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A Reference Structure for Modular Model-based Analyses

A Reference Structure for Modular Model-based Analyses
Author: Koch, Sandro Giovanni
Publisher: KIT Scientific Publishing
Total Pages: 398
Release: 2024-04-25
Genre:
ISBN: 3731513412

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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.


Composing Model-Based Analysis Tools

Composing Model-Based Analysis Tools
Author: Robert Heinrich
Publisher: Springer Nature
Total Pages: 311
Release: 2021-12-02
Genre: Computers
ISBN: 3030819159

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This book presents joint works of members of the software engineering and formal methods communities with representatives from industry, with the goal of establishing the foundations for a common understanding of the needs for more flexibility in model-driven engineering. It is based on the Dagstuhl Seminar 19481 „Composing Model-Based Analysis Tools“, which was held November 24 to 29, 2019, at Schloss Dagstuhl, Germany, where current challenges, their background and concepts to address them were discussed. The book is structured in two parts, and organized around five fundamental core aspects of the subject: (1) the composition of languages, models and analyses; (2) the integration and orchestration of analysis tools; (3) the continual analysis of models; (4) the exploitation of results; and (5) the way to handle uncertainty in model-based developments. After a chapter on foundations and common terminology and a chapter on challenges in the field, one chapter is devoted to each of the above five core aspects in the first part of the book. These core chapters are accompanied by additional case studies in the second part of the book, in which specific tools and experiences are presented in more detail to illustrate the concepts and ideas previously introduced. The book mainly targets researchers in the fields of software engineering and formal methods as well as software engineers from industry with basic familiarity with quality properties, model-driven engineering and analysis tools. From reading the book, researchers will receive an overview of the state-of-the-art and current challenges, research directions, and recent concepts, while practitioners will be interested to learn about concrete tools and practical applications in the context of case studies.


Model-Based Performance Prediction for Concurrent Software on Multicore Architectures---A Simulation-Based Approach

Model-Based Performance Prediction for Concurrent Software on Multicore Architectures---A Simulation-Based Approach
Author: Frank, Markus Kilian
Publisher: KIT Scientific Publishing
Total Pages: 400
Release: 2022-07-18
Genre: Computers
ISBN: 3731511460

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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.


Architecture-based Evolution of Dependable Software-intensive Systems

Architecture-based Evolution of Dependable Software-intensive Systems
Author: Heinrich, Robert
Publisher: KIT Scientific Publishing
Total Pages: 154
Release: 2023-06-05
Genre:
ISBN: 3731512947

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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.


Building Transformation Networks for Consistent Evolution of Interrelated Models

Building Transformation Networks for Consistent Evolution of Interrelated Models
Author: Klare, Heiko
Publisher: KIT Scientific Publishing
Total Pages: 596
Release: 2022-03-24
Genre: Computers
ISBN: 3731511320

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Complex software systems are described with multiple artifacts, such as code, design diagrams and others. Ensuring their consistency is crucial and can be automated with transformations for pairs of artifacts. We investigate how developers can combine independently developed and reusable transformations to networks that preserve consistency between more than two artifacts. We identify synchronization, compatibility and orchestration as central challenges, and we develop approaches to solve them.


Context-based Access Control and Attack Modelling and Analysis

Context-based Access Control and Attack Modelling and Analysis
Author: Walter, Maximilian
Publisher: KIT Scientific Publishing
Total Pages: 350
Release: 2024-07-03
Genre:
ISBN: 3731513625

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This work introduces architectural security analyses for detecting access violations and attack paths in software architectures. It integrates access control policies and vulnerabilities, often analyzed separately, into a unified approach using software architecture models. Contributions include metamodels for access control and vulnerabilities, scenario-based analysis, and two attack analyses. Evaluation demonstrates high accuracy in identifying issues for secure system development.


Consistent View-Based Management of Variability in Space and Time

Consistent View-Based Management of Variability in Space and Time
Author: Ananieva, Sofia
Publisher: KIT Scientific Publishing
Total Pages: 310
Release: 2022-12-06
Genre: Computers
ISBN: 3731512416

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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.


Architectural Data Flow Analysis for Detecting Violations of Confidentiality Requirements

Architectural Data Flow Analysis for Detecting Violations of Confidentiality Requirements
Author: Seifermann, Stephan
Publisher: KIT Scientific Publishing
Total Pages: 412
Release: 2022-12-09
Genre: Computers
ISBN: 3731512467

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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.


Evaluating Architectural Safeguards for Uncertain AI Black-Box Components

Evaluating Architectural Safeguards for Uncertain AI Black-Box Components
Author: Scheerer, Max
Publisher: KIT Scientific Publishing
Total Pages: 472
Release: 2023-10-23
Genre:
ISBN: 373151320X

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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.