Model Based Performance Prediction For Concurrent Software On Multicore Architectures A Simulation Based Approach

Die modellbasierte Performancevorhersage ist ein bekanntes Konzept zur Gewährleistung der Softwarequalität. Derzeitige Ansätze basieren auf einem Modell mit einer Metrik, was zu ungenauen Vorhersagen für moderne Architekturen führt. In dieser Arbeit wird ein Multi-Strategie-Ansatz zur Erweiterung von Performancevorhersagemodellen zur Unterstützung von Multicore-Architekturen vorgestellt, in Palladio implementiert und dadurch die Genauigkeit der Vorhersage deutlich verbessert. - Model-based performance prediction is a well-known concept to ensure the quality of software. Current approaches are based on a single-metric model, which leads to inaccurate predictions for modern architectures. This thesis presents a multi-strategies approach to extend performance prediction models to support multicore architectures. We implemented the strategies into Palladio and significantly increased the performance prediction power.

In this work, the authors analysed the co-dependency between models and analyses, particularly the structure and interdependence of artefacts and the feature-based decomposition and composition of model-based analyses. Their goal is to improve the maintainability of model-based analyses. They have investigated the co-dependency of Domain-specific Modelling Languages (DSMLs) and model-based analyses regarding evolvability, understandability, and reusability.

Although tremendous progress has been made in Artificial Intelligence (AI), it entails new challenges. The growing complexity of learning tasks requires more complex AI components, which increasingly exhibit unreliable behaviour. In this book, we present a model-driven approach to model architectural safeguards for AI components and analyse their effect on the overall system reliability.

This cumulative habilitation thesis, proposes concepts for (i) modelling and analysing dependability based on architectural models of software-intensive systems early in development, (ii) decomposition and composition of modelling languages and analysis techniques to enable more flexibility in evolution, and (iii) bridging the divergent levels of abstraction between data of the operation phase, architectural models and source code of the development phase.

Developing variable systems faces many challenges. Dependencies between interrelated artifacts within a product variant, such as code or diagrams, across product variants and across their revisions quickly lead to inconsistencies during evolution. This work provides a unification of common concepts and operations for variability management, identifies variability-related inconsistencies and presents an approach for view-based consistency preservation of variable systems.

Software vendors must consider confidentiality especially while creating software architectures because decisions made here are hard to change later. Our approach represents and analyzes data flows in software architectures. Systems specify data flows and confidentiality requirements specify limitations of data flows. Software architects use detected violations of these limitations to improve the system. We demonstrate how to integrate our approach into existing development processes.

Business processes and information systems evolve constantly and affect each other in non-trivial ways. Aligning security requirements between both is a challenging task. This work presents an automated approach to extract access control requirements from business processes with the purpose of transforming them into a) access permissions for role-based access control and b) architectural data flow constraints to identify violations of access control in enterprise application architectures.

The four-volume set LNCS 11244, 11245, 11246, and 11247 constitutes the refereed proceedings of the 8th International Symposium on Leveraging Applications of Formal Methods, Verification and Validation, ISoLA 2018, held in Limassol, Cyprus, in October/November 2018. The papers presented were carefully reviewed and selected for inclusion in the proceedings. Each volume focusses on an individual topic with topical section headings within the volume: Part I, Modeling: Towards a unified view of modeling and programming; X-by-construction, STRESS 2018. Part II, Verification: A broader view on verification: from static to runtime and back; evaluating tools for software verification; statistical model checking; RERS 2018; doctoral symposium. Part III, Distributed Systems: rigorous engineering of collective adaptive systems; verification and validation of distributed systems; and cyber-physical systems engineering. Part IV, Industrial Practice: runtime verification from the theory to the industry practice; formal methods in industrial practice - bridging the gap; reliable smart contracts: state-of-the-art, applications, challenges and future directions; and industrial day.