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The Qualitas Corpus: A Curated Collection of Java Code for Empirical Studies
Open accessAbstract
In order to increase our ability to use measurement to support software development practise we need to do more analysis of code. However, empirical studies of code are expensive and their results are difficult to compare. We describe the Qualitas Corpus, a large curated collection of open source Java systems. The corpus reduces the cost of performing large empirical studies of code and supports comparison of measurements of the same artifacts. We discuss its design, organisation, and issues associated with its development.
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Cited by
The adverse effects of code duplication in machine learning models of code
Allamanis, M. (2019) · Proceedings of the 2019 ACM SIGPLAN International Symposium on New Ideas, New Paradigms, and Reflections on Programming and Software · doi:10.1145/3359591.3359735 · Cited by 284
Quantifying the Transition from Python 2 to 3: An Empirical Study of Python Applications
Malloy, B. A., & Power, J. F. (2017) · 2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM) · doi:10.1109/esem.2017.45 · Cited by 27
New Initiative: The Naturalness of Software
Devanbu, P. (2015) · 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering · doi:10.1109/icse.2015.190 · Cited by 9
JEMMA: An extensible Java dataset for ML4Code applications
Karmakar, A., Allamanis, M., & Robbes, R. (2023) · Empirical Software Engineering · doi:10.1007/s10664-022-10275-7 · Cited by 4
Metadata
- Authors
- Tempero, E., Anslow, C., Dietrich, J., Han, T., Li, J., Lumpe, M., Melton, H., & Noble, J.
- Venue
- 2010 Asia Pacific Software Engineering Conference
- Publisher
- IEEE
- Published
- 2010-11
- Pages
- 336-345
- ISSN
- 1530-1362 (ISSN-L)
- OpenAlex
- W2095938258
- Cited by
- 407
- References
- 0
- FWCI
- 15.74
- Type
- conference paper
- Language
- en
- Open access
- green
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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