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- TextdokumentExplanations in Everyday Software Systems: Towards a Taxonomy for Explainability Needs(Software Engineering 2025, 2025) Droste, Jakob; Deters, Hannah; Obaidi, Martin; Schneider, KurtThe integration of explanations within software can address the opacity of complex systems, making them more understandable to end-users. Understanding what type of system requires what types of explanations is necessary to facilitate the consideration of explainability in early software design processes. In order to specify explainability requirements, an explainability taxonomy that applies to different software types is needed. Our work reports on the results of an online survey with 84 participants. We asked the participants to state their questions and confusions concerning their three most recently used software systems and elicited explainability needs from their statements. These needs were coded by three researchers. In total, we identified and classified 315 explainability needs from the survey answers.
- TextdokumentExploring Architectural Design Decisions in Mailing Lists and their Traceability to Issue Trackers(Software Engineering 2025, 2025) Soliman, MohamedSoftware developers commonly use mailing lists to communicate and discuss issues. Some of the emails discuss architectural design decisions (ADDs) to design the components of a system, or achieve quality attributes. In this paper, we explore (a) The types of ADDs in mailing lists, and their co-occurrences, and (b) Methods used by practitioners to discuss ADDs using both mailing lists and issue trackers (e.g. Jira). We applied qualitative methods, as well as deep learning classification to classify ADDs in mailing lists. Furthermore, we applied similarity algorithms to detect related ADDs between emails and issues. Our findings support empirically-grounded approaches to identify and classify ADDs in mailing lists and issue trackers for future system design.
- TextdokumentSoftware Engineering 2025 - Complete Volume(Software Engineering 2025, 2025)
- TextdokumentAdvanced Mutation Testing of Java Bytecode Using Model Transformation(Software Engineering 2025, 2025) Bockisch, Christoph; Dorn, Freya; Eren, Deniz; Lehmann, Sascha; Neufeld, Daniel; Taentzer, Gabriele
- TextdokumentAnalyzing the reproducibility of research-related Jupyter notebooks at scale(Software Engineering 2025, 2025) Mietchen, Daniel; Samuel, SheebaWe address computational reproducibility of publication-associated Jupyter notebooks at 3 levels: (i) using fully automated workflows, we analyzed the computational reproducibility of Jupyter notebooks associated with publications indexed in the biomedical literature repository PubMed Central. We identified such notebooks by mining the article’s full text, trying to locate them on GitHub, and attempting to rerun them in an environment as close to the original as possible. We documented reproduction success and exceptions and explored relationships between notebook reproducibility and variables related to the notebooks or publications. (ii) This study represents a reproducibility attempt in and of itself, using essentially the same methodology twice on PubMed Central over the course of 2 years, during which the corpus of Jupyter notebooks from articles indexed in PubMed Central has grown in a highly dynamic fashion. (iii) We imported the corpus into a knowledge graph with a public SPARQL endpoint that allows for fine-grained exploration of notebooks individually or in aggregation (e.g. by topic, by journal or by error type). In this talk, we zoom in on common problems and practices, highlight trends, and discuss potential improvements to Jupyter-related workflows associated with biomedical publications.
- TextdokumentLearning From Each Other: How Are Architectural Mistakes Communicated in Industry?(Software Engineering 2025, 2025) Wiese, Marion; Brand, Axel-Frederik; van Hoorn, AndréOwn experiences and faulty decisions can be an important source of information for software architects. The experiences and mistakes of other architects can also be valuable information sources. Under the assumption that the knowledge about faulty decisions, i.e., mistakes, regarding software architecture is not shared adequately in practice, this work qualitatively investigates the handling and particularly communication of those mistakes by software architects. We conducted a grounded-theory study in which we interviewed ten German software architects from various domains. We identified software architects’ definitions of architectural mistakes, their handling of these mistakes, and their preferred communication strategies regarding these mistakes. We found that architects communicate mistakes mainly within their project teams and seldom within or across companies. We derived strategies to make learning and prevention of mistakes more effective. To share experiences and knowledge beyond architects’ peer groups, companies should invest more effort in discussing mistakes more consciously and create an environment where mistakes can be discussed openly.
- TextdokumentThe vision of on-demand architectural knowledge systems as a decision-making companion(Software Engineering 2025, 2025) Razavian, Maryam; Paech, Barbara; Tang, AntonyIn this paper, we provide the vision of on-demand architectural knowledge systems (ODAKS) and research challenges for software architecture knowledge management. We argue that there are many issues in the management of architectural knowledge, which cannot be handled properly by the current architectural knowledge management systems (AKS). Furthermore, we discuss in detail the issues of human decision making which need to be taken into account by AKS. Based on literature review, analysis and synthesis of past research works from both areas, we derive our vision of ODAKS as decision making companion to the architect. ODAKS organize and provide relevant information and knowledge to the architect, but also provide an assistive conversation to assist decision making. ODAKS use probing to understand the architects’ goals and their questions, they suggest relevant knowledge and present reflective hints to mitigate human decision making issues, such as cognitive bias, cognitive limitations, as well as of design process aspects, such as problem solution co-evolution and the balance between intuitive and rational decision making. We present validated technologies and technologies under research that could be used in ODAKS’ implementation. We conclude with the main challenges for research on ODAKS.
- TextdokumentArchitecture-based Issue Propagation Analysis(Software Engineering 2025, 2025) Speth, Sandro; Krieger, Niklas; Heinrich, Robert; Becker, SteffenIn this paper, we presented an architecture-based analysis approach to predict potential issue propagation graphs when an issue is opened in a component’s issue management system. The results of our evaluation indicate that such an approach is suitable to identify issue propagations quickly. However, the overestimation highly depends on the quality of the modeled propagation rules. In future work, we plan to include more elements of the Gropius metamodel to increase the precision further and reduce our results’ overestimation. Furthermore, we plan to evaluate the trade-off between model-details and the increasing modeling effort to obtain good results.
- TextdokumentFormal Synthesis of Uncertainty Reduction Controllers(Software Engineering 2025, 2025) Carwehl, Marc; Imrie, Calum; Vogel, Thomas; Rodrigues, Genaina; Calinescu, Radu; Grunske, LarsIn this extended abstract, we summarise our work on the Parley approach and uncertainty reduction controllers. This work has been published under the title “Formal Synthesis of Uncertainty Reduction Controllers” at the Conference on Software Engineering for Adaptive and Self-Managing Systems (SEAMS’24).
- TextdokumentInnovating at the Intersection: Software Engineering for Science and Industry(Software Engineering 2025, 2025) Felderer, MichaelThis paper provides a summary of the keynote talk ’Innovating at the Intersection: Software Engineering for Science and Industry’ held at the conference Software Engineering 2025.