Auflistung Softwaretechnik-Trends 43(2) - 2023 nach Titel
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- ZeitschriftenartikelAdapter-Muster(Softwaretechnik-Trends Band 43, Heft 2, 2023) Herrmann, AndreaIm Adapter-Muster behebt die Adapter-Klasse Kompatibilitätsprobleme zwischen Klassen.
- KonferenzbeitragBest Student Paper Award des 25. Workshop Software-Reengineering und -Evolution(Softwaretechnik-Trends Band 43, Heft 2, 2023) Quante, Jochen; Konersmann, Marco; Sauer, Stefan; Schilling, Daniela; Schulze, SandroZum 25. Workshop Software-Reengineering und -Evolution (WSRE) wurde durch die Fach gruppe Software-Reengineering zum zweiten Mal nach 2022 der Preis für den besten studentischen Beitrag ausgelobt. Der Best Student Paper Award ist mit einem Preisgeld in Höhe von 250 € verbunden, das die Sponsoren bereitstellen. Wir gratulieren Ulrike Engeln als Gewinnerin des Best Student Paper Awards des WSRE 2023.
- Konferenz-AbstractCall for Papers: 2nd International Workshop on Requirements Engineering Frameworks REFrame auf der IEEE Requirements Engineering Conference RE 2023(Softwaretechnik-Trends Band 43, Heft 2, 2023) Birk, AndreasCall for Papers: 2nd International Workshop on Requirements Engineering Frameworks REFrame auf der IEEE Requirements Engineering Conference RE 2023
- Konferenz-AbstractCall for Papers: Fachgruppentreffen Requirements Engineering(Softwaretechnik-Trends Band 43, Heft 2, 2023) Karras, OliverCall for Papers: Fachgruppentreffen Requirements Engineering
- KonferenzbeitragCode Smell Detection using Features from Version History(Softwaretechnik-Trends Band 43, Heft 2, 2023) Engeln, UlrikeCode smells are indicators for bad quality of source code. A well suited approach for the development of a smell detector are machine learning techniques that learn based on features, i.e., measurable properties of the software under investigation, e.g., code metrics. One major objective of our machine learning approach is to decide how to express information from the version history by features. we introduce a method to draw historical features that improve smell detection.
- KonferenzbeitragCollaborative software visualization with SEE(Softwaretechnik-Trends Band 43, Heft 2, 2023) Behnke, William; Kuß, Hannes LennartSEE is a software engineering tool for visualizing software metrics based on the code-cities metaphor. It assists distributed teams in analyzing software collaboratively by offering multi-user functionality (including a voice chat), that allows team members to communicate naturally while investigating software. The tool utilizes graphs supplied in the Graph eXchange Language (GXL) format to represent software data, and allows users—among other things—to compare the current architecture with the original plan and to track changes of a software over time. One of our long-term goals is to enhance communication and collaboration among team members, to bridge spatial gaps, and to facilitate the understanding of software in (spatially separated) teams.
- KonferenzbeitragCommit-Based Continuous Integration of Performance Models(Softwaretechnik-Trends Band 43, Heft 2, 2023) Armbruster, MartinArchitecture-level performance models (aPM) such as the Palladio Component Model (PCM) can be used for, e.g., performance predictions to explore design alternatives and combines the aspects of architecture and performance models. An up-to-date architecture model can support the software maintenance by reducing the architectural degradation or guide the software evolution. At the same time, performance models allow the investigation of the software performance without the need to implement or change the system. However, keeping them up-to-date requires manual effort which hinders their adoption. Especially in the agile software development which is characterized by incremental and iterative development cycles, no or short design phases prevent manual modeling activities. This master thesis presents an approach building upon the previous work with these two main goals: (1) closing the gaps by completing the pipeline for the aPM extraction and instrumentation, and (2) evaluating the pipeline with a real Git history. As a result, in the approach, the Java source code in the state of a new commit is parsed into a code model. By a state-based comparison with the code model of the previous commit, a delta-based change sequence is obtained which describes how the code model of the previous commit can be transformed into a code model conforming to the state of the new commit. Afterwards, the changes are utilized to incrementally update the PCM, i.e., only the PCM elements affected by the source code changes are updated while the other PCM elements remain unchanged.
- KonferenzbeitragDeveloping the Software of Future Cars: A Car DevOps Approach(Softwaretechnik-Trends Band 43, Heft 2, 2023) Weller, Marcel; Stötzner, Miles; Klinaku, Floriment; Becker, SteffenThe amount of deployed software in cars is increasing. Simultaneously, software is updated in shorter release cycles. As a consequence, car manufacturers face new challenges in the management of software. The project Software-Defined Car (SofDCar) consists of academic and industrial partners addressing the development of foundations for a new software development methodology for future car generations. This methodology demands for new roles and continuous engineering activities during the whole car software’s lifecycle. As part of this project, we research several interconnected topics addressing these challenges. We focus on the modeling and orchestration of car fleets, which includes topics such as variant management of car topologies and Over-the-Air updates. Furthermore, the communication between cars and surrounding systems is investigated for use cases such as cooperative overtaking in which cars autonomously overtake each other. Finally, we put all contributions together in a Car DevOps approach.
- KonferenzbeitragExperiences with Using a Pre-Trained Programming Language Model for Reverse Engineering Sequence Diagrams(Softwaretechnik-Trends Band 43, Heft 2, 2023) Greiner, Sandra; Maier, Nicolas; Kehrer, TimoReverse engineering software models from program source code has been extensively studied for decades. Still, most model-driven reverse engineering approaches cover only single programming languages and cannot be transferred to others easily. Large pre-trained AI transformer models which were trained on several programming languages promise to translate source code from one language into another (e.g., Java to Python). Thus, we fine-tuned such a pre-trained model (CodeT5) to extract sequence diagrams from Java code and examined whether it can perform the same task for Python without additional training.
- KonferenzbeitragGenerierte Anwendung modernisieren – Reengineering für Fortgeschrittene?(Softwaretechnik-Trends Band 43, Heft 2, 2023) Schilling, DanielaGeneratoren haben in der Software-Entwicklung eine lange Historie. Bis heute werden Generatoren aus den 1970er und 80er Jahren eingesetzt, um große und komplexe Anwendungen zu erzeugen. Durch ihre lange Lebensdauer haben auch generierte Anwendung Modernisierungsbedarf. Allerdings ist es hierfür notwendig, Reengineering-Methoden auf den Generator anzuwenden, statt auf die generierte Anwendung, wodurch neue Herausforderungen an den Ansatz entstehen.
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