five

Replication package for the paper "What do Developers Discuss about Code Comments"

收藏
NIAID Data Ecosystem2026-03-12 收录
下载链接:
https://zenodo.org/record/4470125
下载链接
链接失效反馈
官方服务:
资源简介:
# RP-commenting-practices-multiple-sources Replication package for the paper "What do Developers Discuss about Code Comments?" ## Structure ``` Appendix.pdf Tags-topics.md Stack-exchange-query.md RQ1/ LDA_input/ combined-so-quora-mallet-metadata.csv topic-input.mallet LDA_output/ Mallet/ output_csv/ docs-in-topics.csv topic-words.csv topics-in-docs.csv topics-metadata.csv output_html/ all_topics.html Docs/ Topics/ RQ2/ datasource_rawdata/ quora.csv stackoverflow.csv manual_analysis_output/ stackoverflow_quora_taxonomy.xlsx ``` ## Contents of the Replication Package --- - **Appendix.pdf**- Appendix of the paper containing supplement tables - **Tags-topics.md** tags selected from Stack overflow and topics selected from Quora for the study (RQ1 & RQ2) - **Stack-exchange-query.md** the query interface used to extract the posts from stack exchnage explorer. - **RQ1/** - contains the data used to answer RQ1 - **LDA_input/** - input data used for LDA analysis - `combined-so-quora-mallet-metadata.csv` - Stack overflow and Quora questions used to perform LDA analysis - `topic-input.mallet` - input file to the mallet tool - **LDA_output/** - **Mallet/** - contains the LDA output generated by MALLET tool - **output_csv/** - `docs-in-topics.csv` - documents per topic - `topic-words.csv` - most relevant topic words - `topics-in-docs.csv` - topic probability per document - `topics-metadata.csv` - metadata per document and topic probability - **output_html/** - Browsable results of mallet output - `all_topics.html` - `Docs/` - `Topics/` - **RQ2/** - contains the data used to answer RQ2 - **datasource_rawdata/** - contains the raw data for each source - `quora.csv` - contains the processed dataset (like removing html tags). To know more about the preprocessing steps, please refer to the reproducibility section in the paper. The data is preprocessed using Makar tool. - `stackoverflow.csv` - contains the processed stackoverflow dataset. To know more about the preprocessing steps, please refer to the reproducibility section in the paper. The data is preprocessed using Makar tool. - **manual_analysis_output/** - `stackoverflow_quora_taxonomy.xlsx` - contains the classified dataset of stackoverflow and quora and description of taxonomy. - `Taxonomy` - contains the description of the first dimension and second dimension categories. Second dimension categories are further divided into levels, separated by `|` symbol. - `stackoverflow-posts` - the questions are labelled relevant or irrelevant and categorized into the first dimension and second dimension categories. - `quota-posts` - the questions are labelled relevant or irrelevant and categorized into the first dimension and second dimension categories. ---
创建时间:
2021-06-30
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作