308 research outputs found

    Software Evolution for Industrial Automation Systems. Literature Overview

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    Software Architecture in Practice: Challenges and Opportunities

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    Software architecture has been an active research field for nearly four decades, in which previous studies make significant progress such as creating methods and techniques and building tools to support software architecture practice. Despite past efforts, we have little understanding of how practitioners perform software architecture related activities, and what challenges they face. Through interviews with 32 practitioners from 21 organizations across three continents, we identified challenges that practitioners face in software architecture practice during software development and maintenance. We reported on common software architecture activities at software requirements, design, construction and testing, and maintenance stages, as well as corresponding challenges. Our study uncovers that most of these challenges center around management, documentation, tooling and process, and collects recommendations to address these challenges.Comment: Preprint of Full Research Paper, the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE '23

    Ernst Denert Award for Software Engineering 2020

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    This open access book provides an overview of the dissertations of the eleven nominees for the Ernst Denert Award for Software Engineering in 2020. The prize, kindly sponsored by the Gerlind & Ernst Denert Stiftung, is awarded for excellent work within the discipline of Software Engineering, which includes methods, tools and procedures for better and efficient development of high quality software. An essential requirement for the nominated work is its applicability and usability in industrial practice. The book contains eleven papers that describe the works by Jonathan BrachthĂ€user (EPFL Lausanne) entitled What You See Is What You Get: Practical Effect Handlers in Capability-Passing Style, Mojdeh Golagha’s (Fortiss, Munich) thesis How to Effectively Reduce Failure Analysis Time?, Nikolay Harutyunyan’s (FAU Erlangen-NĂŒrnberg) work on Open Source Software Governance, Dominic Henze’s (TU Munich) research about Dynamically Scalable Fog Architectures, Anne Hess’s (Fraunhofer IESE, Kaiserslautern) work on Crossing Disciplinary Borders to Improve Requirements Communication, Istvan Koren’s (RWTH Aachen U) thesis DevOpsUse: A Community-Oriented Methodology for Societal Software Engineering, Yannic Noller’s (NU Singapore) work on Hybrid Differential Software Testing, Dominic Steinhofel’s (TU Darmstadt) thesis entitled Ever Change a Running System: Structured Software Reengineering Using Automatically Proven-Correct Transformation Rules, Peter WĂ€gemann’s (FAU Erlangen-NĂŒrnberg) work Static Worst-Case Analyses and Their Validation Techniques for Safety-Critical Systems, Michael von Wenckstern’s (RWTH Aachen U) research on Improving the Model-Based Systems Engineering Process, and Franz Zieris’s (FU Berlin) thesis on Understanding How Pair Programming Actually Works in Industry: Mechanisms, Patterns, and Dynamics – which actually won the award. The chapters describe key findings of the respective works, show their relevance and applicability to practice and industrial software engineering projects, and provide additional information and findings that have only been discovered afterwards, e.g. when applying the results in industry. This way, the book is not only interesting to other researchers, but also to industrial software professionals who would like to learn about the application of state-of-the-art methods in their daily work

    Ernst Denert Award for Software Engineering 2020

    Get PDF
    This open access book provides an overview of the dissertations of the eleven nominees for the Ernst Denert Award for Software Engineering in 2020. The prize, kindly sponsored by the Gerlind & Ernst Denert Stiftung, is awarded for excellent work within the discipline of Software Engineering, which includes methods, tools and procedures for better and efficient development of high quality software. An essential requirement for the nominated work is its applicability and usability in industrial practice. The book contains eleven papers that describe the works by Jonathan BrachthĂ€user (EPFL Lausanne) entitled What You See Is What You Get: Practical Effect Handlers in Capability-Passing Style, Mojdeh Golagha’s (Fortiss, Munich) thesis How to Effectively Reduce Failure Analysis Time?, Nikolay Harutyunyan’s (FAU Erlangen-NĂŒrnberg) work on Open Source Software Governance, Dominic Henze’s (TU Munich) research about Dynamically Scalable Fog Architectures, Anne Hess’s (Fraunhofer IESE, Kaiserslautern) work on Crossing Disciplinary Borders to Improve Requirements Communication, Istvan Koren’s (RWTH Aachen U) thesis DevOpsUse: A Community-Oriented Methodology for Societal Software Engineering, Yannic Noller’s (NU Singapore) work on Hybrid Differential Software Testing, Dominic Steinhofel’s (TU Darmstadt) thesis entitled Ever Change a Running System: Structured Software Reengineering Using Automatically Proven-Correct Transformation Rules, Peter WĂ€gemann’s (FAU Erlangen-NĂŒrnberg) work Static Worst-Case Analyses and Their Validation Techniques for Safety-Critical Systems, Michael von Wenckstern’s (RWTH Aachen U) research on Improving the Model-Based Systems Engineering Process, and Franz Zieris’s (FU Berlin) thesis on Understanding How Pair Programming Actually Works in Industry: Mechanisms, Patterns, and Dynamics – which actually won the award. The chapters describe key findings of the respective works, show their relevance and applicability to practice and industrial software engineering projects, and provide additional information and findings that have only been discovered afterwards, e.g. when applying the results in industry. This way, the book is not only interesting to other researchers, but also to industrial software professionals who would like to learn about the application of state-of-the-art methods in their daily work

    The Role of Complex Constraints in Feature Modeling: Master’s Thesis

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    Feature modeling is a method to compactly capture commonality and variability of a software product line. Multiple feature modeling languages have been proposed that evolved over the last decades to become more expressive in syntax and semantics. Most of today’s languages are capable of utilizing arbitrary propositional formulas in cross-tree constraints, denoted as complex constraints, a mechanism enabling complete expressiveness. However, many of today’s publications and feature model applications are targeting older, less expressive languages, due to their history and long domination in the product-line community. We present a study on the importance of complex constraints in feature modeling. Furthermore, to build a bridge between feature models using complex constraints and methods lacking support for complex constraints, we present a sound refactoring of complex constraints, discuss preconditions that must be met, and conduct empirical experiments on real-world feature models to evaluate its usefulness and scalability.Feature-Modellierung ist eine Methode, um Gemeinsamkeiten und VariabilitĂ€t einer Produktlinie in der Softwareentwicklung kompakt darzustellen. Über die letzten Jahrzehnte wurden verschiedene Sprachen fĂŒr die Feature-Modellierung vorgestellt, die sich sowohl syntaktisch als auch semantisch voneinander unterscheiden. Viele der heute eingesetzten Sprachen unterstĂŒtzen die Angabe beliebiger logischer AudrĂŒcke, so genannte komplexe Constraints, um orthogonale Beziehungen zwischen Features festzulegen. Komplexe Constraints geben einer Feature-Modellierungssprache volle AusdrucksmĂ€chtigkeit. Allerdings werden heutzutage immer noch eine große Menge an Methoden und Applikationen publiziert, die auf bekanntere Sprachen mit weniger AusdrucksmĂ€chtigkeit aufbauen. In dieser Arbeit untersuchen wir die Notwenidigkeit von komplexen Constraints in der Feature Modellierung. Zudem ĂŒberbrĂŒcken wir die Problematik zwischen neueren Sprachen mit komplexen Constraints und Methoden und Tools, die auf Ă€lteren Sprachen aufbauen, indem wir einen Ansatz prĂ€sentieren, um komplexe Constraints in Feature Modellen zu eliminieren. Wir diskutieren Vorbedingungen und evaluieren unseren Ansatz hinsichtlich Nutzen und Skalierbarkeit an Feature Modellen aus der realen Welt

    Grand Challenges of Traceability: The Next Ten Years

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    In 2007, the software and systems traceability community met at the first Natural Bridge symposium on the Grand Challenges of Traceability to establish and address research goals for achieving effective, trustworthy, and ubiquitous traceability. Ten years later, in 2017, the community came together to evaluate a decade of progress towards achieving these goals. These proceedings document some of that progress. They include a series of short position papers, representing current work in the community organized across four process axes of traceability practice. The sessions covered topics from Trace Strategizing, Trace Link Creation and Evolution, Trace Link Usage, real-world applications of Traceability, and Traceability Datasets and benchmarks. Two breakout groups focused on the importance of creating and sharing traceability datasets within the research community, and discussed challenges related to the adoption of tracing techniques in industrial practice. Members of the research community are engaged in many active, ongoing, and impactful research projects. Our hope is that ten years from now we will be able to look back at a productive decade of research and claim that we have achieved the overarching Grand Challenge of Traceability, which seeks for traceability to be always present, built into the engineering process, and for it to have "effectively disappeared without a trace". We hope that others will see the potential that traceability has for empowering software and systems engineers to develop higher-quality products at increasing levels of complexity and scale, and that they will join the active community of Software and Systems traceability researchers as we move forward into the next decade of research

    Software Engineering 2021 : Fachtagung vom 22.-26. Februar 2021 Braunschweig/virtuell

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    Grand Challenges of Traceability: The Next Ten Years

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    In 2007, the software and systems traceability community met at the first Natural Bridge symposium on the Grand Challenges of Traceability to establish and address research goals for achieving effective, trustworthy, and ubiquitous traceability. Ten years later, in 2017, the community came together to evaluate a decade of progress towards achieving these goals. These proceedings document some of that progress. They include a series of short position papers, representing current work in the community organized across four process axes of traceability practice. The sessions covered topics from Trace Strategizing, Trace Link Creation and Evolution, Trace Link Usage, real-world applications of Traceability, and Traceability Datasets and benchmarks. Two breakout groups focused on the importance of creating and sharing traceability datasets within the research community, and discussed challenges related to the adoption of tracing techniques in industrial practice. Members of the research community are engaged in many active, ongoing, and impactful research projects. Our hope is that ten years from now we will be able to look back at a productive decade of research and claim that we have achieved the overarching Grand Challenge of Traceability, which seeks for traceability to be always present, built into the engineering process, and for it to have "effectively disappeared without a trace". We hope that others will see the potential that traceability has for empowering software and systems engineers to develop higher-quality products at increasing levels of complexity and scale, and that they will join the active community of Software and Systems traceability researchers as we move forward into the next decade of research

    Test-driven development of embedded control systems: application in an automotive collision prevention system

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    With test-driven development (TDD) new code is not written until an automated test has failed, and duplications of functions, tests, or simply code fragments are always removed. TDD can lead to a better design and a higher quality of the developed system, but to date it has mainly been applied to the development of traditional software systems such as payroll applications. This thesis describes the novel application of TDD to the development of embedded control systems using an automotive safety system for preventing collisions as an example. The basic prerequisite for test-driven development is the availability of an automated testing framework as tests are executed very often. Such testing frameworks have been developed for nearly all programming languages, but not for the graphical, signal driven language Simulink. Simulink is commonly used in the automotive industry and can be considered as state-of-the-art for the design and development of embedded control systems in the automotive, aerospace and other industries. The thesis therefore introduces a novel automated testing framework for Simulink. This framework forms the basis for the test-driven development process by integrating the analysis, design and testing of embedded control systems into this process. The thesis then shows the application of TDD to a collision prevention system. The system architecture is derived from the requirements of the system and four software components are identiïŹed, which represent problems of particular areas for the realisation of control systems, i.e. logical combinations, experimental problems, mathematical algorithms, and control theory. For each of these problems, a concept to systematically derive test cases from the requirements is presented. Moreover two conventional approaches to design the controller are introduced and compared in terms of their stability and performance. The eïŹ€ectiveness of the collision prevention system is assessed in trials on a driving simulator. These trials show that the system leads to a signiïŹcant reduction of the accident rate for rear-end collisions. In addition, experiments with prototype vehicles on test tracks and ïŹeld tests are presented to verify the system’s functional requirements within a system testing approach. Finally, the new test-driven development process for embedded control systems is evaluated in comparison to traditional development processes
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