The DOI matches its Crossref record; 86 of the 87 references it cites were found in a registry or an index.
Understanding understanding source code with functional magnetic resonance imaging
Open accessAbstract
Program comprehension is an important cognitive process that inherently eludes direct measurement. Thus, researchers are struggling with providing suitable programming languages, tools, or coding conventions to support developers in their everyday work. In this paper, we explore whether functional magnetic resonance imaging (fMRI), which is well established in cognitive neuroscience, is feasible to soundly measure program comprehension. In a controlled experiment, we observed 17 participants inside an fMRI scanner while they were comprehending short source-code snippets, which we contrasted with locating syntax errors. We found a clear, distinct activation pattern of five brain regions, which are related to working memory, attention, and language processing---all processes that fit well to our understanding of program comprehension. Our results encourage us and, hopefully, other researchers to use fMRI in future studies to measure program comprehension and, in the long run, answer questions, such as: Can we predict whether someone will be an excellent programmer? How effective are new languages and tools for program understanding? How should we train programmers?
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“When comprehension of code was compared to detection of syntactic errors in code, activity in both fronto-parietal and putative language areas was observed (Siegmund et al., 2014, Siegmund, 2017).”
From Computer code comprehension shares neural resources with formal logical inference in the fronto-parietal network (2020) · cites this paper as Siegmund et al., 2014
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Coding as another language: a pedagogical approach for teaching computer science in early childhood
Bers, M. U. (2019) · Journal of Computers in Education · doi:10.1007/s40692-019-00147-3 · Cited by 248
Eye Movements in Code Reading: Relaxing the Linear Order
Busjahn, T., Bednarik, R., Begel, A., Crosby, M. E., Paterson, J. H., Schulte, C., Sharif, B., & Tamm, S. (2015) · IEEE International Conference on Program Comprehension (ICPC) · doi:10.1109/icpc.2015.36 · Cited by 182
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Muller, S. C., & Fritz, T. (2015) · ACM/IEEE International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) · doi:10.1109/icse.2015.334 · Cited by 150
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Decoding the Representation of Code in the Brain: An fMRI Study of Code Review and Expertise
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Metadata
- Authors
- Siegmund, J., Kästner, C., Apel, S., Parnin, C., Bethmann, A., Leich, T., Saake, G., & Brechmann, A.
- Affiliations
- University of Passau (DE)
- Carnegie Mellon University (US)
- Georgia Institute of Technology (US)
- Leibniz Institute for Neurobiology (DE)
- Metop Research Institute, Germany
- Otto-von-Guericke-Universität Magdeburg (DE)
- Venue
- Proceedings of the 36th International Conference on Software Engineering
- Publisher
- ACM
- Published
- 2014-05-31
- Pages
- 378-389
- ISSN
- 0270-5257 (ISSN-L)
- OpenAlex
- W2014232144
- Cited by
- 219
- References
- 87
- Citations by year
- 2026: 19 · 2025: 13 · 2024: 15 · 2023: 8 · 2022: 12 · 2021: 24 · 2020: 38 · 2019: 22 · 2018: 18 · 2017: 10 · 2016: 18 · 2015: 17 · 2014: 4
- FWCI
- 13.93
- Type
- conference paper
- Language
- en
- Open access
- green
- figshare.com
- Locations
- ACM/IEEE International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) (publishedVersion)
- KiltHub Repository (submittedVersion)
- Figshare (submittedVersion, cc-by)
- KiltHub Repository
- Funders
- National Science Foundation
- Deutsche Forschungsgemeinschaft
- Topics
- Physical Sciences › Computer Science › Information Systems › Software Engineering Research
- Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neuroscience, Education and Cognitive Function
- Keywords
- program comprehension, source code understanding, functional MRI, brain activation patterns, working memory, attention, language processing, programming languages, programmer training
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