feature modeling

The automated analysis of feature models is recognized as one of the key challenges for automated software de- velopment in the context of Software Product Lines (SPL). However, after years of research only a few ad-hoc propos- als have been presented in such area and the tool support demanded by the SPL community is still insufficient. In pre- vious work we showed how the selection of a logic repre- sentation and a solver to handle analysis on feature models can have a remarkable impact in the performance of the analysis process. In this paper we present a first imple- mentation of FAMA (FeAture Model Analyser). FAMA is a framework for the automated analysis of feature models in- tegrating some of the most commonly used logic represen- tations and solvers proposed in the literature. To the best o f our knowledge, FAMA is the first tool integrating different solvers for the automated analyses of feature models.

Software product line (SPL) approaches [1-3] aim at improving the productivity and quality of software development by enabling the management of common and variable features of a system family. A system family is defined as a set of programs that shares common functionalities ...

The authors describe work in feature modeling at the Helsinki University of Technology. Described are three experimental software systems dealing with parametric design of mechanical parts, modeling of mechanical assemblies, and generative process planning of prismatic parts for three-axis milling. The authors conclude that the synthesized features and feature taxonomy form a good basis for linking manufacturing information with design

Feature modeling is commonly used to capture the commonalities and variabilities of systems in a domain during Domain Analysis. The output of feature modeling will be some reusable assets (components, patterns, domainspecific language, etc.) to be fed into the application engineering phase for ultimate software products. But current practice lacks an automatic approach for seamless generation of reusable assets from feature models. This paper presents an algorithm for generating sets of instance descriptions (feature instances) from feature models of a domain and applies this algorithm in creating a Generic Feature Modeling Environment for automating Feature-

Service Oriented Architecture (SOA) has emerged as a model for distributed software development that promotes flexible deployment and reuse. Software product lines (SPL) promote reusable application development for product families. Service oriented systems change to respond to changing clients’ requirements. As they change, service oriented systems can be modeled as service families similar to the SPL concept. Some SPL development techniques rely on feature models to describe the commonality and variability of member applications. We use SPL feature modeling techniques to model the variability of service families. In this paper, we introduce a platform independent approach to model SOA variability based on feature modeling. We develop a UML meta-model to describe features. Then, we describe SOA variability scenarios using the newly released OMG standard SoaML. Finally, we develop a meta-model that maps features into SoaML. We believe that such an approach facilitates variability ma...

Being simplified representations of reality, simulation models can never be perfect and their results are always somewhat uncertain. That is why quantification of model uncertainty is important during interpretation of simulation results in decision making process. Uncertainty describes deviations of simulated ecosystem's characteristics from known or observed values. Several sources contribute to such deviations including those associated with main model components such as forcing functions, mathematical formulae, parameters and universal constants and intrinsic model features. Model uncertainty can be evaluated based on its linear estimate under the assumption that all sources of uncertainty are independent. Traditional approaches to investigating model uncertainty consider individual sources whose contribution to the uncertainty can be quantified for a given task. Although the result is incomplete it helps to improve the understanding of the model and increase the confidence ...

Feature-based model templates have been proposed as a technique for modeling software product lines. We describe a set of tools supporting the technique, namely a feature model editor and feature configurator, and a model-template editor, processor, and verifier.

Logos sometimes also known as trademark have high importance in today's marketing world. Products, companies and different gaming leagues are often recognized by their respective logos. In this paper, an implementation system for logo detection and recognition in video stream is presented. Feature set using SIFT (Scale Invariant Feature Transform) key-points is created for each query logo and the video frame being processed. The system uses a concept of bidirectional or two-way matching of features. Model fitting ...

Abstract Feature Models are popular tools for describing software product lines. Analysis of feature models has traditionally focused on consistency checking (yielding a yes/no answer) and product selection assistance, interactive or offline. In this paper, we describe a novel approach to identify the most critical decisions in product selection/configuration by taking advantage of a large pool of randomly generated, generally inconsistent, product variants. Range Ranking, a data mining technique, is utilized to single out the most critical design ...

A key aspect for effective variability modeling of Software Product Lines (SPL) is to harmonize the need to achieve separation of concerns with the need to satisfy consistency of requirements and constraints. Techniques for variability modeling such as feature models used together with use scenarios help to achieve separation of stakeholders' concerns but ensuring their joint consistency is largely unsupported. Therefore, inconsistent assumptions about system's expected use scenarios and the way in which they vary according to the ...

The increasing demand on developing Software Product Lines (SPL) has given a lot of interest to software engineering researchers in improving and also replacing, current methods and techniques applied to clasical sofware sys-tems development. In this paper, we introduce our first ideas within our proposal on improving the decision making while SPL Product Plan Managing. The key points in our pro-posal are originality and viability. We do not know any other proposal dealing with the same problem so far, and our first impressions guide us to predict a high viability.

Increasingly, Smart Homes should dynamically reconfigure their services at run-time in response to changing conditions in the user actions, and in the surrounding physical environment. Considering the high heterogeneity of technologies and user requirements involved in Smart Homes, these systems become difficult to adjust to the specific user needs. This paper introduces an approach to build selfconfiguring Smart Homes using

To provide efficient services to end-user it is essential to manage variability among services. Feature modeling is an important approach to manage variability and commonalities of a system in product line. Feature models are composed of feature diagrams. Service feature diagrams (an extended form of feature diagrams) introduced some new notations to classical feature diagrams. Service feature diagrams provide selection rights for variable features. In our previous work, we introduced cardinalities for the selection of features from a service feature diagram which we call cardinality-based service feature diagrams (CSFD). In this paper, we provide semantics to CSFDs. These semantics are backed by the formal calculus of Linear Logic. We provide rules to interpret CSFDs into linear logical formula. Our results show that the linear formulas of CSFDs give the same results as expected from the CSFDs. Keywords feature modelling; service feature diagrams; software product line; variability and similarity management; cardinality-based service feature diagrams.