Datasets:

Modalities:
Text
Formats:
parquet
Size:
< 1K
ArXiv:
DOI:
Libraries:
Datasets
pandas
License:
File size: 2,847 Bytes
ae96f17
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
2f0a0a7
b46f829
 
 
 
 
 
45360fd
 
 
 
 
 
 
 
 
 
5f47b9f
45360fd
5f47b9f
45360fd
 
5f47b9f
45360fd
 
b46f829
45360fd
5f47b9f
 
 
 
2afb71a
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
---
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
dataset_info:
  features:
  - name: source
    dtype: string
  - name: file_name
    dtype: string
  - name: cwe
    dtype: string
  splits:
  - name: train
    num_bytes: 87854
    num_examples: 76
  download_size: 53832
  dataset_size: 87854
---
# Dataset Card for "static-analysis-eval"

A dataset of 76 Python programs taken from real Python open source projects (top 1000 on GitHub), 
where each program is a file that has exactly 1 vulnerability as detected by a particular static analyzer (Semgrep).

# Leaderboard

| Model                        | StaticAnalysisEval (%) | Time (mins) | Price (USD) |
|------------------------------|------------------------|-------------|-------------|
| gpt-4o                       | 69.74                  | 23:05       |  1.53       |
| gemini-1.5-flash-latest      | 68.42                  | 18:23       |  0.07       |
| Llama-3-70B-instruct         | 65.78                  | 35:26       |             |
| Llama-3-8B-instruct          | 65.78                  | 31.34       |             |
| gemini-1.5-pro-latest        | 64.47                  | 34:40       |             |
| gpt-4-1106-preview           | 64.47                  | 27:56       |  3.04       |
| gpt-4                        | 63.16                  | 26:31       |  6.84       |
| gpt-4-0125-preview           | 53.94                  | 34:40       |             |
| patched-coder-7b             | 51.31                  | 45.20       |             |
| patched-coder-34b            | 46.05                  | 33:58       |  0.87       |
| Mistral-Large                | 40.80                  | 60:00+      |             |
| Gemini-pro                   | 39.47                  | 16:09       |  0.23       |
| Mistral-Medium               | 39.47                  | 60:00+      |  0.80       |
| Mixtral-Small                | 30.26                  | 30:09       |             |
| gpt-3.5-turbo-0125           | 28.95                  | 21:50       |             |
| claude-3-opus-20240229       | 25.00                  | 60:00+      |             |
| Gemma-7b-it                  | 19.73                  | 36:40       |             |
| gpt-3.5-turbo-1106           | 17.11                  | 13:00       |  0.23       |
| Codellama-70b-Instruct       | 10.53                  | 30.32       |             |
| CodeLlama-34b-Instruct       |  7.89                  | 23:16       |             |


The price is calcualted by assuming 1000 input and output tokens per call as all examples in the dataset are < 512 tokens (OpenAI cl100k_base tokenizer). 

Some models timed out during the run or had intermittent API errors. We try each example 3 times in such cases. This is why some runs are reported to be longer than 1 hr (60:00+ mins).