output
20132026
most citedRethinking Sustainability Requirements: Drivers, Barriers and Impacts of Digitalisation from the Viewpoint of Experts

169 citations

71 papers

cs.SE2026

Causal Software Engineering: A Vision and Roadmap

Roberto Pietrantuono, Luca Giamattei, Stefano Russo +2

Software engineering increasingly involves making high-stakes decisions under uncertainty, using signals from code, field data, and socio-technical processes. Recent AI-driven supp…

cs.SE2025★ 9 cited

Greening AI-enabled Systems with Software Engineering: A Research Agenda for Environmentally Sustainable AI Practices

Luís Cruz, João Paulo Fernandes, Maja H. Kirkeby +22

The environmental impact of Artificial Intelligence (AI)-enabled systems is increasing rapidly, and software engineering plays a critical role in developing sustainable solutions.…

quant-ph2024★ 4 cited

QCEDA: Using Quantum Computers for EDA

Matthias Jung, Sven O. Krumke, Christof Schroth +2

The field of Electronic Design Automation (EDA) is crucial for microelectronics, but the increasing complexity of Integrated Circuits (ICs) poses challenges for conventional EDA: C…

cs.SE2023

Operationalizing Assurance Cases for Data Scientists: A Showcase of Concepts and Tooling in the Context of Test Data Quality for Machine Learning

Lisa Jöckel, Michael Kläs, Janek Groß +8

Assurance Cases (ACs) are an established approach in safety engineering to argue quality claims in a structured way. In the context of quality assurance for Machine Learning (ML)-b…

eess.SY2023★ 11 cited

Risk Management Core -- Towards an Explicit Representation of Risk in Automated Driving

Nayel Fabian Salem, Thomas Kirschbaum, Marcus Nolte +4

While current automotive safety standards provide implicit guidance on how unreasonable risk can be avoided, manufacturers are required to specify risk acceptance criteria for Auto…

cs.SE2022★ 37 cited

Applications of statistical causal inference in software engineering

Julien Siebert

This paper reviews existing work in software engineering that applies statistical causal inference methods. These methods aim at estimating causal effects from observational data.…