Using Multiple Feature Models to Design Applications for Mobile Phones

International audienceThe design of a mobile phone application is a tedious task according to its intrinsic variability. Software designers must take into account in their development process the versatility of available platforms (e.g., Android, iPhone). In addition to this, the variety of existing devices and their divergences (e.g., frontal camera, GPS) introduce another layer of com- plexity in the development process. These two dimensions can be formalized as Software Product Lines (SPL), inde- pendently defined. In this paper, we use a dedicated meta- model to bridge the gap between an application SPL and a mobile device one. This meta-model is also the support for the product derivation process. The approach is imple- mented in a framework named ApplIDE, and is used to successfully derive customer relationship management soft- ware on different devices

Hephaestus-PL : uma linha de produtos de ferramentas para linha de produtos de software

Dissertação (mestrado)—Universidade de Brasília, Departamento de Ciência da Computação, 2012.Suporte ferramental e essencial para a Engenharia de Aplica ção em Linhas de Produto de Software (LPS). Apesar de uma variedade de ferramentas existentes, a maioria delas não apresenta suporte adequado a con gurabilidade e exibilidade. Assim sendo, e dif cil para elas serem aplicadas em diferentes contextos, por exemplo, endere car variabilidade em diferentes combina ções de artefatos e permitir a inserção e o gerenciamento de variabilidades de novos artefatos de diferentes dom nios. Para abordar esta questão, e necessário explorar sistematicamente a comunalidade e, adequadamente, gerenciar a variabilidade de tais ferramentas. Nesse sentido, realizamos uma an alise comparativa de t ecnicas de gerenciamento de variabilidades para o desenvolvimento de ferramentas de LPS no contexto da ferramenta Hephaestus. A an alise revela que duas t ecnicas, uma anotativa e outra transformacional, são as mais adequadas ao gerenciamento de variabilidades em Hephaestus, e que a sua combina ção e uma estrat egia viável para melhorar esse gerenciamento. Além disso, apresentamos a an álise, projeto e implementa ção do dom ínio e um processo que suporta a evolu cão de Hephaestus-PL, uma linha de produtos de ferramentas de linha de produtos de software onde o gerenciamento de variabilidades foi implementado por abordagem transformacional usando opera c~oes de metaprogramação. Hephaestus-PL suporta um processo que permite a instanciaç~~ao de ferramentas de linha de produtos modelando a variabilidade em novos e em qualquer combina ção de artefatos, e foi desenvolvida por bootstrapping de versões da ferramenta Hephaestus. Este processo suporta a aborda- gem reativa e a exibilidade para introduzir novos ativos aumentando a con gurabilidade de Hephaestus-PL e permitindo a gera cão de diferentes instâncias de Hephaestus-PL. Uma avalia cão da solu ção proposta revela que a mesma melhorou a con gurabilidade e exibilidade quando comparamos com as evolu cões anteriores de Hephaestus. ______________________________________________________________________________ ABSTRACTTool support is essential for application engineering in software product lines. Despite a myriad of existing tools, most still lack adequate support for con gurability and exibility, so that it is hard for them to be applied in di erent contexts, e.g., addressing variability in an arbitrary combination of di erent artifacts and introducing and managing variabil- ity in new artifacts. Addressing this issue requires systematically exploring underlying commonality and adequately managing variability of such tools. Accordingly, we have conducted a comparative analysis of variability management techniques for SPL tool development in the context of the SPL Hephaestus tool. The analysis reveals that two techniques, one annotative and another transformational, are most suitable to variability management in Hephaestus, and that their combination is a feasible strategy to improve such management. Furthermore, we present domain analysis, design, implementation, and a supporting process for extending Hephaestus-PL, a software product line of software product line tools whose variability management was implemented by transformational approach us- ing metaprogramming operations. Hephaestus-PL is supported by a process allowing instantiating product line tools for modeling variability in new and in any combination of artifacts, and has been developed by bootstrapping previous versions of the Hephaestus tool. This process supports the reactive approach and exibility to add new assets increas- ing the con gurability of Hephaestus-PL and reaching the goal of enabling the generation of di erent instances of Hephaestus-PL. An assessment of the proposed solution reveals that it has improved con gurability and exibility when compared to previous evolution of Hephaestus

A systematic review of quality attributes and measures for software product lines

[EN] It is widely accepted that software measures provide an appropriate mechanism for understanding, monitoring, controlling, and predicting the quality of software development projects. In software product lines (SPL), quality is even more important than in a single software product since, owing to systematic reuse, a fault or an inadequate design decision could be propagated to several products in the family. Over the last few years, a great number of quality attributes and measures for assessing the quality of SPL have been reported in literature. However, no studies summarizing the current knowledge about them exist. This paper presents a systematic literature review with the objective of identifying and interpreting all the available studies from 1996 to 2010 that present quality attributes and/or measures for SPL. These attributes and measures have been classified using a set of criteria that includes the life cycle phase in which the measures are applied; the corresponding quality characteristics; their support for specific SPL characteristics (e. g., variability, compositionality); the procedure used to validate the measures, etc. We found 165 measures related to 97 different quality attributes. The results of the review indicated that 92% of the measures evaluate attributes that are related to maintainability. In addition, 67% of the measures are used during the design phase of Domain Engineering, and 56% are applied to evaluate the product line architecture. However, only 25% of them have been empirically validated. In conclusion, the results provide a global vision of the state of the research within this area in order to help researchers in detecting weaknesses, directing research efforts, and identifying new research lines. In particular, there is a need for new measures with which to evaluate both the quality of the artifacts produced during the entire SPL life cycle and other quality characteristics. There is also a need for more validation (both theoretical and empirical) of existing measures. In addition, our results may be useful as a reference guide for practitioners to assist them in the selection or the adaptation of existing measures for evaluating their software product lines. © 2011 Springer Science+Business Media, LLC.This research has been funded by the Spanish Ministry of Science and Innovation under the MULTIPLE (Multimodeling Approach For Quality-Aware Software Product Lines) project with ref. TIN2009-13838.Montagud Gregori, S.; Abrahao Gonzales, SM.; Insfrán Pelozo, CE. (2012). A systematic review of quality attributes and measures for software product lines. Software Quality Journal. 20(3-4):425-486. https://doi.org/10.1007/s11219-011-9146-7S425486203-4Abdelmoez, W., Nassar, D. 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B., Barachisio Lisboa, L., de Almeida E. S., & de Lemos Meira, S. R. (2008). Evaluating domain design approaches using systematic review. In 2nd European conference on software architecture, Cyprus, pp. 50–65.Ejiogu, L. (1991). Software engineering with formal metrics. QED Publishing.Engström, E., & Runeson, P. (2011). Software product line testing—A systematic mapping study. Information & Software Technology, 53(1), 2–13.Etxeberria, L., Sagarui, G., & Belategi, L. (2008). Quality aware software product line engineering. Journal of the Brazilian Computer Society, 14(1), Campinas Mar.Ganesan, D., Knodel, J., Kolb, R., Haury, U., & Meier, G. (2007). Comparing costs and benefits of different test strategies for a software product line: A study from Testo AG. In 11th international software product line conference, Kyoto, Japan, pp. 74–83, September 2007.Gómez, O., Oktaba, H., Piattini, M., & García, F. (2006). 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Engineering Management Approach to Software Production Plan, based on the Principles of Software Product Lines

The concept of the software factory and discussions over its realization dates back more than three decades; however it is still only a vision for medium and large size Information Technology [IT] organizations on an earnest journey for software excellence. The principles and practices of Software Product Lines [SPL] can be a catalyst in realizing such a vision. SPL ensembles three elements namely, core asset development, product development, and management to run an efficient and consistent software factory. The core asset development is based on “Domain Engineering” and is fundamental to leveraging commonalties between software products & services developed. The product development encircles the core assets and provides the variability required in the product line. Finally, management acts as the strategic objective provider. Employing these principles of SPL, a software production plan can be devised with five essential practice areas such as Configuration Management; Data Collection, Metrics and Tracking; Process Definition; Technical Planning; and Tool Support. Configuration Management is a disciplined approach of evaluating, coordinating, approving or disapproving and finally implementing changes in the software artifacts. Data Collection, Metrics and Tracking enable the software factory to assure quality and seek continuous improvements. Process Definition ensures the software factory is scientific in its approach and delivers repeatable performance. Technical Planning chalks the roadmap of realizing the prophecy of reusability and fulfilling the software factory vision. Finally proper Tool Support ensures productivity, efficiency and consistent performance from all the stakeholders in the software factory

MUSA: A Scalable Multi-Touch and Multi-Perspective Variability Management Tool

Variability management is one of the main activities in the Software Product Line Engineering process. Common and varied features of related products are modelled along with the dependencies and relationships among them. With the increase in size and complexity of product lines and the more holistic systems approach to the design process, managing the ever- growing variability models has become a challenge. In this paper, we present MUSA, a tool for managing variability and features in large-scale models. MUSA adopts the Separation of Concerns design principle by providing multiple perspectives to the model, each conveying different set of information. The demonstration is conducted using a real-life model (comprising of 1000+ features) particularly showing the Structural View, which is displayed using a mind-mapping visualisation technique (hyperbolic trees), and the Dependency View, which is displayed graphically using logic gates

PACOGEN : Automatic Generation of Pairwise Test Configurations from Feature Models

International audienceFeature models are commonly used to specify variability in software product lines. Several tools support feature models for variability management at different steps in the development process. However, tool support for test configuration generation is currently limited. This test generation task consists in systematically selecting a set of configurations that represent a relevant sample of the variability space and that can be used to test the product line. In this paper we propose PACOGEN to analyze feature models and automatically generate a set of configurations that cover all pairwise interactions between features. PACOGEN relies on constraint programming to generate configurations that satisfy all constraints imposed by the feature model and to minimize the set of the tests configurations. This work also proposes an extensive experiment, based on the state-of-the art SPLOT feature models repository, showing that PACOGEN scales over variability spaces with millions of configurations and covers pairwise with less configurations than other available tools

Integrated Management of Variability in Space and Time in Software Families

Software Product Lines (SPLs) and Software Ecosystems (SECOs) are approaches to capturing families of closely related software systems in terms of common and variable functionality (variability in space). SPLs and especially SECOs are subject to software evolution to adapt to new or changed requirements resulting in different versions of the software family and its variable assets (variability in time). Both dimensions may be interconnected (e.g., through version incompatibilities) and, thus, have to be handled simultaneously as not all customers upgrade their respective products immediately or completely. However, there currently is no integrated approach allowing variant derivation of features in different version combinations. In this thesis, remedy is provided in the form of an integrated approach making contributions in three areas: (1) As variability model, Hyper-Feature Models (HFMs) and a version-aware constraint language are introduced to conceptually capture variability in time as features and feature versions. (2) As variability realization mechanism, delta modeling is extended for variability in time, and a language creation infrastructure is provided to devise suitable delta languages. (3) For the variant derivation procedure, an automatic version selection mechanism is presented as well as a procedure to derive large parts of the application order for delta modules from the structure of the HFM. The presented integrated approach enables derivation of concrete software systems from an SPL or a SECO where both features and feature versions may be configured.:I. Context and Preliminaries 1. The Configurable TurtleBot Driver as Running Example 1.1. TurtleBot: A Domestic Service Robot 1.2. Configurable Driver Functionality 1.3. Software Realization Artifacts 1.4. Development History of the Driver Software 2. Families of Variable Software Systems 2.1. Variability 2.1.1. Variability in Space and Time 2.1.2. Internal and External Variability 2.2. Manifestations of Configuration Knowledge 2.2.1. Variability Models 2.2.2. Variability Realization Mechanisms 2.2.3. Variability in Realization Assets 2.3. Types of Software Families 2.3.1. Software Product Lines 2.3.2. Software Ecosystems 2.3.3. Comparison of Software Product Lines and Software Ecosystems 3. Fundamental Approaches and Technologies of the Thesis 3.1. Model-Driven Software Development 3.1.1. Metamodeling Levels 3.1.2. Utilizing Models in Generative Approaches 3.1.3. Representation of Languages using Metamodels 3.1.4. Changing the Model-Representation of Artifacts 3.1.5. Suitability of Model-Driven Software Development 3.2. Fundamental Variability Management Techniques of the Thesis 3.2.1. Feature Models as Variability Models 3.2.2. Delta Modeling as Variability Realization Mechanism 3.2.3. Variant Derivation Process of Delta Modeling with Feature Models 3.3. Constraint Satisfaction Problems 3.4. Scope 3.4.1. Problem Statement 3.4.2. Requirements 3.4.3. Assumptions and Boundaries II. Integrated Management of Variability in Space and Time 4. Capturing Variability in Space and Time with Hyper-Feature Models 4.1. Feature Models Cannot Capture Variability in Time 4.2. Formal Definition of Feature Models 4.3. Definition of Hyper-Feature Models 4.4. Creation of Hyper-Feature Model Versions 4.5. Version-Aware Constraints to Represent Version Dependencies and Incompatibilities 4.6. Hyper-Feature Models are a True Extension to Feature Models 4.7. Case Study 4.8. Demarcation from Related Work 4.9. Chapter Summary 5. Creating Delta Languages Suitable for Variability in Space and Time 5.1. Current Delta Languages are not Suitable for Variability in Time 5.2. Software Fault Trees as Example of a Source Language 5.3. Evolution Delta Modules as Manifestation of Variability in Time 5.4. Automating Delta Language Generation 5.4.1. Standard Delta Operations Realize Usual Functionality 5.4.2. Custom Delta Operations Realize Specialized Functionality 5.5. Delta Language Creation Infrastructure 5.5.1. The Common Base Delta Language Provides Shared Functionality for all Delta Languages 5.5.2. Delta Dialects Define Delta Operations for Custom Delta Languages 5.5.3. Custom Delta Languages Enable Variability in Source Languages 5.6. Case Study 5.7. Demarcation from Related Work 5.8. Chapter Summary 6. Deriving Variants with Variability in Space and Time 6.1. Variant Derivation Cannot Handle Variability in Time 6.2. Associating Features and Feature Versions with Delta Modules 6.3. Automatically Select Versions to Ease Configuration 6.4. Application Order and Implicitly Required Delta Modules 6.4.1. Determining Relevant Delta Modules 6.4.2. Forming a Dependency Graph of Delta Modules 6.4.3. Performing a Topological Sorting of Delta Modules 6.5. Generating Variants with Versions of Variable Assets 6.6. Case Study 6.7. Demarcation from Related Work 6.8. Chapter Summary III. Realization and Application 7. Realization as Tool Suite DeltaEcore 7.1. Creating Delta Languages 7.1.1. Shared Base Metamodel 7.1.2. Common Base Delta Language 7.1.3. Delta Dialects 7.2. Specifying a Software Family with Variability in Space and Time 7.2.1. Hyper-Feature Models 7.2.2. Version-Aware Constraints 7.2.3. Delta Modules 7.2.4. Application-Order Constraints 7.2.5. Mapping Models 7.3. Deriving Variants 7.3.1. Creating a Configuration 7.3.2. Collecting Delta Modules 7.3.3. Ordering Delta Modules 7.3.4. Applying Delta Modules 8. Evaluation 8.1. Configurable TurtleBot Driver Software 8.1.1. Variability in Space 8.1.2. Variability in Time 8.1.3. Integrated Management of Variability in Space and Time 8.2. Metamodel Family for Role-Based Modeling and Programming Languages 8.2.1. Variability in Space 8.2.2. Variability in Time 8.2.3. Integrated Management of Variability in Space and Time 8.3. A Software Product Line of Feature Modeling Notations and Constraint Languages 8.3.1. Variability in Space 8.3.2. Variability in Time 8.3.3. Integrated Management of Variability in Space and Time 8.4. Results and Discussion 8.4.1. Results and Discussion of RQ1: Variability Model 8.4.2. Results and Discussion of RQ2: Variability Realization Mechanism 8.4.3. Results and Discussion of RQ3: Variant Derivation Procedure 9. Conclusion 9.1. Discussion 9.1.1. Supported Evolutionary Changes 9.1.2. Conceptual Representation of Variability in Time 9.1.3. Perception of Versions as Incremental 9.1.4. Version Numbering Schemes 9.1.5. Created Delta Languages 9.1.6. Scalability of Approach 9.2. Possible Future Application Areas 9.2.1. Extend to Full Software Ecosystem Feature Model 9.2.2. Model Software Ecosystems 9.2.3. Extract Hyper-Feature Model Versions and Record Delta Modules 9.2.4. Introduce Metaevolution Delta Modules 9.2.5. Support Incremental Reconfiguration 9.2.6. Apply for Evolution Analysis and Planning 9.2.7. Enable Evolution of Variable Safety-Critical Systems 9.3. Contribution 9.3.1. Individual Contributions 9.3.2. Handling Updater Stereotypes IV. Appendix A. Delta Operation Generation Algorithm B. Delta Dialects B.1. Delta Dialect for Java B.2. Delta Dialect for Eclipse Projects B.3. Delta Dialect for DocBook Markup B.4. Delta Dialect for Software Fault Trees B.5. Delta Dialect for Component Fault Diagrams B.6. Delta Dialect for Checklists B.7. Delta Dialect for the Goal Structuring Notation B.8. Delta Dialect for EMF Ecore B.9. Delta Dialect for EMFText Concrete Syntax File

Variability and Evolution in Systems of Systems

In this position paper (1) we discuss two particular aspects of Systems of Systems, i.e., variability and evolution. (2) We argue that concepts from Product Line Engineering and Software Evolution are relevant to Systems of Systems Engineering. (3) Conversely, concepts from Systems of Systems Engineering can be helpful in Product Line Engineering and Software Evolution. Hence, we argue that an exchange of concepts between the disciplines would be beneficial.Comment: In Proceedings AiSoS 2013, arXiv:1311.319

Variability management in a model-driven software product line

Variability management in Software Product Lines (SPLs) has two fundamental challenges: (1) the expression of common and variable features, and (2) the development of applications employing properly such features. In this paper, we present a Software Product Line based on Models (MD-SPL). We separate the concepts related to SPLs in different domains and we build core assets like feature models, metamodels, and three different types of transformation rules to transform models from a source domain to different (variable) models into a target domain. By using transformation rules, we are able to generate applications in an incremental process, guided by a set of features selected for each target domain. Thus, we manage to extend the SPLs scope, separate the domains diminishing the complexity to create applications with variable characteristics, and automatically generate applications using transformation rules. In order to illustrate our approach, we have built a MDSPL where the products are small applications used in programming computers teaching