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Supplementary materials for paper "Characterizing and Classifying Developer Forum Posts with their Intentions"

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Supplementary materials for "Characterizing and Classifying Developer Forum Posts with their Intentions"

Code

Academic use only.

model.py: model definition

train.py: code for model training, configurations can be modified.

predict.py: generating prediction results for new samples

We also provide a tool to calculate the metrics used in our manuscript.

python ./tools/evaluation.py -h shows the usage of the tool.

About the dataset

The annotated dataset used in our study is shared under the ./dataset folder.

Format: We share dataset in npy format to facilitate model training and evaluation to replicate our experimental results.

Number of posts: 784

Intention labels are manually annotated.

The source of posts can be identified by the url (id key).

Load data

import numpy as np
dataset = np.load(path, allow_pickle=True)

Data format

Keys

label, id, title, description, description_raw, code, code_fea

Example

{'label': ['Errors'],
 'id': 'https://stackoverflow.com/questions/72557738',
 'title': 'Command "python setup.py egg_info" failed with error code 1 in /tmp/pip-build-epojkmk3/duckdb/',
 'description': 'I\'m trying to set up mindsdb in local(visual studio code) with (python version 3.7) using pip3 install mindsdb command but facing an error. Command "python setup.py egg_info" failed with error code 1 in /tmp/pip-build-epojkmk3/duckdb/ How do I resolving this error?',
 'description_raw': "<p>I'm trying to set up mindsdb in local(visual studio code) with (python version 3.7) using</p>\n<pre><code>pip3 install mindsdb \n</code></pre>\n<p>command but facing an error.</p>\n<pre><code>Command &quot;python setup.py egg_info&quot; failed with error code 1 in /tmp/pip-build-epojkmk3/duckdb/\n</code></pre>\n<p>How do I resolving this error?</p>\n",
 'code': ['pip3 install mindsdb \n',
  'Command &quot;python setup.py egg_info&quot; failed with error code 1 in /tmp/pip-build-epojkmk3/duckdb/\n'],
 'code_fea': array([0.01638031, 0.01324874, 0.19329876, 0.13227859, 0.97585787])}

Dataset preprocessing

The dataset has been preprocessed. We preprocess the raw HTML using BeautifulSoup library. Sample code can be found in tools folder.

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Supplementary materials for paper "Characterizing and Classifying Developer Forum Posts with their Intentions"

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