CatQualia/code-quality-corpus

CatQualia code-quality corpus — semantic smell classes with before/after fixes 39,383 rows · 25,541,792 bytes · JSON Lines, one object per line. What this is Real code smells paired with the fix: a smell_class that names the semantic problem (not just the syntax), the original lines, the corrected lines, the file and line it came from, and a rationale explaining why the original was wrong. Useful for code-review or repair training where the label has to say what… See the full description on the dataset page: https://huggingface.co/datasets/CatQualia/code-quality-corpus.