SmellyCode++.csv
<p dir="ltr">The dataset provides a well-rounded representation of code quality by incorporating both textual and numerical features, making it valuable for machine learning and code analysis tasks. The textual feature, represented by a "Code" column, contains Java classes...
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2025
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| Summary: | <p dir="ltr">The dataset provides a well-rounded representation of code quality by incorporating both textual and numerical features, making it valuable for machine learning and code analysis tasks. The textual feature, represented by a "Code" column, contains Java classes or methods that exhibit code smells. These code snippets have been preprocessed to remove unnecessary elements like comments, empty lines, and extra newline characters, ensuring consistency. In addition, the dataset includes 14 numerical features that capture various code metrics, such as logical lines, distinct operators and operands, cyclomatic complexity, and effort estimation. These numerical attributes help assess code complexity, maintainability, and potential defects. The dataset’s statistical summaries and visual representations further highlight the distribution of these features, making it a robust resource for empirical research and model training.</p> |
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