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Code Smells Dataset (oracles)

This repository contains the datasets, obtained in 3 years, resulting from the Crowdsmelling methodology. Each file contains the dataset (oracle) of the year or set of years, for the code smells Long Method, God Class, and Feature Envy. The file Exercise-Code smells detection (ESII 2020).pdf

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CreatorPereira dos Reis, José
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Published2022-05-16
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DOI10.5281/zenodo.6555241
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Downloads8,305
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Licensecc-by-4.0
File Size2.8 MB
Data TypeDataset
Published2022
Licensecc-by-4.0
Total Views3,434
Total Downloads8,305

This repository contains the datasets, obtained in 3 years, resulting from the Crowdsmelling methodology.
Each file contains the dataset (oracle) of the year or set of years, for the code smells Long Method, God Class, and Feature Envy. The file Exercise-Code smells detection (ESII 2020).pdf describes the exercise used in the validation of code smells, and the file code-classification-statistics.csv shows statistics about the percentages of teams that classified the methods and classes.

More information about the datasets can be found in the article:

Reis, José Pereira dos , Abreu, Fernando Brito e . & Carneiro, Glauco de Figueiredo.   Crowdsmelling: A preliminary study on using collective knowledge in code smells detection. Empir Software Eng 27, 69 (2022). https://doi.org/10.1007/s10664-021-10110-5

DATASET STRUCTURE
  – project name
  – package name
  – class name
  – method name
  – code metrics [1]
  – code smell classification

 

REFERENCES

[1] Metrics description can be found in the study: "Fontana, F. A., Mantyla, M. V., Zanoni, M., and Marino, A. (2015), Comparing and experimenting machine learning techniques for code smell detection, Empirical Software Engineering"

 

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Code Smells Dataset (oracles) (Full Dataset)2.8 MB
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Files are hosted on the source repository. Click download to access the full dataset.

Pereira dos Reis, José (2022). Code Smells Dataset (oracles). https://doi.org/10.5281/zenodo.6555241