[pt] Softwares personalizados para as necessidades de um cliente proveem vantagem competitiva quando comparados aos softwares de proposito geral. Linhas de produtos de softwares tem como objetivo a produção de produtos personalizados a partir de um conjunto de features reutilizáveis. É conhecido que o reuso sistemático de features potencialmente leva a ganhos significativos como rápida produção de software a um baixo custo e com maior qualidade. Na prática, a construção de linhas de produtos de softwares empresariais pode se tornar uma tarefa arriscada e sujeita a erros quando se leva em consideração o uso das técnicas atuais de implementação de features. O desenvolvimento de linhas de produtos de software empresariais de fato requer a convergência coordenada de várias visões (ex., especialistas de domínio, projetistas de interface, e desenvolvedores). Neste caso, cada participante do processo de desenvolvimento tem uma linguagem particular para resolver o problema específico a sua especialidade. Os desafios para integração de diferentes linguagens, evitando uma potencial cacofonia, é o problema do conhecimento de configuração heterogêneo. Nesta tese, nos examinamos as dificuldades atuais na especificação do conhecimento de configuração heterogêneo e como solução nos propomos a noção de Linguagens de Modelagem do Conhecimento do Domínio (LMCD). O propósito das LMCDs é evidenciar os conceitos do domínio e suas interfaces de programação, o que ajuda reduzir o ofuscamento do código fonte e aumentar a compreensão. Além disso, evidenciando os conceitos específicos de domínio, somos aptos a prevenir inconsistências em produtos pela detecção de erros em toda a linha de produto de software. Outro resultado deste trabalho de pesquisa é GenArchPlus, uma ferramenta extensível que suporta de forma flexível a incorporação de LMCDs na engenharia de linhas de produtos de softwares tradicional. Nos enfatizamos os benefícios da ferramenta, incluindo simplicidade, expressividade, e a capacidade de ser independente de qualquer tecnologia de implementação do domínio. Finalmente, nos ilustramos e avaliamos o uso de LMCDs em três diferentes linhas de produtos de software. / [en] Customer-specific software can provide a competitive advantage compared to general-purpose software. A software product line (SPL) aims at tailoring customer-specific products from a set of reusable features. It is well known that systematic reuse of features potentially leads to significant gains such as faster production with low costs and high quality. In practice, building enterprise software product lines might become a laborious and error-prone task when we take into account the use of current implementation techniques. Successful development of modern enterprise software product lines requires the convergence of multiple views (e.g., domain experts, interface designers, and developers), which are usually managed via domain-specific concepts. In this case, each participant of the development process has a particular working language to solve specific problems to its expertise. The challenge of integrating these differences into the engineering process, avoiding the potential cacophony of multiple different languages, is the heterogeneous configuration knowledge problem. In this thesis, we examine the current shortcomings on the specification of heterogeneous configuration knowledge and as a solution we propose the notion of Domain Knowledge Modeling Languages (DKMLs). The purpose of DKMLs is to put in evidence the domain concepts and their programming interfaces, which help to reduce source code obfuscation and increase feature comprehension. Moreover, evidencing the domain-specific concepts, we are also able to prevent inconsistencies on products by detecting errors in the entire software product line. Another result of this research is the GenArchPlus, an extensible tool that supports the flexible incorporation of DKMLs in traditional software product line engineering. We emphasize the benefits of GenArchPlus, including simplicity, expressiveness, and being framework independent. Finally, we illustrate and evaluate the use of DKMLs in three different product lines.

Orientador: Cecília Mary Fischer Rubira / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Computação / Made available in DSpace on 2018-08-24T09:31:42Z (GMT). No. of bitstreams: 1 NascimentoeSilva_AmandaSavio_D.pdf: 8931458 bytes, checksum: 448739042e9597c70abf120976d316b8 (MD5) Previous issue date: 2013 / Resumo: A confiabilidade é um requisito de qualidade indispensável a muitos sistemas orientados a serviços, cada vez mais disseminados em várias atividades humanas. Composições confiáveis de serviços são formadas por um conjunto de serviços com diversidade de projetos, isto é, um conjunto de serviços funcionalmente equivalentes, ou serviços alternativos, usados para implementar técnicas de tolerância a falhas. Uma determinada técnica, como por exemplo, Recovery Blocks ou N-version Programming, pode ser mais adequada para um contexto específico de execução do que outra, dependendo dos requisitos exigidos pela aplicação, como por exemplo, desempenho. Sistemas orientados a serviços são usualmente implantados num ambiente altamente dinâmico, em que são comuns alterações nos requisitos dos clientes e flutuações na qualidade de serviços. Portanto, uma composição de serviços confiável deveria poder modificar seu próprio comportamento dinamicamente em resposta a essas mudanças. Entretanto, as soluções existentes, que usam diversidade de projetos para implementar composições confiáveis, apresentam algumas limitações: (i) não apóiam a seleção de serviços alternativos adequados que garantam que a composição realmente tolere falhas de software; (ii) em geral implementam uma única técnica de tolerância a falhas, não apoiando os requisitos diversos de clientes; e (iii) não apoiam um mecanismo autoadaptativo capaz de mudar a estratégia de tolerância a falhas em tempo de execução. Nessa tese, é apresentada uma solução baseada em linhas de produtos de software, que explora a variabilidade de software existente nas técnicas de tolerância a falhas e nas mudanças ocorridas no ambiente de execução, para a implementação de composições de serviços tolerantes a falhas e autoadaptativas. A solução encompassa: (a) um conjunto de diretrizes para investigar até que ponto serviços alternativos são realmente diversos entre si para tolerar falhas de software; (b) uma família de técnicas de tolerância a falhas para construir composições confíaveis que permite a escolha de uma técnica mais adequada para o contexto; e (c) uma infraestrutura autoadaptiva que apoia a instanciação de técnicas diferentes de tolerância a falhas como resposta a mudanças ocorridas no contexto, baseando-se no gerenciamento dinâmico de variabilidades de software. Resultados de estudos empíricos sugerem que a solução é eficiente para apoiar composições de serviços tolerantes a falhas e autoadaptativas. Direções para trabalhos futuros são apresentadas / Abstract: Nowadays, society is dependent on systems based on Service-Oriented Architecture (SOA) for its basic day-to-day functioning. As a consequence, these systems should be reliable. Fault-tolerant service compositions encompass a set of services, each with equivalent functionality yet different designs, called alternate services, that are used to implement fault tolerance techniques. A particular technique, for example, Recovery Blocks or N-version Programming, might be more suitable in a context than in another one, depending on non-functional requirements of an application, for example, performance or reliability. SOA-based applications often rely in an environment that is highly dynamic and several decisions should be postponed until runtime, where we have different stakeholders with conflicting requirements, and fluctuations in the quality of services (QoS) are recurrent. Therefore, a fault-tolerant service composition should adapt itself to meet the dynamically and widely changing context. Nevertheless, the existing diversity-based solutions for fault-tolerant service compositions present some drawbacks: (i) they do not support the selection of alternate services that in fact efficient to support a reliable service composition; (ii) they usually support only one fault tolerance technique, thus not being able to face various clients' requirements; (iii) they do not support an adaptive fault tolerance mechanism able to instantiate different fault tolerance strategies at runtime to cope with dynamic changes in the context. In this thesis, we present a solution based on software product line, which explores the variability among various software fault tolerance techniques and changes in the execution environment, to implement fault-tolerant and self-adaptive service compositions. The proposed solution encompasses: (a) a set of directives to investigate to what extent alternate services are able to tolerate software faults; (b) a family of software fault tolerance techniques to support reliable service compositions, such as the most suitable technique can be chosen according to the context; (c) a self-adaptive infrastructure to instantiate at runtime appropriate fault tolerance techniques in response to changes in the context, through dynamic management of software variability. Results from empirical studies suggest that the proposed solution is efficient to support fault-tolerant and self-adaptive service compositions. Directions for future work are also presented / Doutorado / Ciência da Computação / Doutora em Ciência da Computação

Zur einfacheren Entwicklung von technischen Systemen werden heutzutage vielfach funktionsblockorientierte Modellierungssprachen wie MATLAB/Simulink verwendet, die ein System als Netzwerk von miteinander verbundenen Funktionsblöcken darstellen. Aufgrund wechselnder Anforderungen entstehen dabei viele Modellvarianten, die nicht mehr effizient verwaltet werden können. Eine Lösung hierfür ist der Einsatz von Produktlinien, bei dem alle Varianten zusammengefasst und in wiederverwendbare Bestandteile zerlegt werden. Die Einzelvarianten werden dabei nur noch bei Bedarf aus diesen Bestandteilen zusammengesetzt. Die Erstellung dieser Produktlinien ist jedoch mit hohem manuellen Aufwand verbunden, besonders wenn vorhandene Modelle wiederverwendet werden sollen. Dies verhindert oft die Einführung dieses Paradigmas. Das Ziel der Dissertation war es deshalb, diese Migration vorhandener Modellvarianten und damit die Erstellung der Produktlinien zu automatisieren. Hierzu wurde eine Migrationsschrittfolge vorgeschlagen: Mithilfe eines Model-Matching-Ansatzes werden zuerst Gemeinsamkeiten und Unterschiede zwischen den Modellen identifiziert und daraus ein zusammengefasstes Modell und sogenannte Features abgeleitet. Mithilfe der Formalen Begriffsanalyse werden daraufhin die Abhängigkeiten zwischen diesen Features extrahiert und daraus ein Feature-Modell erstellt. Feature-Modell und zusammengefasstes Modell bilden dabei eine Produktlinie, die exakt die vorgegebenen Modellvarianten beschreibt.

With the widespread use of information systems in modern society comes a growing demand for customizable and adaptable software. As a result, systems are increasingly developed as families of products adapted to specific contexts and requirements. Features are an established concept to capture the commonalities and variability between system variants. Most prominently, the concept is applied in the design, modeling, analysis, and implementation of software product lines where products are built upon a common base and are distinguished by their features. While adaptations encapsulated within features are mainly static and remain part of the system after deployment, dynamic adaptations become increasingly important. Especially interconnected mobile devices and embedded systems are required to be context-sensitive and (self-)adaptive. A promising concept for the design and implementation of such systems are roles as they capture context-dependent and collaboration-specific behavior. A major challenge in the development of feature-oriented and role-based systems are interactions, i.e., emergent behavior that arises from the combination of multiple features or roles. As the number of possible combinations is usually exponential in the number of features and roles, the detection of such interactions is difficult. Since unintended interactions may compromise the functional correctness of a system and may lead to reduced efficiency or reliability, it is desirable to detect them as early as possible in the development process. The goal of this thesis is to adopt the concepts of features and roles in the formal modeling and analysis of systems and system families. In particular, the focus is on the quantitative analysis of operational models by means of probabilistic model checking for supporting the development process and for ensuring correctness. The tool ProFeat, which enables a quantitative analysis of stochastic system families defined in terms of features, has been extended with additional language constructs, support for a one-by-one analysis of system variants, and a symbolic representation of analysis results. The implementation is evaluated by means of several case studies which compare different analysis approaches and show how ProFeat facilitates a family-based quantitative analysis of systems. For the compositional modeling of role-based systems, role-based automata (RBA) are introduced. The thesis presents a modeling language that is based on the input language of the probabilistic model checker PRISM to compactly describe RBA. Accompanying tool support translates RBA models into the PRISM language to enable the formal analysis of functional and non-functional properties, including system dynamics, contextual changes, and interactions. Furthermore, an approach for a declarative and compositional definition of role coordinators based on the exogenous coordination language Reo is proposed. The adequacy of the RBA approach for detecting interactions within context-sensitive and adaptive systems is shown by several case studies.:1 Introduction 1.1 Engineering approaches for variant-rich adaptive systems 1.2 Validation and verification methods 1.3 Analysis of feature-oriented and role-based systems 1.4 Contribution 1.5 Outline 2 Preliminaries I Feature-oriented systems 3 Feature-oriented engineering for family-based analysis 3.1 Feature-oriented development 3.2 Describing system families: The ProFeat language 3.2.1 Feature-oriented language constructs 3.2.2 Parametrization 3.2.3 Metaprogramming language extensions 3.2.4 Property specifications 3.2.5 Semantics 3.3 Implementation 3.3.1 Translation of ProFeat models 3.3.2 Post-processing of analysis results 4 Case studies and application areas 4.1 Comparing family-based and product-based analysis 4.1.1 Analysis of feature-oriented systems 4.1.2 Analysis of parametrized systems 4.2 Software product lines 4.2.1 Body sensor network 4.2.2 Elevator product line 4.3 Self-adaptive systems 4.3.1 Adaptive network system model 4.3.2 Adaptation protocol for distributed systems II Role-based Systems 5 Formal modeling and analysis of role-based systems 5.1 The role concept 5.1.1 Towards a common notion of roles 5.1.2 The Compartment Role Object Model 5.1.3 Roles in programming languages 5.2 Compositional modeling of role-based behavior 5.2.1 Role-based automata and their composition 5.2.2 Algebraic properties of compositions 5.2.3 Coordination and semantics of RBA 6 Implementation of a role-oriented modeling language 6.1 Role-oriented modeling language 6.1.1 Declaration of the system structure 6.1.2 Definition of operational behavior 6.2 Translation of role-based models 6.2.1 Transformation to multi-action MDPs 6.2.2 Multi-action extension of PRISM 6.2.3 Translation of components 6.2.4 Translation of role-playing coordinators 6.2.5 Encoding role-playing into states 7 Exogenous coordination of roles 7.1 The exogenous coordination language Reo 7.2 Constraint automata 7.3 Embedding of role-based automata in constraint automata 7.4 Implementation 7.4.1 Exogenous coordination of PRISM modules 7.4.2 Reo for exogenous coordination within PRISM 8 Evaluation of the role-oriented approach 8.1 Experimental studies 8.1.1 Peer-to-peer file transfer 8.1.2 Self-adaptive production cell 8.1.3 File transfer with exogenous coordination 8.2 Classification 8.3 Related work 8.3.1 Role-based approaches 8.3.2 Aspect-oriented approaches 8.3.3 Feature-oriented approaches 9 Conclusion

Nicht-funktionale Eigenschaften geben Aussagen über Qualitätsaspekte einer Software. Mit einer Software-Produktlinie (SPL) wird eine Menge von verwandten Software-Produkten beschrieben, die auf Basis gemeinsam genutzter Bausteine und Architekturen entwickelt werden, um die Anforderungen unterschiedlicher Kundengruppen zu erfüllen. Hierbei werden gezielt Software-Bestandteile wiederverwendet, um Software effizienter zu entwickeln. In dieser Arbeit wird der Einfluss von Eingabedaten auf die nicht-funktionalen Eigenschaften von SPL untersucht. Es wird auf Basis von Messungen ausgewählter nicht-funktionaler Eigenschaften einzelner Software-Produkte ein Vorhersagemodell für beliebige Software-Produkte der SPL erstellt. Das Vorhersagemodell kann genutzt werden, um den Konfigurationsprozess zu unterstützen. Das Verfahren wird anhand einer SPL von verlustfreien Kompressionsalgorithmen evaluiert. Die Berücksichtigung von Eingabedaten kann die Vorhersage von nicht-funktionalen Eigenschaften einer SPL gegenüber einfacheren Vorhersagemodellen ohne die Berücksichtigung von Eingabedaten signifikant verbessern.

Variability modeling is one of the key disciplines to cope with complex variability in large software product lines. It aims at creating, evolving, and configuring variability models, which describe the common and variable characteristics, also known as features, of products in a product line. Since the introduction of feature models more than twenty years ago, many variability modeling languages and notations have been proposed both in academia and industry, followed by hundreds of publications on variability modeling techniques that have built upon these theoretical foundations. Surprisingly, there are relatively few empirical studies that aim at understanding the use of such languages. What variability modeling concepts are actually used in practice? Do variability models applied in real-world look similar to those published in literature? In what technical and organizational contexts are variability models applicable? We present an empirical study that addresses this research gap. Our goals are i) to verify existing theoretical research, and ii) to explore real-world variability modeling languages and models expressed in them. We study concepts and semantics of variability modeling languages conceived by practitioners, and the usage of these concepts in real, large-scale models. Our aim is to support variability modeling research by providing empirical data about the use of its core modeling concepts, by identifying and characterizing further concepts that have not been as widely addressed, and by providing realistic assumptions about scale, structure, content, and complexity of real-world variability models. We believe that our findings are of relevance to variability modeling researchers and tool designers, for example, those working on interactive product configurators or feature dependency checkers. Our extracted models provide realistic benchmarks that can be used to evaluate new techniques. Recognizing the recent trend in software engineering to open up software platforms to facilitate inter-organizational reuse of software, we extend our empirical discourse to the emerging field of software ecosystems. As natural successors of successful product lines, ecosystems manage huge variability among and within their software assets, thus, represent a highly interesting class of systems to study variability modeling concepts and mechanisms. Our studied systems comprise eleven highly configurable software systems, two ecosystems with closed platforms, and three ecosystems relying on open platforms. Some of our subjects are among the largest successful systems in existence today. Results from a survey on industrial variability modeling complement these subjects. Our overall results provide empirical evidence that the well-researched concepts of feature modeling are used in practice, but also that more advanced concepts are needed. We observe that assumptions about variability models in the literature do not hold. Our study also reveals that variability models work best in centralized variability management scenarios, and that they are fragile and have to be controlled by a small team. We also identify a particular type of dependencies that is increasingly used in open platforms and helps sustain the growth of ecosystems. Interestingly, while enabling distributed variability, these dependencies rely on a centralized and stable vocabulary. Finally, we formulate new hypotheses and research questions that provide direction for future research.

Les lignes de produits logiciels (LdPs) permettent la dérivation d'une famille de produits basés sur une gestion de la variabilité. Les LdPs utilisent des configurations de caractéristiques afin de satisfaire les besoins de chaque client et, de même, permettre une réutilisation systématique en utilisant des assets réutilisables. L’approche capitalisant sur des variantes des produits existants est appelé une approche extractive pour l'adoption de LdPs. L’identification des caractéristiques est nécessaire pour analyser la variabilité d’un ensemble de variantes. Il est également nécessaire de localiser les éléments associés à ces caractéristiques. Les contraintes entre ces caractéristiques doivent être identifiées afin de garantir la sélection de configurations valides. Par ailleurs, il faut construire les assets réutilisables et synthétiser un modèle de caractéristiques. Cette thèse présente BUT4Reuse (Bottom-Up Technologies for Reuse), un framework unifié, générique et extensible pour l’adoption extractive de LdPs. Une attention particulière est accordée à des scénarios de développement dirigée par les modèles. Nous nous concentrons aussi sur l'analyse des techniques en proposant un benchmark pour la localisation de caractéristiques et une technique d’identification de familles de variantes. Nous présentons des paradigmes de visualisation pour accompagner les experts du domaine dans le nommage de caractéristiques et aider à la découverte de contraintes. Finalement, nous étudions l'exploitation des variantes pour l'analyse de la LdP après sa création. Nous présentons une approche pour trouver des variantes pertinentes guidée par des évaluations des utilisateurs finaux. / Software Product Lines (SPLs) enable the derivation of a family of products based on variability management techniques. Inspired by the manufacturing industry, SPLs use feature configurations to satisfy different customer needs, along with reusable assets to allow systematic reuse. Capitalizing on existing variants by extracting the common and varying elements is referred to as extractive approaches for SPL adoption. Feature identification is needed to analyse the domain variability. Also, to identify the associated implementation elements of the features, their location is needed. In addition, feature constraints should be identified to guarantee that customers are not able to select invalid feature combinations. Then, the reusable assets associated to the features should be constructed. And finally, a comprehensive feature model need to be synthesized. This dissertation presents Bottom-Up Technologies for Reuse (BUT4Reuse), a unified, generic and extensible framework for mining software artefact variants. Special attention is paid to model-driven development scenarios. We also focus on benchmarks and in the analysis of variants, in particular, in benchmarking feature location techniques and in identifying families of variants in the wild for experimenting with feature identification techniques. We present visualisation paradigms to support domain experts on feature naming and to support on feature constraints discovery. Finally, we investigate and discuss the mining of artefact variants for SPL analysis once the SPL is already operational. Concretely, we present an approach to find relevant variants within the SPL configuration space guided by end user assessments.

Optimization is omnipresent in our world. Its numerous applications spread from industrial cases, such as logistics, construction management or production planning; to the private sphere, filled with problems of selecting daycare or vacation planning. In this thesis, we concentrate on expensive black-box optimization (EBBO) problems, a subset of optimization problems (OPs), which are characterized by an expensive cost of evaluating an objective function. Such OPs are reoccurring in various domains, being known as: hyperpameter optimization in machine learning, performance configuration optimization or parameter tuning in search-based software engineering, simulation optimization in operations research, meta-optimization or parameter tuning in the optimization domain itself. High diversity of domains introduces a plethora of solving approaches, which adhere to a similar structure and workflow, but differ in details. The software frameworks stemming from different areas possess only partially intersecting manageability points, i.e., lack manageability. In this thesis, we argue that the lack of manageability in EBBO is a major problem, which leads to underachieving optimization quality. The goal of this thesis is to study the role of manageability in EBBO and to investigate whether improving the manageability of EBBO frameworks increases optimization quality. To reach this goal, we appeal to software product line engineering (SPLE), a methodology for developing highly-manageable software systems. Based on the foundations of SPLE, we introduce a novel framework for EBBO called BRISE. It offers: 1) a loosely-coupled software architecture, separating concerns of the experiment designer and the developer of EBBO strategies; 2) a full coverage of all EBBO problem types; and 3) a context-aware variability model, which captures the experiment-designer-defined OP with the content model; and manageability points including their variants and constraints with the cardinality-based feature model. High manageability of the introduced BRISE framework enables us: 1) to extend the framework with novel efficient strategies, such as adaptive repetition management; and 2) to introduce novel EBBO mechanisms, such as multi-objective compositional surrogate modeling, dynamic sampling and hierarchical surrogate modeling. The evaluation of the novel approaches with a set of case studies, including: the WFG benchmark for multi-objective optimization, combined selection and parameter control of meta-heuristics, and energy optimization; demonstrated their superiority over the state-of-the-art competitors. Thus, it supports the research hypothesis of this thesis: Improving manageability of an EBBO framework enables to increase optimization quality.

Modern business applications are getting increasingly distributed as multi-tenant software as a service (SaaS). This leads to new challenges in terms of quality assurance, because all customers are directly affected by software changes. The resulting problem is to proactively determinate evolutionary effects. Because SaaS applications are often realized in the sense of a software product line, this thesis examines ways of using feature models to face the mentioned problem. For this purpose, two approaches are analyzed: extended feature models with quality attributes annotated per feature and the analysis of structural aspects of feature models and corresponding concrete configurations. The presented attributed feature model approach measures the quality of concrete configurations to make configurations comparable according to specific quality goals. Criteria are elicited for when configurations can be compared to draw helpful conclusions. The structural approach focuses economic questions that are quality assurance related, such as identifying features that none of the tenants selected in their application configurations. Furthermore, three algorithms are presented that demonstrate the structural analysis approach to gather information relevant to quality assurance.

To offer customisable software, there are two main concepts yet: software product lines that allow the product customisation based on a fixed set of variability and software ecosystems, allowing an open product customisation based on a common platform. Offering a software family that enables external developers to supply software artefacts means to offer a common platform as part of an ecosystem and to sacrifice variability control. Keeping full variability control means to offer a customisable product as a product line, but without the support for external contributors. This thesis proposes a third concept of variable software: partly open software families. They combine a customisable platform similar to product lines with controlled openness similar to ecosystems. As a major contribution of this thesis a variability modelling concept is proposed which is part of a variability management for these partly open software families. This modelling concept is based on feature models and extends them to support open variability modelling by means of interfaces, structural interface specifications and the inclusion of semantic information. Additionally, the introduction of a rights management allows multiple contributors to work with the model. This is required to enable external developers to use the model for the concrete extension development. The feasibility of the proposed model is evaluated using a prototypically developed modelling tool and by means of a case study based on a car infotainment system.