Demo Data from VLDB 2026 / reviewers in the wild / expert
Xiao-Su Hu
dblp:63/9772 · also Xiaosu Hu
· DBLP profile ↗
2ranked-venue papers
0as first author
1since 2021 · last 2021
0000-0003-1401-000XORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 2 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Software engineering, system software, and programming languages
2 papers |
Empirical software engineering · 100% | |
| Interdisciplinary, comprehensive, and emerging computing
2 papers |
Computing education · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Empirical software engineering
developer studies |
0.9 | 2 | 2021 | Relating Reading, Visualization, and Coding for New Programmers: A Neuroimaging Study · ICSE 2021 Distilling neural representations of data structure manipulation using fMRI and fNIRS · ICSE 2019 |
Computing education › programming education
novice programming |
0.1 | 1 | 2021 | Relating Reading, Visualization, and Coding for New Programmers: A Neuroimaging Study · ICSE 2021 |
Computing education › programming education
cognitive processes in programming |
0.1 | 1 | 2019 | Distilling neural representations of data structure manipulation using fMRI and fNIRS · ICSE 2019 |
Methods — techniques the papers use, named apart from their topics
functional near-infrared spectroscopy · 1.0neuroimaging · 0.8fNIRS · 0.8fMRI · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Relating Reading, Visualization, and Coding for New Programmers: A Neuroimaging StudyabstractUnderstanding how novices reason about coding at a neurological level has implications for training the next generation of software engineers. In recent years, medical imaging has been increasingly employed to investigate patterns of neural activity associated with coding activity. However, such studies have focused on advanced undergraduates and professionals. In a human study of 31 participants, we use functional near-infrared spectroscopy to measure the neural activity associated with introductory programming. In a controlled, contrast-based experiment, we relate brain activity when coding to that of reading natural language or mentally rotating objects (a spatial visualization task). Our primary result is that all three tasks-coding, prose reading, and mental rotation-are mentally distinct for novices. However, while those tasks are neurally distinct, we find more significant differences between prose and coding than between mental rotation and coding. Intriguingly, we generally find more activation in areas of the brain associated with spatial ability and task difficulty for novice coding compared to that reported in studies with more expert developers. Finally, in an exploratory analysis, we also find a neural activation pattern predictive of programming performance 11 weeks later. While preliminary, these findings both expand on previous results (e.g., relating expertise to a similarity between coding and prose reading) and also provide a new understanding of the cognitive processes underlying novice programming. Madeline Endres, Zachary Karas, Xiao-Su Hu, Ioulia Kovelman, Westley Weimer |
ICSE | 3 |
| 2019 | Distilling neural representations of data structure manipulation using fMRI and fNIRSabstractData structures permeate many aspects of software engineering, but their associated human cognitive processes are not thoroughly understood. We leverage medical imaging and insights from the psychological notion of spatial ability to decode the neural representations of several fundamental data structures and their manipulations. In a human study involving 76 participants, we examine list, array, tree, and mental rotation tasks using both functional near-infrared spectroscopy (fNIRS) and functional magnetic resonance imaging (fMRI). We find a nuanced relationship: data structure and spatial operations use the same focal regions of the brain but to different degrees. They are related but distinct neural tasks. In addition, more difficult computer science problems induce higher cognitive load than do problems of pure spatial reasoning. Finally, while fNIRS is less expensive and more permissive, there are some computing-relevant brain regions that only fMRI can reach. Yu Huang 0015, Ryan Krueger, Tyler Santander, Xiao-Su Hu, Kevin Leach, Westley Weimer |
ICSE | 5 |