
# Dataset Card for the Juliet Test Suite 1.3

### Dataset Summary

This Datasets contains all test cases from the NIST's [Juliet test suite](https://samate.nist.gov/SARD/test-suites/112) for the C and C++ programming languages. The dataset contains a benign and a defective implementation of each sample, which have been extracting by means of the OMITGOOD and OMITBAD preprocessor macros of the Juliet test suite.

### Supported Tasks and Leaderboards

Software defect prediction, code clone detection.

### Languages

The C and C++ programming languages.

## Dataset Structure

### Data Instances

### Data Fields

| index | name | type | description |
| --- | --- | --- | --- |
| 0 | index | int | The index of each sample in the dataset. |
| 1 | filename | str | The path to the test case including the file name. |
| 2 | class | int | The class of the defect, i.e., the collection by CWE number from which the sample was taken. |
| 3 | good | str | The code of the benign implementation. |
| 4 | bad | str | The code of the defective implementation. |

### Data Splits

| type | size |
|------|------|
| train | 80706 cases |
| test | 20177 cases |

## Dataset Creation

### Curation Rationale

### Source Data

https://samate.nist.gov/SARD/test-suites/112

#### Initial Data Collection and Normalization

#### Who are the source language producers?

### Annotations

#### Annotation process

#### Who are the annotators?

### Personal and Sensitive Information

## Considerations for Using the Data

### Social Impact of Dataset

### Discussion of Biases

### Other Known Limitations

The Juliet test suite is a synthetic dataset, meaning that all samples have been manually crafted. Therefore they are not entirely representative of actual software defects found in the wild. A classifier trained on these samples may suffer from decreased predictive performance, leading to gross misclassifactions. Critical software defects may therefore be overlooked, when such model is applied in a realistic environment.

## Additional Information

### Dataset Curators

https://github.com/lorenz9314/

### Licensing Information

### Citation Information

### Contributions

task_categories:text-classification size_categories:10K<n<100K license:cc0-1.0 region:us
{"license": "cc0-1.0", "size_categories": ["10K<n<100K"], "task_categories": ["text-classification"], "pretty_name": "Juliet Test Suite 1.3"}
TAGS
#task_categories-text-classification #size_categories-10K<n<100K #license-cc0-1.0 #region-us 

Dataset Card for the Juliet Test Suite 1.3
==========================================


### Dataset Summary


This Datasets contains all test cases from the NIST's Juliet test suite for the C and C++ programming languages. The dataset contains a benign and a defective implementation of each sample, which have been extracting by means of the OMITGOOD and OMITBAD preprocessor macros of the Juliet test suite.


### Supported Tasks and Leaderboards


Software defect prediction, code clone detection.


### Languages


The C and C++ programming languages.


Dataset Structure
-----------------


### Data Instances


### Data Fields



### Data Splits



Dataset Creation
----------------


### Curation Rationale


### Source Data


URL


#### Initial Data Collection and Normalization


#### Who are the source language producers?


### Annotations


#### Annotation process


#### Who are the annotators?


### Personal and Sensitive Information


Considerations for Using the Data
---------------------------------


### Social Impact of Dataset


### Discussion of Biases


### Other Known Limitations


The Juliet test suite is a synthetic dataset, meaning that all samples have been manually crafted. Therefore they are not entirely representative of actual software defects found in the wild. A classifier trained on these samples may suffer from decreased predictive performance, leading to gross misclassifactions. Critical software defects may therefore be overlooked, when such model is applied in a realistic environment.


Additional Information
----------------------


### Dataset Curators


URL


### Licensing Information


### Contributions



### Dataset Summary


This Datasets contains all test cases from the NIST's Juliet test suite for the C and C++ programming languages. The dataset contains a benign and a defective implementation of each sample, which have been extracting by means of the OMITGOOD and OMITBAD preprocessor macros of the Juliet test suite. ### Supported Tasks and Leaderboards


Software defect prediction, code clone detection. ### Languages


The C and C++ programming languages.


Dataset Structure
----------------- ### Data Instances ### Data Fields ### Data Splits



Dataset Creation
---------------- ### Curation Rationale ### Source Data


URL #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations


The Juliet test suite is a synthetic dataset, meaning that all samples have been manually crafted. Therefore they are not entirely representative of actual software defects found in the wild. A classifier trained on these samples may suffer from decreased predictive performance, leading to gross misclassifactions. Critical software defects may therefore be overlooked, when such model is applied in a realistic environment.


Additional Information
---------------------- ### Dataset Curators


URL ### Licensing Information ### Contributions
TAGS
#task_categories-text-classification #size_categories-10K<n<100K #license-cc0-1.0 #region-us 
 ### Dataset Summary


This Datasets contains all test cases from the NIST's Juliet test suite for the C and C++ programming languages. The dataset contains a benign and a defective implementation of each sample, which have been extracting by means of the OMITGOOD and OMITBAD preprocessor macros of the Juliet test suite. ### Supported Tasks and Leaderboards


Software defect prediction, code clone detection. ### Languages


The C and C++ programming languages.


Dataset Structure
----------------- ### Data Instances ### Data Fields ### Data Splits



Dataset Creation
---------------- ### Curation Rationale ### Source Data


URL #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations


The Juliet test suite is a synthetic dataset, meaning that all samples have been manually crafted. Therefore they are not entirely representative of actual software defects found in the wild. A classifier trained on these samples may suffer from decreased predictive performance, leading to gross misclassifactions. Critical software defects may therefore be overlooked, when such model is applied in a realistic environment.


Additional Information
---------------------- ### Dataset Curators


URL ### Licensing Information ### Contributions
passage: TAGS
#task_categories-text-classification #size_categories-10K<n<100K #license-cc0-1.0 #region-us 
### Dataset Summary


This Datasets contains all test cases from the NIST's Juliet test suite for the C and C++ programming languages. The dataset contains a benign and a defective implementation of each sample, which have been extracting by means of the OMITGOOD and OMITBAD preprocessor macros of the Juliet test suite.### Supported Tasks and Leaderboards


Software defect prediction, code clone detection.### Languages


The C and C++ programming languages.


Dataset Structure
-----------------### Data Instances### Data Fields### Data Splits



Dataset Creation
----------------### Curation Rationale### Source Data


URL#### Initial Data Collection and Normalization#### Who are the source language producers?### Annotations#### Annotation process#### Who are the annotators?### Personal and Sensitive Information


Considerations for Using the Data
---------------------------------### Social Impact of Dataset### Discussion of Biases### Other Known Limitations


The Juliet test suite is a synthetic dataset, meaning that all samples have been manually crafted. Therefore they are not entirely representative of actual software defects found in the wild. A classifier trained on these samples may suffer from decreased predictive performance, leading to gross misclassifactions. Critical software defects may therefore be overlooked, when such model is applied in a realistic environment.


Additional Information
----------------------### Dataset Curators


URL### Licensing Information### Contributions