Auflistung P279 - Software Engineering und Software Management 2018 nach Erscheinungsdatum
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- KonferenzbeitragModularity and architecture of PLC-based software for automated production Systems(Software Engineering und Software Management 2018, 2018) Vogel-Heuser, Birgit; Fischer, Juliane; Feldmann, Stefan; Ulewicz, Sebastian; Rösch, Susanne; Bougouffa, SafaAdaptive and flexible production systems require modular and reusable software, especially considering their long-term life cycle of up to 50 years. We introduce a benchmark process – so-called SWMAT4aPS – to measure software maturity for industrial control software of automated production systems.
- KonferenzbeitragEmpirical Evaluation of a Domain-Specific Language for High-Performance Marine Ecosystem Simulation(Software Engineering und Software Management 2018, 2018) Johanson, Arne; Hasselbring, WilhelmIn this paper, we report on the empirical evaluation of domain-specific languages by evaluating the Sprat Ecosystem DSL for its effectiveness and efficiency.
- Konferenzbeitrag1st Workshop on Innovative Software Engineering Education (ISEE)(Software Engineering und Software Management 2018, 2018) Krusche, Stephan; Kuhrmann, Marco; Schneider, KurtDue to the growing numbers of students, courses can no longer be offered in high quality without systematic approaches. Hence, this workshop aims at presenting and discussing innovative teaching approaches in software engineering education, which are highly relevant for teaching at universities, colleges, and in online courses.
- KonferenzbeitragSoftware Engineering und Software Management 2018(Software Engineering und Software Management 2018, 2018)
- KonferenzbeitragContinuous Innovation and Experimentation in Complex Problem Domains(Software Engineering und Software Management 2018, 2018) Klepper, Sebastian; Grimm, Christian; Bruegge, BerndContinuous software engineering enables experimentation and empirical research in complex problem domains. Existing process models describe different approaches for exploration, innovation, and refinement. We propose a new approach based on problem solving techniques and focused on decision support to serve as the starting point for a unified process framework.
- KonferenzbeitragAgile Software Quality Function Deployment(Software Engineering und Software Management 2018, 2018) Schockert, Sixten; Herzwurm, GeorgUser Stories repräsentieren das wesentliche Artefakt der Kommunikation von Anforderungen in einer agilen Entwicklung. Und unabhängig davon, ob sie sich als präzise Anforderungen für die Entwickler eignen, auf Basis der User Stories im Product Backlog wird entschieden, was in der nächsten Iteration umgesetzt wird und was nicht. Von daher muss ein Agiles Requirements Engineering Wege aufzeigen, gute User Stories zu finden, zu entwerfen und die gemäß Business Value vielversprechendsten für die Implementierung in der nächsten Iteration auszuwählen. Das ist entscheidend für eine nicht nur effiziente, sondern auch effektive agile Entwicklung, die an den wichtigsten Anforderungen ansetzt und nicht „nur“ plausible User Stories zügig umsetzt. Dieser Beitrag stellt dazu das Agile Software Quality Function Deployment (QFD) vor. Es basiert auf 27 Gestaltungsanforderungen, abgeleitet aus den Prinzipien und Werten der agilen Softwareentwicklung, dem Umgang mit Anforderungen in agilen Entwicklungsmodellen und empirischen Quellen des agilen Requirements Engineering. Den Vorschlag zum Agilen Software QFD kennzeichnen die nahtlose Einbettung in den agilen Iterationszyklus und besondere methodische Merkmale wie die inkrementell wachsende Priorisierungsmatrix und die Priority Map. Bewertet gegen die Gestaltungsanforderungen und verglichen mit weit verbreiteten Techniken des agilen Requirements Engineering kann das Agile Software QFD durch die konsequente Ausrichtung an den wichtigsten Stakeholderbedürfnissen, der Suche nach alternativen und besseren Lösungen sowie der engen Zusammenarbeit mit den Kunden/Nutzern einen Mehrwert für die agile Entwicklung darstellen. Agiles Software QFD verkörpert damit den Gestaltungsanspruch des Requirements Engineering in einer agilen Softwareentwicklung und ist Ausdruck eines am Business Value orientierten agilen Requirements Engineering.
- KonferenzbeitragSearching for Common Ground(Software Engineering und Software Management 2018, 2018) Hohl, Philipp; Ghofrani, Javad; Münch, Jürgen; Stupperich, Michael; Schneider, KurtIn Proceedings of 2017 International Conference on Software and Systems Process, Paris, France, July 2017 (ICSSP’17), 10 pages. DOI: 10.1145/3084100.3084109 Automotive development processes are significantly influenced by digital transformation and need to be adapted. Agile methods are a promising approach but they are not tailored to the specific characteristics of the automotive domain like product line development. Although, there have been efforts to apply agile methods in the automotive domain, widespread adoptions have not yet taken place. This literature review gives an overview of agile methods for embedded software development in the automotive domain, especially with respect to software product lines (SPLs). A mapping study was conducted to analyze the relation between agile software development (ASD), automotive embedded software development and SPLs. Three research questions were defined and 68 papers were evaluated. The study shows that ASD and SPL approaches tailored for the automotive domain are not yet fully explored in the literature. Only few approaches for combining ASD and SPLs in the automotive domain were found, these findings were valuable for identifying research gaps and provide insights into how existing approaches can be combined, extended and tailored to suit the characteristics of the automotive domain.
- KonferenzbeitragReporting on a Survey on Approaches to Co-Evolution of Metamodels and Models(Software Engineering und Software Management 2018, 2018) Hebig, Regina; Khelladi, Djamel Eddine; Bendraou, RedaThe paper was published in 2016 in IEEE Transactions on Software Engineering (http://dx.doi.org/10.1109/TSE.2016.2610424). Modeling languages, just as all software artifacts, evolve. This poses the risk that legacy models of a company get lost, when they become incompatible with the new language version. To address this risk, a multitude of approaches for metamodel-model co-evolution were proposed in the last 10 years. However, the high number of solutions makes it difficult for practitioners to choose an appropriate approach. In this paper, we present a survey on 31 approaches to support metamodel-model co-evolution. We introduce a taxonomy of solution techniques and classify the existing approaches. To support researchers, we discuss the state of the art, in order to better identify open issues. Furthermore, we use the results to provide a decision support for practitioners, who aim to adopt solutions from research.
- KonferenzbeitragGenerating Explanations for Algorithmic Decisions of Usage-Based Insurances using Natural Language Generation(Software Engineering und Software Management 2018, 2018) Braun, Daniel; Matthes, FlorianUsage-based insurances are becoming more and more popular, especially for cars. These so called telematics insurances use different sensors installed in a car to track the individual driving style of the driver. Instead of calculating insurance premiums based on statistical risk groups, insurance companies can use these data to create individual risk profiles and calculate insurance premiums accordingly. We present an approach to use Natural Language Generation (NLG) in order to explain customers which aspects of their behaviour influenced the assessment of the algorithm. In this way, we can not only increase the acceptance of customers regarding such systems, but also positively influence their future behaviour.
- KonferenzbeitragReinforcement Learning for Automatic Test Case Prioritization and Selection in Continuous Integration(Software Engineering und Software Management 2018, 2018) Spieker, Helge; Gotlieb, Arnaud; Marijan, Dusica; Mossige, MortenThe paper appeared at the International Symposium on Software Testing and Analysis (ISSTA 2017). It is part of a project on test case prioritization, selection, and execution in Continuous Integration (CI). Selecting the most promising test cases to detect bugs is hard if there are uncertainties on the impact of committed code changes or if traceability links between code and tests are not available. This paper introduces Retecs, a new method for automatically learning test case selection and prioritization in CI with the goal to minimize the round-trip time between code commits and developer feedback on failed test cases. Retecs uses reinforcement learning to select and prioritize test cases according to their duration, previous last execution and failure history. In a constantly changing environment, where new test cases are created and obsolete test cases are deleted, the Retecs method learns to prioritize error-prone test cases higher under the guidance of a reward function and by observing previous CI cycles. By application on three industrial case studies, we show for the first time that reinforcement learning enables fruitful automatic adaptive test case selection and prioritization in CI and regression testing.