Published July 5, 2024
| Version v2
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The artifacts of ISSTA 2024 paper titled "One Size Does Not Fit All: Multi-Granularity Patch Generation for Better Automated Program Repair"
Creators
Description
This is the artifact evaluation for the ISSTA 2024 paper titled "One Size Does Not Fit All: Multi-Granularity Patch Generation for Better Automated Program Repair." We are applying for the Availability badge.
Getting Started
Prerequisites
```
pytorch=2.0.0;
torchvision=0.15.1;
torchaudio;
datasets==1.16.1;
transformers==4.21.1;
tensorboard==2.12.2;
tree-sitter==0.19.1;
nltk=3.8.1;
scipy=1.10.1;
```
prepare the dataset
```bash
bash scripts/prepare_pretraining_dataset.sh
bash scripts/prepare_finetuning_dataset.sh
```
Pretrain the model
```bash
bash scripts/pretrain.sh --granularity [stmt|expr|token]
```
Finetune the model
```bash
bash scripts/finetune.sh --granularity [stmt|expr|token]
```
Files
Mulpor_zenodo.zip
Files
(366.3 MB)
| Name | Size | Download all |
|---|---|---|
|
md5:75bfca85f5450999d7a514006a905b22
|
366.3 MB | Preview Download |
Additional details
Dates
- Available
-
2024-07-04