Abstract
The aim of this paper is to present a dataset of metrics as- sociated to the first release of a curated collection of Python software systems. We describe the dataset along with the adopted criteria and the issues we faced while building such corpus. This dataset can enhance the reliability of empirical studies, enabling their reproducibility, reducing their cost, and it can foster further research on Python software.
Original language | English |
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Title of host publication | 11th International Conference on Predictive Models and Data Analytics in Software Engineering, PROMISE 2015 |
Publisher | ACM Press |
Volume | 2015-October |
ISBN (Electronic) | 9781450337151 |
DOIs | |
Publication status | Published - 21 Oct 2015 |
Event | 11th International Conference on Predictive Models and Data Analytics in Software Engineering, PROMISE 2015 - Beijing, China Duration: 21 Oct 2015 → … |
Conference
Conference | 11th International Conference on Predictive Models and Data Analytics in Software Engineering, PROMISE 2015 |
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Country/Territory | China |
City | Beijing |
Period | 21/10/15 → … |
Keywords
- Curated Code Collection
- Empirical Studies
- Python