Prof. Dr. Sven Apel holds the Chair of Software Engineering at Saarland University & Saarland Informatics Campus, Germany. Prof. Apel received a Ph.D. in Computer Science in 2007 from the University of Magdeburg. His research interests include software product lines, software analysis, optimization, and evolution, as well as empirical methods and the human factor in software engineering. He is the author or co-author of over two hundred peer-reviewed scientific publications. He serves regularly in program committees of top-ranked international conferences, and he is a member of the editorial boards of Empirical Software Engineering and IEEE Software. He was PC co-chair of the 31st International Conference on Automated Software Engineering (ASE) and the 27th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE), and he served in the editorial board of IEEE Transactions on Software Engineering (2017-2021). In 2022, he received an ERC Advanced Grant. His work has been funded further by the esteemed Emmy-Noether Program and the Heisenberg Program of the German Research Foundation (DFG). In 2018, the Association for Computing Machinery appointed him as ACM Distinguished Member for “Outstanding Scientific Contributions to Computing”. His work has received two Most Influential Paper Awards (SPLC'18, ICPC'22), two Best Paper Awards (SPLC'11, Modularity'15), two ACM SIGSOFT Distinguished Paper Awards (ICSE'15, ICSE'21), as well as awards by the Ernst-Denert Foundation, the Karin-Witte Foundation, and the State of Saxony-Anhalt.
Research on program comprehension has a fundamental limitation: program comprehension is a cognitive process that cannot be directly observed, which leaves considerable room for misinterpretation, uncertainty, and confounders. In project Brains On Code, we are developing a neuroscientific foundation of program comprehension. Instead of merely observing whether there is a difference regarding program comprehension (e.g., between two programming methods), we aim at precisely and reliably determining the key factors that cause the difference. This is especially challenging as humans are the subjects of study, and inter-personal variance and other confounding factors obfuscate the results. The key idea of Brains On Code is to leverage established methods from cognitive neuroscience to obtain insights into the underlying processes and influential factors of program comprehension. Brains On Code pursues a multimodal approach that integrates different neuro-physiological measures as well as a cognitive computational modeling approach to establish the theoretical foundation. This way, Brains On Code lays the foundations of measuring and modeling program comprehension and offers substantial feedback for programming methodology, language design, and education. With Brains On Code, addressing longstanding foundational questions such as “How can we reliably measure program comprehension?”, “What makes a program hard to understand?”, and “What skills should programmers have?” comes into reach. Brains On Code does not only help answer these questions, but also provides an outline for applying the methodology beyond program code (models, specifications, requirements, etc.).