61 citations · 72 across the 6 of their papers we have counts for
6 papers
Evaluating the Impact of Explainable AI on Trust in AI-Assisted Code Review
Zhenhan Gao, Marvin Muñoz Barón, Umm-e Habiba +2
Background: Large language models (LLMs) are increasingly used to automate code review, but the reasoning behind their decisions remains hard to understand. Developers struggle to…
Guidelines for Empirical Studies in Software Engineering involving Large Language Models
Sebastian Baltes, Florian Angermeir, Chetan Arora +19
Large Language Models (LLMs) are widely used in software engineering (SE) research and practice, yet their non-determinism, opaque training data, and rapidly evolving models threat…
Towards Evaluation Guidelines for Empirical Studies involving LLMs
Stefan Wagner, Marvin Muñoz Barón, Davide Falessi +1
In the short period since the release of ChatGPT, large language models (LLMs) have changed the software engineering research landscape. While there are numerous opportunities to u…
Apples, Oranges, and Software Engineering: Study Selection Challenges for Secondary Research on Latent Variables
Marvin Wyrich, Marvin Muñoz Barón, Justus Bogner
Software engineering (SE) is full of abstract concepts that are crucial for both researchers and practitioners, such as programming experience, team productivity, code comprehensio…
Evidence Profiles for Validity Threats in Program Comprehension Experiments
Marvin Muñoz Barón, Marvin Wyrich, Daniel Graziotin +1
Searching for clues, gathering evidence, and reviewing case files are all techniques used by criminal investigators to draw sound conclusions and avoid wrongful convictions. Simila…
An Empirical Validation of Cognitive Complexity as a Measure of Source Code Understandability
Marvin Muñoz Barón, Marvin Wyrich, Stefan Wagner
Background: Developers spend a lot of their time on understanding source code. Static code analysis tools can draw attention to code that is difficult for developers to understand.…