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.

Software security for agile methods, particularly for those designed for individual developers, is still a major concern. With most software products deployed over the Internet, security as a key component of software quality has become a major problem. In addressing this problem, this research proposes a solo software development methodology (SSDM) that uses as minimum resources as possible, at the same time conforming to the best practice for delivering secure and high-quality software products. Agile methods have excelled on delivering timely and quality software. At the same time research also shows that most agile methods do not address the problem of security in the developed software. A metasynthesis of SSDMs conducted in this thesis confirmed the lack practices that promote security in the developed software product. On the other hand, some researchers have demonstrated the feasibility of incorporating existing lightweight security practices into agile methods. This research uses Design Science Research (DSR) to build, demonstrate and evaluate a lightweight SSDM. Using an algorithm adapted for the purpose, the research systematically integrates lightweight security and quality practices to produce an agile secure-solo software development methodology (Secure-SSDM). A multiple-case study in an academic and industry setting is conducted to demonstrate and evaluate the utility of the methodology. This demonstration and evaluation thereof, indicates the applicability of the methodology in building high-quality and secure software products. Theoretical evaluation of the agility of the Secure-SSDM using the four-dimensional analytical tool (4-DAT) shows satisfactory compliance of the methodology with agile principles. The main contributions in this thesis are: the Secure-SSDM, which entails description of the concepts, modelling languages, stages, tasks, tools and techniques; generation of a quality theory on practices that promote quality in a solo software development environment; adaptation of Keramati and Mirian-Hosseinabadi’s algorithm for the purposes of integrating quality and security practices. This research would be of value to researchers as it introduces the security component of software quality into a solo software development environment, probing more research in the area. To software developers the research has provided a lightweight methodology that builds quality and security into the product using minimum resources. / School of Computing / D. Phil. (Computer Science)

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.

Der betriebliche Einsatz von Smart Glasses zur Unterstützung von manuellen Dienstleistungsprozessen bietet viele Vorteile, die mit anderen Technologien nicht erreicht werden können. Insbesondere im Bereich der Logistik kann von der Informationsversorgung bei gleichzeitiger Mobilität Gebrauch gemacht werden. Um dieses Potenzial auszunutzen, bedarf es allerdings Softwarelösungen, die auf die jeweiligen Anforderungen zugeschnitten sind. In dieser Forschungsarbeit wird daher untersucht, wie Smart-Glasses-basierte Informationssysteme zur Unterstützung der Logistik zu gestalten und zu implementieren sind. Die Forschungsarbeit folgt dabei zwei Zielen: (A) Die Unterstützung von Logistikprozessen durch Smart-Glasses-basierte Informationssysteme wird im Hinblick auf Anforderungen, Herausforderungen und Gestaltungsprinzipien untersucht, und (B) wird der Entwicklungsprozess zur Gestaltung und Implementierung von derartigen Informationssystemen im Rahmen eines Forschungsprojekts konzipiert und evaluiert. Das Vorgehen wird durch methodische Betrachtungen von Gestaltungsanforderungen und -prinzipien geleitet und entspricht so dem gestaltungsorientierten Forschungsansatz der Wirtschaftsinformatik. Die genauere Beantwortung der gestellten Forschungsfrage erfolgt in drei Schritten: (1) Methoden zur Initiierung von agilen Softwareprojekten und der Integration von Softwareentwicklung und -betrieb werden basierend auf der Wissensbasis agiler Methoden, Praktiken und Ansätze abgeleitet, (2) Grundlagen zur thematischen Fokussierung auf die Technologie Smart Glasses und die Anwendungsdomäne der Logistik werden durch multimethodische Studien geschaffen, und (3) werden entsprechende Systeme zur Mitarbeiterunterstützung instanziiert, evaluiert und die Forschungsergebnisse in ein Vorgehensframework zur Durchführung von Implementierungsprojekten überführt. Die vorliegende Dissertation trägt somit zur Wissensbasis der gestaltungsorientierten Wirtschaftsinformatik durch die erreichten Erkenntnisse zur Initiierung und Durchführung von Softwareentwicklungsprojekten zur Unterstützung von betrieblichen Prozessen durch Smart-Glasses-basierte Informationssysteme bei. Darüber hinaus bietet die Arbeit durch die bewusst praxisnahe Orientierung mit dem generierten Gestaltungswissen einen Mehrwert für Praktiker aus den betrachteten Bereichen, insbesondere für Stakeholder für die Einführung mobiler Informationssysteme in betrieblichen Umfeldern.

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.

Mobile applications are developed to run on fast-evolving platforms, such as Android or iOS. Respective mobile devices are heterogeneous concerning hardware (e.g., sensors, displays, communication interfaces) and software, especially operating system functions. Software vendors cope with platform evolution and various hardware configurations by abstracting from these variable assets. However, they cannot be sure about their assumptions on the inner conformance of all device parts and that the application runs reliably on each of them—in consequence, comprehensive testing is required. Thereby, in testing, variability becomes tedious due to the large number of test cases required to validate behavior on all possible device configurations. In this paper, we provide remedy to this problem by combining model-based testing with variability concepts from Software Product Line engineering. For this purpose, we use feature-based test modeling to generate test cases from variable operational models for individual application configurations and versions. Furthermore, we illustrate our concepts using the commercial mobile application “runtastic” as example application.

The thesis is devoted to the development of software for the system of optimal distribution of fuel and energy resources in the group of blast furnaces. In the course of work, the main stages of software development are considered: analysis of the subject area; creation of software architecture, user interface, database structure; development of algorithmic support and reference documentation; preparation of the distribution. The result of the work is a software product intended for the engineering and technological personnel of the blast furnace shop of the metallurgical plant. The results of the work can also be used in the educational process for training bachelors and undergraduates in the areas of "Metallurgy" and "Information Systems and Technologies". / Диссертационная работа посвящена разработке программного обеспечения системы оптимального распределения топливно-энергетических ресурсов в группе доменных печей. В ходе работы рассмотрены основные этапы разработки программного обеспечения: анализ предметной области; создание архитектуры программного обеспечения, пользовательского интерфейса, структуры базы данных; разработка алгоритмического обеспечения и справочной документации; подготовка дистрибутива. Результатом работы является программный продукт, предназначенный для инженерно-технологического персонала доменного цеха металлургического комбината. Результаты работы могут быть использованы также в учебном процессе для обучения бакалавров и магистрантов по направлениям «Металлургия» и «Информационные системы и технологии».