Datasets:

Modalities:
Text
Formats:
json
Size:
< 1K
Libraries:
Datasets
pandas
joannacss commited on
Commit
435f4c1
1 Parent(s): a83a8d0

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +27 -99
README.md CHANGED
@@ -4,35 +4,35 @@ language:
4
  ---
5
  # Dataset Card for Dataset Name
6
 
7
- <!-- Provide a quick summary of the dataset. -->
8
 
9
- This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
 
 
 
 
10
 
11
  ## Dataset Details
12
 
13
  ### Dataset Description
14
 
15
- <!-- Provide a longer summary of what this dataset is. -->
16
 
17
 
18
 
19
- - **Curated by:** [More Information Needed]
20
- - **Funded by [optional]:** [More Information Needed]
21
- - **Shared by [optional]:** [More Information Needed]
22
- - **Language(s) (NLP):** [More Information Needed]
23
- - **License:** [More Information Needed]
24
 
25
  ### Dataset Sources [optional]
26
 
27
- <!-- Provide the basic links for the dataset. -->
28
 
29
- - **Repository:** [github.com/s2e-lab/SecurityEval]
30
- - **Paper [optional]:** [More Information Needed]
31
- - **Demo [optional]:** [More Information Needed]
 
 
32
 
33
  ## Uses
34
 
35
- <!-- Address questions around how the dataset is intended to be used. -->
36
 
37
  ### Direct Use
38
 
@@ -40,102 +40,30 @@ This dataset card aims to be a base template for new datasets. It has been gener
40
 
41
  [More Information Needed]
42
 
43
- ### Out-of-Scope Use
44
-
45
- <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
46
-
47
- [More Information Needed]
48
 
49
  ## Dataset Structure
50
 
51
- <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
52
-
53
- [More Information Needed]
54
-
55
- ## Dataset Creation
56
-
57
- ### Curation Rationale
58
-
59
- <!-- Motivation for the creation of this dataset. -->
60
-
61
- [More Information Needed]
62
-
63
- ### Source Data
64
-
65
- <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
66
-
67
- #### Data Collection and Processing
68
-
69
- <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
70
-
71
- [More Information Needed]
72
-
73
- #### Who are the source data producers?
74
-
75
- <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
76
-
77
- [More Information Needed]
78
-
79
- ### Annotations [optional]
80
-
81
- <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
82
-
83
- #### Annotation process
84
-
85
- <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
86
-
87
- [More Information Needed]
88
 
89
- #### Who are the annotators?
90
-
91
- <!-- This section describes the people or systems who created the annotations. -->
92
-
93
- [More Information Needed]
94
-
95
- #### Personal and Sensitive Information
96
-
97
- <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
98
-
99
- [More Information Needed]
100
-
101
- ## Bias, Risks, and Limitations
102
-
103
- <!-- This section is meant to convey both technical and sociotechnical limitations. -->
104
-
105
- [More Information Needed]
106
-
107
- ### Recommendations
108
-
109
- <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
110
-
111
- Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
112
 
113
  ## Citation [optional]
114
 
115
- <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
116
 
117
  **BibTeX:**
118
 
119
- [More Information Needed]
 
 
 
 
 
 
 
 
120
 
121
  **APA:**
122
 
123
- [More Information Needed]
124
-
125
- ## Glossary [optional]
126
-
127
- <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
128
-
129
- [More Information Needed]
130
-
131
- ## More Information [optional]
132
-
133
- [More Information Needed]
134
-
135
- ## Dataset Card Authors [optional]
136
-
137
- [More Information Needed]
138
-
139
- ## Dataset Card Contact
140
-
141
- [More Information Needed]
 
4
  ---
5
  # Dataset Card for Dataset Name
6
 
 
7
 
8
+ This dataset is from the paper titled **SecurityEval Dataset: Mining Vulnerability Examples to Evaluate Machine Learning-Based Code Generation Techniques**.
9
+ The project is accepted for The first edition of the International Workshop on Mining Software Repositories Applications for Privacy and Security (MSR4P&S '22).
10
+ The paper describes the dataset for evaluating machine learning-based code generation output and application of the dataset to the code generation tools.
11
+
12
+
13
 
14
  ## Dataset Details
15
 
16
  ### Dataset Description
17
 
 
18
 
19
 
20
 
21
+ - **Curated by:** Mohammed Latif Siddiq & Joanna C. S. Santos
22
+ - **Language(s):** Python
 
 
 
23
 
24
  ### Dataset Sources [optional]
25
 
 
26
 
27
+ - **Repository:** https://github.com/s2e-lab/SecurityEval
28
+ - **Paper:**
29
+ "SecurityEval Dataset: Mining Vulnerability Examples to Evaluate Machine Learning-Based Code Generation Techniques".
30
+ International Workshop on Mining Software Repositories Applications for Privacy and Security (MSR4P&S '22).
31
+ https://s2e-lab.github.io/preprints/msr4ps22-preprint.pdf
32
 
33
  ## Uses
34
 
35
+
36
 
37
  ### Direct Use
38
 
 
40
 
41
  [More Information Needed]
42
 
 
 
 
 
 
43
 
44
  ## Dataset Structure
45
 
46
+ - dataset.jsonl: dataset file in jsonl format. Every line contains a JSON object with the following fields:
47
+ - `ID`: unique identifier of the sample.
48
+ - `Prompt`: Prompt for the code generation model.
49
+ - `Insecure_code`: code of the vulnerability example that may generate from the prompt.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
50
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
51
 
52
  ## Citation [optional]
53
 
 
54
 
55
  **BibTeX:**
56
 
57
+ ```
58
+ @inproceedings{siddiq2022seceval,
59
+ author={Siddiq, Mohammed Latif and Santos, Joanna C. S. },
60
+ booktitle={Proceedings of the 1st International Workshop on Mining Software Repositories Applications for Privacy and Security (MSR4P&S22)},
61
+ title={SecurityEval Dataset: Mining Vulnerability Examples to Evaluate Machine Learning-Based Code Generation Techniques},
62
+ year={2022},
63
+ doi={10.1145/3549035.3561184}
64
+ }
65
+ ```
66
 
67
  **APA:**
68
 
69
+ Siddiq, M. L., & Santos, J. C. (2022, November). SecurityEval dataset: mining vulnerability examples to evaluate machine learning-based code generation techniques. In Proceedings of the 1st International Workshop on Mining Software Repositories Applications for Privacy and Security (pp. 29-33).