Skip to main content
zenodoopen

Automating Code Review Activities 2.0 (datasets, models and results)

<p>Resources related by the research work&nbsp;<em>&quot;Automating Code Review Activities 2.0&quot;.</em></p> <ul> <li><strong>automating_code_review.zip</strong>&nbsp;contains the&nbsp;material&nbsp;to successfully run our Colab notebooks;</li> <li><strong>dataset.zip&nbsp;</strong>contains all the preprocessed datasets used in our work;</li> <li><strong>generate_prediction.zip&nbsp;</strong>contains the material to successfully generate predictions using a T5 model chekpoint;</li> <li><strong>models.zip</strong>&nbsp;contains the (best) checkpoints of the fine-tuned T5 models;</li> <li><strong>results.zip</strong> contains our results;</li> <li><strong>tokenizer.zip</strong>&nbsp;contains the Sentencepiece model and vocabulary trained on our pre-training dataset.</li> </ul> <p>More information in the&nbsp;replication package of our work:&nbsp;<a href="https://github.com/CodeReviewAutomation/code_review_automation">code_review_autmoation</a></p>

ShareScore

32/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
4
Access
16
Reuse readiness
8
Engagement
0