Results 1 - 10
of
108
Formalizing cardinality-based feature models and their specialization
- Software Process: Improvement and Practice
, 2005
"... Abstract Feature modeling is an important approach to capture the commonalities and variabilities in system families and product lines. Cardinality-based feature modeling integrates a number of existing extensions of the original feature-modeling notation from Feature-Oriented Domain Analysis. Stage ..."
Abstract
-
Cited by 169 (18 self)
- Add to MetaCart
(Show Context)
Abstract Feature modeling is an important approach to capture the commonalities and variabilities in system families and product lines. Cardinality-based feature modeling integrates a number of existing extensions of the original feature-modeling notation from Feature-Oriented Domain Analysis. Staged configuration is a process that allows the incremental configuration of cardinality-based feature models. It can be achieved by performing a step-wise specialization of the feature model. In this paper, we argue that cardinality-based feature models can be interpreted as a special class of context-free grammars. We make this precise by specifying a translation from a feature model into a context-free grammar. Consequently, we provide a semantic interpretation for cardinalitybased feature models by assigning an appropriate semantics to the language recognized by the corresponding grammar. Finally, we give an account on how feature model specialization can be formalized as transformations on the grammar equivalent of feature models.
Staged configuration through specialization and multilevel configuration of feature models
- Software Process: Improvement and Practice
"... Abstract Feature modeling is a key technique for capturing commonalities and variabilities in system families and product lines. In this paper, we propose a cardinality-based notation for feature modeling, which integrates a number of existing extensions of previous approaches. We then introduce and ..."
Abstract
-
Cited by 141 (14 self)
- Add to MetaCart
(Show Context)
Abstract Feature modeling is a key technique for capturing commonalities and variabilities in system families and product lines. In this paper, we propose a cardinality-based notation for feature modeling, which integrates a number of existing extensions of previous approaches. We then introduce and motivate the novel concept of staged configuration. Staged configuration can be achieved by the stepwise specialization of feature models or by multi-level configuration, where the configuration choices available in each stage are defined by separate feature models. Staged configuration is important because in a realistic development process, different groups and different people make product configuration choices in different stages. Finally, we also discuss how multi-level configuration avoids a breakdown between the different abstraction levels of individual features. This problem, sometimes referred to as “analysis paralysis”, easily occurs in feature modeling because features can denote entities at arbitrary levels of abstractions within a system family. Key words: Software product lines, system families, domain analysis, software configuration 1
Cardinality-Based Feature Modeling and Constraints: A Progress Report
- OOPSLA'05
, 2005
"... Software factories have been proposed as a comprehensive and integrative approach to generative software development. Feature modeling has several applications in generative software development, including domain analysis, product-line scoping, and feature-based product specification. This paper rep ..."
Abstract
-
Cited by 75 (10 self)
- Add to MetaCart
Software factories have been proposed as a comprehensive and integrative approach to generative software development. Feature modeling has several applications in generative software development, including domain analysis, product-line scoping, and feature-based product specification. This paper reports on our recent progress in cardinalitybased feature modeling and its support for expressing additional constraints. We show that the Object-Constraint Language (OCL) can adequately capture such constraints. Furthermore, we identify a set of facilities based on constraint satisfaction that can be provided by feature modeling and feature-based configuration tools and present a prototype implementing some of these facilities. We report on our experience with the prototype and give directions for future work.
Overview of generative software development
- In Proceedings of Unconventional Programming Paradigms (UPP) 2004, 15-17 September, Mont Saint-Michel, France, Revised Papers
, 2004
"... Abstract. System family engineering seeks to exploit the commonalities among systems from a given problem domain while managing the variabilities among them in a systematic way. In system family engineering, new system variants can be rapidly created based on a set of reusable assets (such as a comm ..."
Abstract
-
Cited by 53 (4 self)
- Add to MetaCart
(Show Context)
Abstract. System family engineering seeks to exploit the commonalities among systems from a given problem domain while managing the variabilities among them in a systematic way. In system family engineering, new system variants can be rapidly created based on a set of reusable assets (such as a common architecture, components, models, etc.). Generative software development aims at modeling and implementing system families in such a way that a given system can be automatically generated from a specification written in one or more textual or graphical domainspecific languages. This paper gives an overview of the basic concepts and ideas of generative software development including DSLs, domain and application engineering, generative domain models, networks of domains, and technology projections. The paper also discusses the relationship of generative software development to other emerging areas such as Model Driven Development and Aspect-Oriented Software Development. 1
Automated Diagnosis of Product-Line Configuration Errors in Feature Models, in: SPLC
- IEEE Computer Society,
, 2008
"... ..."
(Show Context)
Using Constraint Programming to Reason on Feature Models
- IN THE SEVENTEENTH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING
, 2005
"... Feature models have been cited as one of the main contributions to model software product families. However, there is still a gap in product family engineering which is the automated reasoning on feature models. In this paper we describe how to reason on feature models using constraint programming. ..."
Abstract
-
Cited by 22 (5 self)
- Add to MetaCart
Feature models have been cited as one of the main contributions to model software product families. However, there is still a gap in product family engineering which is the automated reasoning on feature models. In this paper we describe how to reason on feature models using constraint programming. Although, there are a few attempts to reason on feature models there are two main drawbacks in these proposals: ## none of them associate parameters to features ### none of them use constraint programming as the reasoning base. Using constraint programming endows our proposal with a more powerful reasoning capacity and greater expressiveness than others.
Scalable Prediction of Non-functional Properties in Software Product Lines
"... Abstract—A software product line is a family of related software products, typically, generated from a set of common assets. Users can select features to derive a product that fulfills their needs. Often, users expect a product to have specific nonfunctional properties, such as a small footprint or ..."
Abstract
-
Cited by 22 (11 self)
- Add to MetaCart
Abstract—A software product line is a family of related software products, typically, generated from a set of common assets. Users can select features to derive a product that fulfills their needs. Often, users expect a product to have specific nonfunctional properties, such as a small footprint or a minimum response time. Because a product line can contain millions of products, it is usually not feasible to generate and measure nonfunctional properties for each possible product of a product line. Hence, we propose an approach to predict a product’s nonfunctional properties, based on the product’s feature selection. To this end, we generate and measure a small set of products, and by comparing the measurements, we approximate each feature’s non-functional properties. By aggregating the approximations of selected features, we predict the product’s properties. Our technique is independent of the implementation approach and language. We show how already little domain knowledge can improve predictions and discuss trade-offs regarding accuracy and the required number of measurements. Although our approach is in general applicable for quantifiable non-functional properties, we evaluate it for the non-functional property footprint. With nine case studies, we demonstrate that our approach usually predicts the footprint with an accuracy of 98 % and an accuracy of over 99 % if feature interactions are known. I.
Reasoning about feature models in higher-order logic
- Proceedings of the 11th International Software Product Line Conference, SPLC ’07. IEEE Computer Society
, 2007
"... A mechanically formalized feature modeling metamodel is presented. This theory is a generic higher-order formalization of a mathematical model synthesizing several feature modeling approaches found in the literature. This meta-model support not only a better understanding of the various approaches t ..."
Abstract
-
Cited by 19 (3 self)
- Add to MetaCart
A mechanically formalized feature modeling metamodel is presented. This theory is a generic higher-order formalization of a mathematical model synthesizing several feature modeling approaches found in the literature. This meta-model support not only a better understanding of the various approaches to feature modeling, but also supports reasoning about and within feature model approaches, feature models, and on feature trees and their configurations. 1
Extracting and Evolving Mobile Games Product Lines
- Proceedings of SPLC'05, LNCS 3714
, 2005
"... Abstract. For some organizations, the proactive approach to product lines may be inadequate due to prohibitively high investment and risks. As an alternative, the extractive and the reactive approaches are incremental, offering moderate costs and risks, and therefore sometimes may be more appropriat ..."
Abstract
-
Cited by 19 (8 self)
- Add to MetaCart
(Show Context)
Abstract. For some organizations, the proactive approach to product lines may be inadequate due to prohibitively high investment and risks. As an alternative, the extractive and the reactive approaches are incremental, offering moderate costs and risks, and therefore sometimes may be more appropriate. However, combining these two approaches demands a more detailed process at the implementation level. This paper presents a method for extracting a product line and evolving it, relying on a strategy that uses refactorings expressed in terms of simpler programming laws. The approach is evaluated with a case study in the domain of games for mobile devices, where variations are handled with aspect-oriented constructs. 1
Configuring features with stakeholder goals
- In ACM SAC RETrack
, 2008
"... Goal models are effective in capturing stakeholder needs at the time when features of the system-to-be have not yet been conceptualized. Relating goals to solution-oriented features gives rise to a requirement traceability problem. In this paper, we present a new model-driven extension to an Early R ..."
Abstract
-
Cited by 18 (5 self)
- Add to MetaCart
(Show Context)
Goal models are effective in capturing stakeholder needs at the time when features of the system-to-be have not yet been conceptualized. Relating goals to solution-oriented features gives rise to a requirement traceability problem. In this paper, we present a new model-driven extension to an Early Requirements Engineering tool (OpenOME) that generates an initial feature model of the systemto-be from stakeholder goals. Enabled by such generative mapping, configuration constraints among variability features can be obtained by reasoning about stakeholder goals.
