cjl99/PT4Code

PT4code

The repo of ESEC/FSE 2022 paper "No More Fine-Tuning? An Experimental Evaluation of Prompt Tuning in Code Intelligence"

In this report, we upload all three tasks that can also be introduced in detail at CodeXGlue.

You can design and experiment different prompt templates by yourself :).

Defect Detection

Firstly download the dataset.

cd dataset
pip install gdown
gdown https://drive.google.com/uc?id=1x6hoF7G-tSYxg8AFybggypLZgMGDNHfF
cd ..

We provide a prompt version and fine-tuning version.

To prompt tuning a CodeBERT, just

cd defect/prompt
python codebert.py

To prompt tuning a CodeT5:

cd defect/prompt
python prompt_t5_2.py --visible_gpu <GPU> --data_dir=../dataset --max_source_length 512 --max_target_length 3 

To fine-tune a CodeT5, we provide the official and our implementation of CodeT5 repo in

cd defect/finetune

Code Summarization

Download the dataset, where {LANG} can be one of six programming languages.

cd summarization/data
wget https://s3.amazonaws.com/code-search-net/CodeSearchNet/v2/{LANG}.zip
unzip {LANG}.zip
python preprocess.py

To fine-tune or prompt tuning CodeT5 and try some different templates by yourself :)

cd summarization
python finetune_t5_gene.py --visible_gpu <GPU> --lang {LANG} --max_source_length 256 --max_target_length 128 --log_name=./log/{LANG}.log

For prompt tuning, use prompt_t5.py.

Code Translation

Download dataset from CodeXGlue dataset:

cd translation/data
python preprocess.py

The running command is similar to code summarization for fine-tune and prompt tuning.

Full Results

defect detection

Template	Verbalizer	ACC
[x] the code is [Z]	bad, defective&clean, perfect	63.68
the code [x] is [z]	bad, defective&clean, perfect	64.17
[x] it is [z]	bad, defective&clean, perfect	63.98
a [z] code [x]	bad, defective&clean, perfect	63.36
the code [x] is [z]	yes&no	63.08
the code [x] is [z]	bad, defective&indefective, perfect	64.28
the code [x] is [z]	bad&perfect	63.71
the code [x] is [z]	bad, defective, insecure&clean, perfect, secure	63.26
the code [x] is [z]	bad, defective, insecure, vulnerable&clean, perfect, secure,invulnerable	63.10
[SOFT] [z] [SOFT] [x]	bad, defective&clean, perfect	62.95
[x] [SOFT]*2 [z]	bad, defective&clean, perfect	62.77
[x] [SOFT]*3 [z]	bad, defective&clean, perfect	63.15
[SOFT]*10 [x] [z]	bad, defective&clean, perfect	62.52
[SOFT]*50 [x] [z]	bad, defective&clean, perfect	62.96
[SOFT]*100 [x] [z]	bad, defective&clean, perfect	62.46

CodeT5-small	ACC
Defect [X] [Z]	63
prefix 50	62.34
prefix 100	62.65
prefix 150	63.52
prefix 200	63.91
prefix 250	63.77

CodeT5-base	ACC
Defect [X] [Z]	64.98
prefix 50	64.59
prefix 100	64.7
prefix 150	65.66
prefix 200	65.82
prefix 250	65.64

Code Summarization

	Ruby	JavaScript	Go	Python	Java	PHP	Overall
codet5-small	Fine-tuning	13.38	14.94	21.27	17.88	18.38	24.70
Codet5-small	Prompt tuning	13.60	15.91	22.33	18.34	20.60	26.95
codet5-base	Fine-tuning	13.70	15.80	22.60	17.97	19.56	25.77
codet5-base	Prompt tuning	14.29	16.04	23.11	18.52	19.72	27.06

low resource

Python	100	200	300	500	1000	1%
CodeT5-small	5.42	7.62	7.89	11.58	13.23	14.01
CodeT5-small+PT	6.55	9.28	9.6	12.73	13.89	14.33
CodeT5-base	5.8	8.46	9.36	13.58	13.86	14.22
CodeT5-base+PT	7.82	10.78	12.63	14.77	14.78	14.81
Ruby	100	200	300	500	1000	1%
CodeT5-small	4.82	6.75	7.22	9.46	9.85	9.99
CodeT5-small+PT	6.48	7.89	8.26	10.89	10.91	10.85
CodeT5-base	4.93	6.83	7.19	10.1	11.22	10.36
CodeT5-base+PT	6.99	8.52	9.41	10.79	11.87	10.64
PHP	100	200	300	500	1000	1%
CodeT5-small	6.41	9.5	11.89	13.21	16.71	17.25
CodeT5-small+PT	7.9	12.23	14.13	16.26	17.47	17.88
CodeT5-base	5.52	8.9	12.83	15.59	17.65	20.65
CodeT5-base+PT	9.12	13.55	14.94	17.39	18.3	21.05
go	100	200	300	500	1000	1%
CodeT5-small	5.24	7.18	8.65	12.99	15.05	17.65
CodeT5-small+PT	7.2	11.51	12.42	14.32	16.88	17.95
CodeT5-base	7.96	9.64	10.88	13.62	16.93	19.99
CodeT5-base+PT	9.07	12.15	13.66	15.04	17.74	20.54
java	100	200	300	500	1000	1%
CodeT5-small	2.7	3.86	5.33	6.94	7.88	10.12
CodeT5-small+PT	3.56	5.89	7.35	9.9	10.44	11.18
CodeT5-base	3.35	4.73	7.24	8.32	10.94	11.75
CodeT5-base+PT	6.07	7.56	10.14	11.06	11.99	12.4
js	100	200	300	500	1000	1%
CodeT5-small	3.56	5.48	6.97	7.73	8.36	9.81
CodeT5-small+PT	5.9	7.58	8.76	9.6	10.14	11.58
CodeT5-base	4.14	5.6	7.07	10	10.62	11.53
CodeT5-base+PT	6.5	8.37	9.61	11.27	11.81	12.17

Code translation

		BLEU	Accuracy	CodeBLEU	BLEU	Accuracy	CodeBLEU
	Naive copy	18.69	0	-	18.54	0	-
	Transformer	50.47	37.90	61.59	55.84	33.00	63.74
	RoBERTa (code)	71.99	57.90	80.18	77.46	56.10	83.07
	CodeBERT	72.14	58.00	79.41	79.92	59.00	85.10
CodeT5-small	Fine-tuning	78.67	65.40	82.55	82.29	63.80	87.01
CodeT5-small	Prompt tuning	79.59	66.00	83.06	83.33	64.30	87.99
CodeT5-base	Fine-tuning	79.45	66.10	83.96	83.61	65.30	88.32
CodeT5-base	Prompt tuning	79.76	66.10	84.39	83.99	65.40	88.74