Upload intro_prog.py
Browse files- intro_prog.py +51 -18
intro_prog.py
CHANGED
@@ -30,10 +30,18 @@ This dataset contains 2442 correct and 1783 buggy program attempts by 361 underg
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an introduction to Python programming course at NUS (National University of Singapore).
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"""
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_DUBLIN_HOMEPAGE = """https://figshare.com/articles/dataset/_5_Million_Python_Bash_Programming_Submissions_for_5_Courses_Grades_for_Computer-Based_Exams_over_3_academic_years_/12610958"""
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_SINGAPORE_HOMEPAGE = """https://github.com/githubhuyang/refactory"""
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_DUBLIN_CITATION = """
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@inproceedings{azcona2019user2code2vec,
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title={user2code2vec: Embeddings for Profiling Students Based on Distributional Representations of Source Code},
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}
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"""
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"""
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_DUBLIN_URLS = {
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@@ -104,7 +130,7 @@ _SINGAPORE_URLS = {
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}
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}
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"metadata": {
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"train": "./data/newcaledonia_metadata_train.jsonl",
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},
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@@ -115,7 +141,8 @@ NEW_CALEDONIA_URLS = {
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_URLS = {
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"dublin": _DUBLIN_URLS,
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"singapore": _SINGAPORE_URLS
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}
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class IntroProgConfig(datasets.BuilderConfig):
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@@ -145,31 +172,37 @@ class IntroProg(datasets.GeneratorBasedBuilder):
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configurations = list(product(tasks, sources))
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configurations.append((tasks[0], "newcaledonia"))
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BUILDER_CONFIGS = []
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for (task, description), source in configurations:
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BUILDER_CONFIGS.append(
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IntroProgConfig(
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name=f"{source}_{task}",
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# description=description, # TODO: map to correct description
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version=VERSION,
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)
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)
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def _info(self):
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# TODO: could be more conscise
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description = _DUBLIN_DESCRIPTION
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citation = _DUBLIN_CITATION
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homepage = _DUBLIN_HOMEPAGE
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elif
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description =_SINGAPORE_DESCRIPTION
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citation = _SINGAPORE_CITATION
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homepage = _SINGAPORE_HOMEPAGE
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main_features = datasets.Features({
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"submission_id": datasets.Value("int32"),
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@@ -179,18 +212,18 @@ class IntroProg(datasets.GeneratorBasedBuilder):
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"func_name": datasets.Value("string"),
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"description": datasets.Value(dtype='string'),
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"test": datasets.Value(dtype='string'),
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})
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if
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features = main_features
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features["correct"] = datasets.Value(dtype="bool")
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if
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features["user"] = datasets.Value("string")
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features["academic_year"] = datasets.Value('int32')
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elif
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# metadata information
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features = datasets.Features({
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"assignment_id": datasets.Value("string"),
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"test": datasets.Value("string"),
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})
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elif
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features = main_features
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features["annotation"] = datasets.Value("string")
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elif
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features = main_features
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features["comments"] = datasets.Value("string")
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for key, line in enumerate(lines):
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d = json.loads(line)
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d = {k:v for k, v in d.items() if k in self.info.features}
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yield key, d
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an introduction to Python programming course at NUS (National University of Singapore).
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"""
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_NEW_CALEDONIA_DESCRIPTION = """
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The NewCaledonia dataset includes the programs submitted in 2020 by a group of 60 students from the University of New Caledonia,
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on a programming training platform. This plateform were developed and made available by the Computer Science department from the Orléans'
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Technological Institute (University of Orléans, France). This release contains a subset of the assignments.
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"""
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_DUBLIN_HOMEPAGE = """https://figshare.com/articles/dataset/_5_Million_Python_Bash_Programming_Submissions_for_5_Courses_Grades_for_Computer-Based_Exams_over_3_academic_years_/12610958"""
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_SINGAPORE_HOMEPAGE = """https://github.com/githubhuyang/refactory"""
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_NEW_CALEDONIA_HOMEPAGE = """https://github.com/GCleuziou/code2aes2vec/tree/master/Datasets"""
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_DUBLIN_CITATION = """
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@inproceedings{azcona2019user2code2vec,
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title={user2code2vec: Embeddings for Profiling Students Based on Distributional Representations of Source Code},
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}
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"""
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_NEW_CALEDONIA_CITATION = """
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@inproceedings{DBLP:conf/edm/CleuziouF21,
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author = {Guillaume Cleuziou and
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Fr{\'{e}}d{\'{e}}ric Flouvat},
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editor = {Sharon I{-}Han Hsiao and
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Shaghayegh (Sherry) Sahebi and
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Fran{\c{c}}ois Bouchet and
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Jill{-}J{\^{e}}nn Vie},
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title = {Learning student program embeddings using abstract execution traces},
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booktitle = {Proceedings of the 14th International Conference on Educational Data
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Mining, {EDM} 2021, virtual, June 29 - July 2, 2021},
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publisher = {International Educational Data Mining Society},
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year = {2021},
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timestamp = {Wed, 09 Mar 2022 16:47:22 +0100},
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biburl = {https://dblp.org/rec/conf/edm/CleuziouF21.bib},
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bibsource = {dblp computer science bibliography, https://dblp.org}
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}
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"""
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_DESCRIPTION = """
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Intro Programming. A dataset of student submissions to programming assignments.
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"""
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_DUBLIN_URLS = {
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}
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}
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_NEW_CALEDONIA_URLS = {
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"metadata": {
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"train": "./data/newcaledonia_metadata_train.jsonl",
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},
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_URLS = {
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"dublin": _DUBLIN_URLS,
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"singapore": _SINGAPORE_URLS,
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"newcaledonia": _NEW_CALEDONIA_URLS,
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}
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class IntroProgConfig(datasets.BuilderConfig):
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configurations = list(product(tasks, sources))
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configurations.append((tasks[0], "newcaledonia"))
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configurations.append((tasks[1], "newcaledonia"))
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BUILDER_CONFIGS = []
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for (task, description), source in configurations:
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BUILDER_CONFIGS.append(
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IntroProgConfig(
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name=f"{source}_{task}",
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version=VERSION,
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)
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)
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def _info(self):
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source, task = self.config.name.split("_")
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if source == "dublin":
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description = _DUBLIN_DESCRIPTION
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citation = _DUBLIN_CITATION
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homepage = _DUBLIN_HOMEPAGE
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elif source == "singapore":
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description =_SINGAPORE_DESCRIPTION
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citation = _SINGAPORE_CITATION
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homepage = _SINGAPORE_HOMEPAGE
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elif source == "newcaledonia":
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description = _NEW_CALEDONIA_DESCRIPTION
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citation = _NEW_CALEDONIA_CITATION
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homepage = _NEW_CALEDONIA_HOMEPAGE
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else:
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description = ""
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citation = ""
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homepage = ""
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main_features = datasets.Features({
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"submission_id": datasets.Value("int32"),
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"func_name": datasets.Value("string"),
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"description": datasets.Value(dtype='string'),
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"test": datasets.Value(dtype='string'),
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})
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if task == "data":
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features = main_features
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features["correct"] = datasets.Value(dtype="bool")
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if source == "dublin":
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features["user"] = datasets.Value("string")
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features["academic_year"] = datasets.Value('int32')
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features['date']: datasets.Value('timestamp[s]')
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elif task == "metadata":
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# metadata information
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features = datasets.Features({
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"assignment_id": datasets.Value("string"),
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"test": datasets.Value("string"),
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})
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elif task == "repair":
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features = main_features
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features["annotation"] = datasets.Value("string")
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elif task == "bug":
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features = main_features
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features["comments"] = datasets.Value("string")
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for key, line in enumerate(lines):
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d = json.loads(line)
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d = {k:v for k, v in d.items() if k in self.info.features}
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yield key, d
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