becomes more and more important. We
took the two variability modeling concepts already included in Matlab/Simulink
and our own one and evaluated them to find out which one is suited best for
modeling variability in the automotive domain. We conducted a controlled
experiment with developers at Volkswagen AG to decide which concept is
preferred by developers and if their preference aligns with measurable
performance factors. We found out that all existing concepts are viable
approaches and that the delta approach is both the preferred concept as well as
the objectively most efficient one, which makes Delta-Simulink a good solution
to model variability in the automotive domain.Comment: 10 pages, 7 figures, 6 tables, Proceedings of 48th Hawaii
International Conference on System Sciences (HICSS), pp. 5373-5382, Kauai,
Hawaii, USA, IEEE Computer Society, 201
Synthesis of Attributed Feature Models From Product Descriptions: Foundations
Feature modeling is a widely used formalism to characterize a set of products
(also called configurations). As a manual elaboration is a long and arduous
task, numerous techniques have been proposed to reverse engineer feature models
from various kinds of artefacts. But none of them synthesize feature attributes
(or constraints over attributes) despite the practical relevance of attributes
for documenting the different values across a range of products. In this
report, we develop an algorithm for synthesizing attributed feature models
given a set of product descriptions. We present sound, complete, and
parametrizable techniques for computing all possible hierarchies, feature
groups, placements of feature attributes, domain values, and constraints. We
perform a complexity analysis w.r.t. number of features, attributes,
configurations, and domain size. We also evaluate the scalability of our
synthesis procedure using randomized configuration matrices. This report is a
first step that aims to describe the foundations for synthesizing attributed
feature models
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 EconomĂa y Competitividad TIN2015-70560-RJunta de AndalucĂa TIC-186
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