Autor*innen mit den meisten Dokumenten
Auflistung nach:
Neueste Veröffentlichungen
- TextdokumentThe Effects of Computational Resources on Flaky Tests(Software Engineering 2025, 2025) Silva, Denini; Gruber, Martin; Gokhale, Satyajit; Arteca, Ellen; Turcotte, Alexi; D'Amorim, Marcelo; Lam, Wing; Winter, Stefan; Bell, Jonathan
- TextdokumentSoftware Engineering 2025 - Complete Volume(Software Engineering 2025, 2025)
- 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.
- TextdokumentPromoting Open Science in Test-driven Software Experiments(Software Engineering 2025, 2025) Kessel, Marcus; Atkinson, Colin
- TextdokumentCurrent Trends in Digital Twin Development, Maintenance, and Operation: An Interview Study(Software Engineering 2025, 2025) Muctadir, Hossain Muhammad; Negrin, David M.; Gunasekaran, Raghavendran; Cleophas, Loek; van den Brand, Mark; Haverkort, BoudewijnThis talk is based on our paper entitled “Current Trends in Digital Twin development, maintenance, and operation: An interview study” published in the Journal of Software and Systems Modeling in April 2024.
- TextdokumentModeling Variability in Complex Software Systems(Software Engineering 2025, 2025) Damiani, Ferruccio; Hähnle, Reiner; Kamburjan, Eduard; Lienhardt, Michaël; Paolini, LucaA Software Product Line (SPL) is a family of related programs, called variants, generated from a common artifact base. A Multi SPL (MPL) is a set of interdependent SPLs: Each variant may depend on variants from other SPLs. MPLs occur frequently in practice and are challenging to model and implement efficiently when different variants of the same SPL must coexist and interoperate. We address this by introducing the concept of a variability module (VM), a new language construct. A VM constitutes at the same time a module and an SPL of standard (variability-free), possibly interdependent, modules. A set of interdependent VMs represents an MPL that can be compiled into a set of standard modules. We instantiate the concept of a VM for the modeling language ABS.
- TextdokumentVariability Modeling of Products, Processes, and Resources in Cyber-Physical Production Systems Engineering(Software Engineering 2025, 2025) Meixner, Kristof; Feichtinger, Kevin; Fadhlillah, Hafiyyan Sayyid; Greiner, Sandra; Marcher, Hannes; Rabiser, Rick; Biffl, StefanThis summary of a paper (with the same title) initially published in the Journal on Systems and Software (JSS) discusses efficient variability exploration of products, production processes, and production resources in engineering Cyber-Physical Production Systems.
- TextdokumentHow Does Simulation-Based Testing for Self-Driving Cars Match Human Perception?(Software Engineering 2025, 2025) Birchler, Christian; Mohammed, Tanzil Kombarabettu; Rani, Pooja; Nechita, Teodora; Kehrer, Timo; Panichella, SebastianoSoftware metrics such as coverage or mutation scores have been investigated for the automated quality assessment of test suites. While traditional tools rely on software metrics, the field of self-driving cars (SDCs) has primarily focused on simulation-based test case generation using quality metrics such as the out-of-bound (OOB) parameter to determine if a test case fails or passes. However, it remains unclear to what extent this quality metric aligns with the human perception of the safety and realism of SDCs. To address this (reality) gap, we conducted an empirical study involving 50 participants to investigate the factors that determine how humans perceive SDC test cases as safe, unsafe, realistic, or unrealistic. To this aim, we developed a framework leveraging virtual reality (VR) technologies, called SDC-Alabaster, to immerse the study participants into the virtual environment of SDC simulators. Our findings indicate that the human assessment of safety and realism of failing/passing test cases can vary based on different factors, such as the test’s complexity and the possibility of interacting with the SDC. Especially for the assessment of realism, the participants’ age leads to a different perception. This study highlights the need for more research on simulation testing quality metrics and the importance of human perception in evaluating SDCs.