Are Students Representatives of Professionals in Software Engineering Experiments?
Abstract
Background: Most of the experiments in software engineering (SE) employ students as subjects. This raises concerns about the realism of the results acquired through students and adaptability of the results to software industry. Aim: We compare students and professionals to understand how well students represent professionals as experimental subjects in SE research. Method: The comparison was made in the context of two test-driven development experiments conducted with students in an academic setting and with professionals in a software organization. We measured the code quality of several tasks implemented by both subject groups and checked whether students and professionals perform similarly in terms of code quality metrics. Results: Except for minor differences, neither of the subject groups is better than the other. Professionals produce larger, yet less complex, methods when they use their traditional development approach, whereas both subject groups perform similarly when they apply a new approach for the first time. Conclusion: Given a carefully scoped experiment on a development approach that is new to both students and professionals, similar performances are observed. Further investigation is necessary to analyze the effects of subject demographics and level of experience on the results of SE experiments.
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CS students can be reasonable proxies for developers in software engineering user studies.
“Prior work has noted that CS students can be reasonable proxies for developers in the context of software engineering user studies.”
From Lost at C: A User Study on the Security Implications of Large Language Model Code Assistants (2022) · cites this paper as [46]
Cites
The Kolmogorov-Smirnov Test for Goodness of Fit
Massey, F. J. (1951) · Journal of the American Statistical Association · doi:10.1080/01621459.1951.10500769 · Cited by 7,210 · see citing works
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Do Developers Read Compiler Error Messages?
Barik, T., Smith, J., Lubick, K., Holmes, E., Feng, J., Murphy-Hill, E., & Parnin, C. (2017) · 2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE) · doi:10.1109/icse.2017.59 · Cited by 86 · see citing works
Tosun, A., Dieste, O., Fucci, D., Vegas, S., Turhan, B., Erdogmus, H., Santos, A., Oivo, M., Toro, K., Jarvinen, J., et al. (2017) · Empirical Software Engineering · doi:10.1007/s10664-016-9490-0 · Cited by 50 · see citing works
Self-citationLost at C: A User Study on the Security Implications of Large Language Model Code Assistants
Sandoval, G., Pearce, H., Nys, T., Karri, R., Garg, S., & Dolan-Gavitt, B. (2022) · arXiv · doi:10.48550/arxiv.2208.09727 · Cited by 52 · see citing works
Wyrich, M., Preikschat, A., Graziotin, D., & Wagner, S. (2021) · 2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE) · doi:10.1109/icse43902.2021.00055 · Cited by 24 · see citing works
- Authors
- Salman, I., Misirli, A. T., & Juristo, N.
- Affiliations
- University of Oulu (FI)
- ORCID
- Salman, Iflaah
- Venue
- 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering
- Publisher
- IEEE
- Published
- 2015-05
- Pages
- 666-676
- ISSN
- 0270-5257 (ISSN-L)
- OpenAlex
- W4248361652
- Cited by
- 304
- References
- 1
- Citations by year
- 2026: 13 · 2025: 24 · 2024: 26 · 2023: 27 · 2022: 24 · 2021: 27 · 2020: 30 · 2019: 43 · 2018: 28 · 2017: 33 · 2016: 18 · 2015: 11
- FWCI
- 26.07
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- ACM/IEEE International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) (publishedVersion)
- Istanbul Technical University Academic Open Archive (Istanbul Technical University) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Software Engineering Techniques and Practices
- Physical Sciences › Computer Science › Information Systems › Software Engineering Research
- Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
- Keywords
- software engineering experiments, test-driven development, code quality, code metrics, experimental subjects, developer experience
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