We present an approach based on Model-Driven Development ideas to create Software Product Lines(SPLs). In Model-Driven SPL approaches, the derivation of a product starts from a domain application model. This model is transformed through several stages reusing model transformation rules until a product is obtained. Transformations rules are selected according to variants included in configurations created by product designers. Configurations include variants from variation points, which are relevant characteristics representing the variability of a product line. Our approach (1) provides mechanisms to improve the expression of variability of Model-Driven SPLs by allowing designers to create fine-grained configurations of products, and (2) integrates a product derivation process which uses decision models and Aspect-Oriented Programming facilitating the reuse, adaptation and composition of model transformation rules. We introduce constraint models which make it possible for product line architects to capture the scope of product lines using the concepts of constraint, cardinality property and structural dependency property. To configure products, we create domain models and binding models, which are sets of bindings between model elements and variants and satisfy the constraint models. We define a decision model as a set of aspects. An aspect maintains information of what and when transformations rules that generate commonalities of products must be intercepted (joinpoints) and what transformation rules (advices) that generate variable structures must be executed instead. Our strategy maintains uncoupled variants from model transformation rules. This solves problems related to modularization, coupling, flexibility and maintainability of transformations rules because they are completely separated from variants; thus, they can evolve independently.

Background: A key idea of feature orientation is to decompose a software product line along the features it provides. Feature decomposition is orthogonal to object-oriented decomposition it crosscuts the underlying package and class structure. It has been argued often that feature decomposition improves system structure (reduced coupling, increased cohesion). However, recent empirical findings suggest that this is not necessarily the case, which is the motivation for our empirical investigation. Aim: In fact, there is little empirical evidence on how the alternative decompositions of feature orientation and object orientation compare to each other in terms of their association with observable properties of system structure (coupling, cohesion). This motivated us to empirically investigate and compare the properties of three decompositions (object-oriented, feature-oriented, and their intersection) of 28 feature-oriented software product lines. Method: In an exploratory, observational study, we quantify internal attributes, such as import coupling and cohesion, to describe and analyze the different decompositions of a feature-oriented product line in a systematic, reproducible, and comparable manner. For this purpose, we use three established software measures (CBU, IUD, EUD) as well as standard distribution statistics (e.g., Gini coefficient). Results: First, feature decomposition is associated with higher levels of structural coupling in a product line than a decomposition into classes. Second, although coupling is concentrated in feature decompositions, there are not necessarily hot-spot features. Third, the cohesion of feature modules is not necessarily higher than class cohesion, whereas feature modules serve more dependencies internally than classes. Fourth, coupling and cohesion measurement show potential for sampling optimization in complex static and dynamic product-line analyses (product-line type checking, feature-interaction detection). Conclusions: Our empirical study raises critical questions about alleged advantages of feature decomposition. At the same time, we demonstrate how the measurement of structural attributes can facilitate static and dynamic analyses of software product lines. (authors' abstract) / Series: Technical Reports / Institute for Information Systems and New Media

Background: A key idea of feature orientation is to decompose a software product line along the features it provides. Feature decomposition is orthogonal to object-oriented decomposition it crosscuts the underlying package and class structure. It has been argued often that feature decomposition improves system structure (reduced coupling, increased cohesion). However, recent empirical findings suggest that this is not necessarily the case, which is the motivation for our empirical investigation. Aim: In fact, there is little empirical evidence on how the alternative decompositions of feature orientation and object orientation compare to each other in terms of their association with observable properties of system structure (coupling, cohesion). This motivated us to empirically investigate and compare the properties of three decompositions (object-oriented, feature-oriented, and their intersection) of 28 feature-oriented software product lines. Method: In an exploratory, observational study, we quantify internal attributes, such as import coupling and cohesion, to describe and analyze the different decompositions of a feature-oriented product line in a systematic, reproducible, and comparable manner. For this purpose, we use three established software measures (CBU, IUD, EUD) as well as standard distribution statistics (e.g., Gini coefficient). Results: First, feature decomposition is associated with higher levels of structural coupling in a product line than a decomposition into classes. Second, although coupling is concentrated in feature decompositions, there are not necessarily hot-spot features. Third, the cohesion of feature modules is not necessarily higher than class cohesion, whereas feature modules serve more dependencies internally than classes. Fourth, coupling and cohesion measurement show potential for sampling optimization in complex static and dynamic product-line analyses (product-line type checking, feature-interaction detection). Conclusions: Our empirical study raises critical questions about alleged advantages of feature decomposition. At the same time, we demonstrate how the measurement of structural attributes can facilitate static and dynamic analyses of software product lines. (authors' abstract) / Series: Technical Reports / Institute for Information Systems and New Media

[pt] A configuração de produto é uma atividade chave para permitir a customização em massa. Ela corresponde a produção de um sistema computacional a partir de uma linha de produtos de software, respeitando as necessidades individuais dos clientes. Na prática, a atividade de configuração do produto pode se tornar uma tarefa complexa, principalmente porque envolve várias partes interessadas com diferentes competências para tomar decisões. Vários trabalhos proprõem decompor a atividade de configuração em estágios pré-estabelecidos, atravrés dos quais os interessados podem tomar suas decisões de forma separada e coerente. No entanto, quando há uma descentralização geográfica do conhecimento necessário em cada etapa e/ou quando os requisitos do cliente forem imprecisos e mudarem com frequência, essas soluções propostas não se aplicam. Para resolver essas questões, este trabalho proprõe uma abordagem de configuração dinâmica e colaborativa de produtos com base na metáfora de assistência pessoal. Os assistentes pessoais num ambiente cooperativo coordenam as decisões dos stakeholders e pró-ativamente executam tarefas, tais como o raciocínio sobre as implicaçõoes das decisões, integrando as decisões distribuídas e resolvendo os requisitos divergentes. Uma ferramenta protótipo, chamada Libertas, e dois cenários ilustrativos que avaliam a aplicabilidade da nossa abordagem também são apresentados. O primeiro cenário analisa o processo de configuração para configurar um sistema operacional para suportar os requisitos de negócio de uma empresa. O segundo aborda um cen´ario com uma linha de produtos de software para portais web. / [en] Product configuration is a key activity for enabling mass customization. It corresponds to tailoring a software application from a software product line, respecting individual customer requirements. In practice, the product configuration activity is challenging, mainly because it involves numerous stakeholders with different expertise making decisions. Several works claim to decompose the configuration activity into pre-arranged stages, whereby stakeholders can make their decisions in a separated way and coherent fashion. However, due to the decentralization in geography of the knowledge required in each stage and that customer requirements could be imprecise and change frequently, the proposed solutions do not apply. To address these issues, this work proposes a dynamic and collaborative product configuration approach based on the personal assistant metaphor. Personal assistants in a cooperative way coordinate stakeholders´ decisions and proactively perform tasks, such as reasoning about the ramifications of decisions, integrating distributed decisions and resolving divergent requirements. A tool prototype, called Libertas, and two case studies that evaluate the applicability of our approach are also presented. The first case study analyzes the configuration process to configure an operational system to support the business requirements of an enterprise. The second one addresses a scenario of a software product line for web portals.

Configuração modelo de features é conhecida por ser uma atividade complexa, demorada e propensa a erros. Esta atividade torna-se ainda mais complicada quando envolve múltiplas partes interessadas no processo de configuração. Trabalhos de pesquisa têm proposto abordagens para ajudar na configuração de modelo de features, mas elas dependem de processos sistemáticos que restringem as decisões de alguns dos stakeholders. Neste trabalho, propomos uma nova abordagem para melhorar o processo de configuração multi-stakeholder, considerando as preferências dos stakeholders expressas através de restrições duras e brandas. Com base em tais preferências, recomendamos diferentes configurações de produto utilizando diferentes estratégias da teoria da escolha social. Nossa abordagem é implementada em uma ferramenta chamada SACRES, que permite criar grupos de stakeholders, especificar preferências dos stakeholders sobre uma configuração e gerar as configurações ideais. Realizamos um estudo empírico para avaliar a eficácia de nossas estratégias no que diz respeito à satisfação individual e justiça entre todos os stakeholders. Os resultados obtidos provem evidência de que estratégias em particular possuem melhor performance em relação à satisfação de grupo, chamadas average e multiplicative considerando as pontuações atribuídas pelos participantes e complexidade computacional. Nossos resultados são relevantes não só no contexto de Linha de Produto de Software, mas também para a Teoria da Escolha Social, dada a instanciação de estratégias de escolha social em um problema prático. / Feature model con guration is known to be a hard, error-prone and timeconsuming activity. This activity gets even more complicated when it involves multiple stakeholders in the con guration process. Research work has proposed approaches to aid multi-stakeholder feature model con guration, but they rely on systematic processes that constraint decisions of some of the stakeholders. In this dissertation, we propose a novel approach to improve the multi-stakeholder con guration process, considering stakeholders' preferences expressed through both hard and soft constraints. Based on such preferences, we recommend di erent product con gurations using di erent strategies from the social choice theory. Our approach is implemented in a tool named SACRES, which allows creation of stakeholder groups, speci cation of stakeholder preferences over a con guration and generation of optimal con guration. We conducted an empirical study to evaluate the e ectiveness of our strategies with respect to individual stakeholder satisfaction and fairness among all stakeholders. The obtained results provide evidence that particular strategies perform best with respect to group satisfaction, namely average and multiplicative, considering the scores given by the participants and computational complexity. Our results are relevant not only in the context software product lines, but also in the context of social choice theory, given the instantiation of social choice strategies in a practical problem.

Made available in DSpace on 2014-12-17T14:56:03Z (GMT). No. of bitstreams: 1 TulioPMC_DISSERT.pdf: 1801045 bytes, checksum: 77adefdeea59e2db6076c8f805d6778f (MD5) Previous issue date: 2012-08-03 / E-learning, which refers to the use of Internet-related technologies to improve knowledge and learning, has emerged as a complementary form of education, bringing advantages such as increased accessibility to information, personalized learning, democratization of education and ease of update, distribution and standardization of the content. In this sense, this paper aims to develop a tool, named ISE-SPL, whose purpose is the automatic generation of E-learning systems for medical education, making use of concepts of Software Product Lines. It consists of an innovative methodology for medical education that aims to assist professors of healthcare in their teaching through the use of educational technologies, all based on computing applied to healthcare (Informatics in Health). The tests performed to validate the ISE-SPL were divided into two stages: the first was made by using a software analysis tool similar to ISE-SPL, called SPLOT and the second was performed through usability questionnaires to healthcare professors who used ISESPL. Both tests showed positive results, proving it to be an efficient tool for generation of E-learning software and useful for professors in healthcare / O e-learning, que se refere ao uso das tecnologias relacionadas ? Internet para aperfei?oar o conhecimento e a aprendizagem, surgiu como uma forma complementar de ensino, trazendo consigo vantagens como o aumento da acessibilidade da informa??o, aprendizado personalizado, democratiza??o do ensino e facilidade de atualiza??o, distribui??o e padroniza??o do conte?do. Neste sentido, o presente trabalho tem como objeto o desenvolvimento de uma ferramenta, intitulada de ISE-SPL, cujo prop?sito ? a gera??o autom?tica de sistemas e-learning para educa??o m?dica, utilizando para isso conceitos de Linha de Produtos de Software. Ela consiste em uma metodologia inovadora para a educa??o m?dica que visa auxiliar o docente da ?rea de sa?de na sua pr?tica pedag?gica por meio do uso de tecnologias educacionais, todas baseadas na computa??o aplicada ? sa?de (Inform?tica em Sa?de). Os testes realizados para validar a ISE-SPL foram divididos em duas etapas: a primeira foi feita atrav?s da utiliza??o de um software de an?lise de ferramentas semelhantes ao ISE-SPL, chamado de SPLOT; e a segunda foi realizada atrav?s da aplica??o de question?rios de usabilidade aos docentes da ?rea da sa?de que utilizaram o ISE-SPL. Ambos os testes demonstraram resultados positivos, comprovando que o ISE-SPL ? uma ferramenta de gera??o de softwares e-learning eficiente e ?til para o docente da ?rea da sa?de

Configuração modelo de features é conhecida por ser uma atividade complexa, demorada e propensa a erros. Esta atividade torna-se ainda mais complicada quando envolve múltiplas partes interessadas no processo de configuração. Trabalhos de pesquisa têm proposto abordagens para ajudar na configuração de modelo de features, mas elas dependem de processos sistemáticos que restringem as decisões de alguns dos stakeholders. Neste trabalho, propomos uma nova abordagem para melhorar o processo de configuração multi-stakeholder, considerando as preferências dos stakeholders expressas através de restrições duras e brandas. Com base em tais preferências, recomendamos diferentes configurações de produto utilizando diferentes estratégias da teoria da escolha social. Nossa abordagem é implementada em uma ferramenta chamada SACRES, que permite criar grupos de stakeholders, especificar preferências dos stakeholders sobre uma configuração e gerar as configurações ideais. Realizamos um estudo empírico para avaliar a eficácia de nossas estratégias no que diz respeito à satisfação individual e justiça entre todos os stakeholders. Os resultados obtidos provem evidência de que estratégias em particular possuem melhor performance em relação à satisfação de grupo, chamadas average e multiplicative considerando as pontuações atribuídas pelos participantes e complexidade computacional. Nossos resultados são relevantes não só no contexto de Linha de Produto de Software, mas também para a Teoria da Escolha Social, dada a instanciação de estratégias de escolha social em um problema prático. / Feature model con guration is known to be a hard, error-prone and timeconsuming activity. This activity gets even more complicated when it involves multiple stakeholders in the con guration process. Research work has proposed approaches to aid multi-stakeholder feature model con guration, but they rely on systematic processes that constraint decisions of some of the stakeholders. In this dissertation, we propose a novel approach to improve the multi-stakeholder con guration process, considering stakeholders' preferences expressed through both hard and soft constraints. Based on such preferences, we recommend di erent product con gurations using di erent strategies from the social choice theory. Our approach is implemented in a tool named SACRES, which allows creation of stakeholder groups, speci cation of stakeholder preferences over a con guration and generation of optimal con guration. We conducted an empirical study to evaluate the e ectiveness of our strategies with respect to individual stakeholder satisfaction and fairness among all stakeholders. The obtained results provide evidence that particular strategies perform best with respect to group satisfaction, namely average and multiplicative, considering the scores given by the participants and computational complexity. Our results are relevant not only in the context software product lines, but also in the context of social choice theory, given the instantiation of social choice strategies in a practical problem.

Submitted by Fabio Sobreira Campos da Costa (fabio.sobreira@ufpe.br) on 2016-03-15T15:21:11Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) TESE_SABRINA.pdf: 1152470 bytes, checksum: a89ffc94cb3ee813cf52ca2c043171ba (MD5) / Made available in DSpace on 2016-03-15T15:21:11Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) TESE_SABRINA.pdf: 1152470 bytes, checksum: a89ffc94cb3ee813cf52ca2c043171ba (MD5) Previous issue date: 2015-03-31 / Software Product Lines (SPLs) allow engineers to systematically build families of software products, defined by a unique combination of features—increments in functionality, improving both the efficiency of the software development process and the quality of the software developed. However, testing these kinds of systems is challenging, as it may require running each test against a combinatorial number of products. We call this problem the High Dimensionality Problem. Another obstacle to product line testing is the absence of Feature Models (FMs), making it difficult to discover the real causes for test failures. We call this problem the Lack of Feature Model Problem. The High Dimensionality Problem is associated to the large space of possible configurations that an SPL can reach. If an SPL has n boolean features, for example, there are 2n possible feature combinations. Therefore, systematically testing this kind of system may require running each test against all those combinations, in the worst case. The Lack of Feature Model Problem is related to the absence of feature models. The FM enables accurate categorization of failing tests as failures of programs or the tests themselves, not as failures due to inconsistent combinations of features. For this reason, the lack of FM presents a huge challenge to discover the true causes for test failures. Aiming to solve these problems, we propose two lightweight techniques: SPLat and SPLif. SPLat is a new approach to dynamically prune irrelevant configurations: the configurations to run for a test can be determined during test execution by monitoring accesses to configuration variables. As a result, SPLat reduces the number of configurations. Consequently, SPLat is lightweight compared to prior works that used static analysis and heavyweight dynamic execution. SPLif is a technique for testing SPLs that does not require a priori availability of feature models. Our insight is to use a profile of passing and failing test runs to quickly identify test failures that are indicative of a problem (in test or code) as opposed to a manifestation of execution against an inconsistent combination of features. Experimental results show that SPLat effectively identifies relevant configurations with a low overhead. We also apply SPLat on two large configurable systems (Groupon and GCC), and it scaled without much engineering effort. Experimental results demonstrate that SPLif is useful and effective to quickly find tests that fail on consistent configurations, regardless of how complete the FMs are. Furthermore, we evaluated SPLif on one large extensively tested configurable system, GCC, where it helped to reveal 5 new bugs, 3 of which have been fixed after our bug reports. / Software Product Lines (SPLs) allow engineers to systematically build families of software products, defined by a unique combination of features—increments in functionality, improving both the efficiency of the software development process and the quality of the software developed. However, testing these kinds of systems is challenging, as it may require running each test against a combinatorial number of products. We call this problem the High Dimensionality Problem. Another obstacle to product line testing is the absence of Feature Models (FMs), making it difficult to discover the real causes for test failures. We call this problem the Lack of Feature Model Problem. The High Dimensionality Problem is associated to the large space of possible configurations that an SPL can reach. If an SPL has n boolean features, for example, there are 2n possible feature combinations. Therefore, systematically testing this kind of system may require running each test against all those combinations, in the worst case. The Lack of Feature Model Problem is related to the absence of feature models. The FM enables accurate categorization of failing tests as failures of programs or the tests themselves, not as failures due to inconsistent combinations of features. For this reason, the lack of FM presents a huge challenge to discover the true causes for test failures. Aiming to solve these problems, we propose two lightweight techniques: SPLat and SPLif. SPLat is a new approach to dynamically prune irrelevant configurations: the configurations to run for a test can be determined during test execution by monitoring accesses to configuration variables. As a result, SPLat reduces the number of configurations. Consequently, SPLat is lightweight compared to prior works that used static analysis and heavyweight dynamic execution. SPLif is a technique for testing SPLs that does not require a priori availability of feature models. Our insight is to use a profile of passing and failing test runs to quickly identify test failures that are indicative of a problem (in test or code) as opposed to a manifestation of execution against an inconsistent combination of features. Experimental results show that SPLat effectively identifies relevant configurations with a low overhead. We also apply SPLat on two large configurable systems (Groupon and GCC), and it scaled without much engineering effort. Experimental results demonstrate that SPLif is useful and effective to quickly find tests that fail on consistent configurations, regardless of how complete the FMs are. Furthermore, we evaluated SPLif on one large extensively tested configurable system, GCC, where it helped to reveal 5 new bugs, 3 of which have been fixed after our bug reports.

This Master thesis proposes a solution to manage variabilities of software product line applications. The objective of the research is to support software decision makers in handling additional software complexity introduced by product line architectures. In order to fulfill this objective an approach to analyze, visualize, and measure product line specific characteristics of the C/C++ source code are proposed. The approach is validated in an empirical experiment using an open source software system. For that purpose the approach is first implemented into ®1 M-System-NT, an existing software measurement tool developed at Fraunhofer. The target hypothesis of the Institute for Experimental Software engineering research master thesis to perform static analysis of C/C++ source code, measure traditional and product line measures to identify the correlation between measures and indicate the fault proneness. / Official Address: Researcher Zeeshan Ahmed, Mechanical Engineering Informatics and TU Virtual Product Development Division (MIVP) Vienna, Austria Permanent Address: Zeeshan Ahmed, Humdered Street Mohala Garhi Shadula Sahib Gujrat, Pakistan

Veículos Aéreos não Tripulados (VANTs) são aeronaves que voam sem tripulação e são capazes de realizar diversos tipos de missões, como vigilância, coleta de dados topográficos e monitoramento ambiental. Este é um domínio que tem muito a ganhar com a aplicação da abordagem de Linha de Produtos de Software (LPS), uma vez que é rico em variabilidades e cada modelo de VANT tem também muitas partes comuns. Neste trabalho é apresentada uma infraestrutura tecnológica e de configuração de ativos em Simulink, gerenciados pelas ferramentas Pure::variant e Hephaestos para uma LPS de VANTs. Um conjunto de padrões para especificação de variabilidades em Simulink é proposto, bem como uma extensão para a ferramenta Hephaestus. Uma comparação entre as ferramentas Pure::variants e Hephaestus é apresentada / Unmanned Aerial Vehicles (UAVs) are aircrafts that can fly without any crew and are capable to realize several types of missions such as surveillance, topographic data collection and environmental monitoring. This is a domain which can benefit very much with the adoption of the Software Product Lines (SPL) approach, as each UAV model is rich in variabilities and has many common parts. In this work it is presented a software asset configuration infrastructure for the Simulink environment, managed by the tools Pure::variants and Hephaestus for a UAV SPL. A set of patterns of variability specification in Simulink is proposed as well as an extension to Hephaestus to support a SPL product engineering for Simulink. A comparison between Pure::variants and Hephaestus is also presented