Update README.md
Browse files
README.md
CHANGED
@@ -133,4 +133,199 @@ dataset_info:
|
|
133 |
num_examples: 5
|
134 |
download_size: 6139
|
135 |
dataset_size: 5577
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
136 |
---
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
133 |
num_examples: 5
|
134 |
download_size: 6139
|
135 |
dataset_size: 5577
|
136 |
+
license: cc
|
137 |
+
task_categories:
|
138 |
+
- text-generation
|
139 |
+
language:
|
140 |
+
- en
|
141 |
+
tags:
|
142 |
+
- code
|
143 |
+
pretty_name: inpro
|
144 |
+
size_categories:
|
145 |
+
- 10K<n<100K
|
146 |
---
|
147 |
+
|
148 |
+
# Dataset Card for intro_prog
|
149 |
+
|
150 |
+
## Dataset Description
|
151 |
+
|
152 |
+
### Dataset Summary
|
153 |
+
|
154 |
+
IntroProg is a collection of students' submissions to assignments in various introductory programming courses offered at different universities.
|
155 |
+
Currently, the dataset contains submissions collected from Dublin City University, and the University of Singapore.
|
156 |
+
|
157 |
+
#### Dublin
|
158 |
+
|
159 |
+
The Dublin programming dataset is a dataset composed of students' submissions to introductory programming assignments at the University of Dublin.
|
160 |
+
Students submitted these programs for multiple programming courses over the duration of three academic years.
|
161 |
+
|
162 |
+
#### Singapore
|
163 |
+
|
164 |
+
The Singapore dataset contains 2442 correct and 1783 buggy program attempts by 361 undergraduate students
|
165 |
+
crediting an introduction to Python programming course at NUS (National University of Singapore).
|
166 |
+
|
167 |
+
|
168 |
+
### Supported Tasks and Leaderboards
|
169 |
+
|
170 |
+
#### "Metadata": Program synthesis
|
171 |
+
|
172 |
+
Similarly to the [Most Basic Python Programs](https://huggingface.co/datasets/mbpp) (mbpp), the data split can be used to evaluate
|
173 |
+
code generations models.
|
174 |
+
|
175 |
+
#### "Data"
|
176 |
+
|
177 |
+
The data configuration contains all the submissions as well as an indicator of whether these passed the required test.
|
178 |
+
|
179 |
+
#### "repair": Program refinement/repair
|
180 |
+
|
181 |
+
The "repair" configuration of each dataset is a subset of the "data" configuration
|
182 |
+
augmented with educators' annotations on the corrections to the buggy programs.
|
183 |
+
This configuration can be used for the task of program refinement. In [Computing Education Research](https://faculty.washington.edu/ajko/cer/) (CER),
|
184 |
+
methods for automatically repairing student programs are used to provide students with feedback and help them debug their code.
|
185 |
+
|
186 |
+
#### "bug": Bug classification
|
187 |
+
|
188 |
+
[Coming soon]
|
189 |
+
|
190 |
+
### Languages
|
191 |
+
|
192 |
+
The assignments were written in Python.
|
193 |
+
|
194 |
+
## Dataset Structure
|
195 |
+
|
196 |
+
One configuration is defined by one source dataset *dublin* or *singapore* and one subconfiguration ("metadata", "data", or "repair"):
|
197 |
+
|
198 |
+
* "dublin_metadata"
|
199 |
+
* "dublin_data"
|
200 |
+
* "dublin_repair"
|
201 |
+
* "singapore_metadata"
|
202 |
+
* "singapore_data"
|
203 |
+
* "singapore_repair"
|
204 |
+
|
205 |
+
|
206 |
+
### Data Instances
|
207 |
+
|
208 |
+
[More Information Needed]
|
209 |
+
|
210 |
+
### Data Fields
|
211 |
+
|
212 |
+
[More Information Needed]
|
213 |
+
|
214 |
+
Some of the fields are configuration specific
|
215 |
+
|
216 |
+
* submission_id: a unique number identifying the submission
|
217 |
+
* user: a unique string identifying the (anonymized) student who submitted the solution
|
218 |
+
* date: the timestamp at which the grading server received the submission
|
219 |
+
* func_code: the cleaned code submitted
|
220 |
+
* func_name: the name of the function that had to be implemented
|
221 |
+
* assingment_id: the unique (string) identifier of the assignment that had to be completed
|
222 |
+
* academic_year: the starting year of the academic year (e.g. 2015 for the academic year 2015-2016)
|
223 |
+
* module: the course/module
|
224 |
+
* test: a human eval-style string which can be used to execute the submitted solution on the provided test cases
|
225 |
+
* Description: a description of what the function is supposed to achieve
|
226 |
+
* correct: whether the solution passed all tests or not
|
227 |
+
|
228 |
+
|
229 |
+
### Data Splits
|
230 |
+
|
231 |
+
#### Dublin
|
232 |
+
|
233 |
+
The Dublin dataset is split into a training and validation set. The training set contains the submissions to the assignments
|
234 |
+
written during the academic years 2015-2016, and 2016-2017, while the test set contains programs written during the academic year 2017-2018.
|
235 |
+
|
236 |
+
#### Singapore
|
237 |
+
|
238 |
+
The Singapore dataset only contains a training split, which can be used as a test split for evaluating how your feedback
|
239 |
+
methods perform on an unseen dataset (if, for instance, you train your methods on the Dublin Dataset).
|
240 |
+
|
241 |
+
## Dataset Creation
|
242 |
+
|
243 |
+
### Curation Rationale
|
244 |
+
|
245 |
+
[More Information Needed]
|
246 |
+
|
247 |
+
### Source Data
|
248 |
+
|
249 |
+
#### Initial Data Collection and Normalization
|
250 |
+
|
251 |
+
[More Information Needed]
|
252 |
+
|
253 |
+
#### Who are the source language producers?
|
254 |
+
|
255 |
+
[More Information Needed]
|
256 |
+
|
257 |
+
### Annotations
|
258 |
+
|
259 |
+
#### Annotation process
|
260 |
+
|
261 |
+
[More Information Needed]
|
262 |
+
|
263 |
+
#### Who are the annotators?
|
264 |
+
|
265 |
+
[More Information Needed]
|
266 |
+
|
267 |
+
### Personal and Sensitive Information
|
268 |
+
|
269 |
+
[More Information Needed]
|
270 |
+
|
271 |
+
## Considerations for Using the Data
|
272 |
+
|
273 |
+
### Social Impact of Dataset
|
274 |
+
|
275 |
+
[More Information Needed]
|
276 |
+
|
277 |
+
### Discussion of Biases
|
278 |
+
|
279 |
+
[More Information Needed]
|
280 |
+
|
281 |
+
### Other Known Limitations
|
282 |
+
|
283 |
+
[More Information Needed]
|
284 |
+
|
285 |
+
## Additional Information
|
286 |
+
|
287 |
+
### Dataset Curators
|
288 |
+
|
289 |
+
[More Information Needed]
|
290 |
+
|
291 |
+
### Licensing Information
|
292 |
+
|
293 |
+
|
294 |
+
#### Dublin
|
295 |
+
|
296 |
+
#### Singapore
|
297 |
+
|
298 |
+
The data was released under a [GNU Lesser General Public License v3.0](https://github.com/githubhuyang/refactory/blob/master/LICENSE) license
|
299 |
+
|
300 |
+
|
301 |
+
### Citation Information
|
302 |
+
|
303 |
+
```
|
304 |
+
@inproceedings{azcona2019user2code2vec,
|
305 |
+
title={user2code2vec: Embeddings for Profiling Students Based on Distributional Representations of Source Code},
|
306 |
+
author={Azcona, David and Arora, Piyush and Hsiao, I-Han and Smeaton, Alan},
|
307 |
+
booktitle={Proceedings of the 9th International Learning Analytics & Knowledge Conference (LAK’19)},
|
308 |
+
year={2019},
|
309 |
+
organization={ACM}
|
310 |
+
}
|
311 |
+
@inproceedings{DBLP:conf/edm/CleuziouF21,
|
312 |
+
author = {Guillaume Cleuziou and
|
313 |
+
Fr{\'{e}}d{\'{e}}ric Flouvat},
|
314 |
+
editor = {Sharon I{-}Han Hsiao and
|
315 |
+
Shaghayegh (Sherry) Sahebi and
|
316 |
+
Fran{\c{c}}ois Bouchet and
|
317 |
+
Jill{-}J{\^{e}}nn Vie},
|
318 |
+
title = {Learning student program embeddings using abstract execution traces},
|
319 |
+
booktitle = {Proceedings of the 14th International Conference on Educational Data
|
320 |
+
Mining, {EDM} 2021, virtual, June 29 - July 2, 2021},
|
321 |
+
publisher = {International Educational Data Mining Society},
|
322 |
+
year = {2021},
|
323 |
+
timestamp = {Wed, 09 Mar 2022 16:47:22 +0100},
|
324 |
+
biburl = {https://dblp.org/rec/conf/edm/CleuziouF21.bib},
|
325 |
+
bibsource = {dblp computer science bibliography, https://dblp.org}
|
326 |
+
}
|
327 |
+
```
|
328 |
+
|
329 |
+
### Contributions
|
330 |
+
|
331 |
+
[More Information Needed]
|