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

<pre><code class="language-markdown"># 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 &amp; 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. --- </code></pre>

# RP-commenting-practices-multiple-sources 论文《开发者如何讨论代码注释？》的复现数据包
## 数据集结构

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

## 复现数据包内容说明
---
- **Appendix.pdf**：论文附录，收录论文补充附表
- **Tags-topics.md**：本研究（RQ1与RQ2）所用的Stack Overflow标签与Quora主题集合
- **Stack-exchange-query.md**：用于从Stack Exchange Explorer中提取帖子的查询脚本
- **RQ1/**：包含用于解答研究问题1的相关数据
- **LDA_input/**：潜在狄利克雷分配（LDA）分析所用的输入数据
- `combined-so-quora-mallet-metadata.csv`：用于执行LDA分析的Stack Overflow与Quora问题数据集
- `topic-input.mallet`：Mallet主题建模工具的输入文件
- **LDA_output/**：
- **Mallet/**：由Mallet工具生成的LDA分析输出结果
- **output_csv/**：
- `docs-in-topics.csv`：各主题对应的文档列表
- `topic-words.csv`：各主题的核心关联词汇
- `topics-in-docs.csv`：单文档的主题概率分布
- `topics-metadata.csv`：文档元数据及对应主题概率
- **output_html/**：Mallet输出结果的可浏览可视化页面
- `all_topics.html`：全主题展示页面
- `Docs/`：文档集目录
- `Topics/`：主题集目录
- **RQ2/**：包含用于解答研究问题2的相关数据
- **datasource_rawdata/**：各数据源的预处理后原始数据
- `quora.csv`：已完成预处理的Quora数据集。预处理流程详见论文可复现性章节，本数据集通过Makar工具完成预处理。
- `stackoverflow.csv`：已完成预处理的Stack Overflow数据集。预处理流程详见论文可复现性章节，本数据集通过Makar工具完成预处理。
- **manual_analysis_output/**：
- `stackoverflow_quora_taxonomy.xlsx`：Stack Overflow与Quora数据集的分类结果及分类体系说明文档
- `Taxonomy`：包含分类体系的一级、二级分类维度说明，二级分类进一步按层级划分，层级间以`|`符号分隔
- `stackoverflow-posts`：已标注相关性（相关/不相关）并完成一级、二级分类的Stack Overflow问题数据集
- `quota-posts`：已标注相关性（相关/不相关）并完成一级、二级分类的对应问题数据集
---