Lutz Prechelt

Lutz Prechelt is Professor of Informatics at Freie Universität Berlin where he heads the Software Engineering research group (AG SE). His academic journey spans theoretical foundations, industry experience, and extensive empirical research in software engineering. He has held significant administrative positions including Executive Director of the Institute of Informatics and member of various academic senates.

Prechelt's research interests have evolved from artificial intelligence and neural networks to empirical software engineering, with a recent focus on qualitative approaches to Agile processes and Pair Programming. His work has consistently emphasized methodological rigor, having conducted pioneering controlled experiments on topics like type-checking, inheritance depth, design patterns, and the Personal Software Process. His research has also ventured into plagiarism detection (JPlag), melody recognition, and qualitative studies of pair programming dynamics.

His publication record shows a clear transition from quantitative to qualitative approaches in empirical software engineering. Early work featured controlled experiments on specific technical aspects of software development, while more recent publications focus on qualitative analysis of team dynamics, agile methodologies, and research methodology itself. A notable thread throughout his career has been platform comparison studies (Plat_Forms) examining how different technologies affect development outcomes.

• Ernst Denert Software Engineering Award 2020

Prechelt has served extensively as reviewer for major funding agencies including DFG, EU, ERC, and BMBF, and as editor for journals like Journal of Universal Computer Science and Transactions on Pattern Languages of Programming. He founded the Forum for Negative Results (FNR) to address publication bias in scientific research. His research group has developed several notable software tools including Saros for distributed pair programming, JPlag for plagiarism detection, and tools for maintainable lecture videos.