Stack Overflow is the largest online community for programmers to learn, share their knowledge, and advance their careers. Updated on a quarterly basis, this BigQuery dataset includes an archive of Stack Overflow content, including posts, votes, tags, and badges. This dataset is updated to mirror the Stack Overflow content on the Internet Archive, and is also available through the Stack Exchange Data Explorer. This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery .

Dataset Card for [Stackoverflow Post Questions]

  Dataset Description

Companies that sell Open-source software tools usually hire an army of Customer representatives to try to answer every question asked about their tool. The first step in this process is the prioritization of the question. The classification scale usually consists of 4 values, P0, P1, P2, and P3, with different meanings across every participant in the industry. On the other hand, every software developer… See the full description on the dataset page: https://huggingface.co/datasets/pacovaldez/stackoverflow-questions.

Dataset Card for Stack Overflow Chat Dutch

  Dataset Summary

This dataset contains 56,964 conversations between een AI assistant and a (fake) "Human" (generated) in Dutch, specifically in the domain of programming (Stack Overflow). They are translations of Baize's machine-generated answers to the Stack Overflow dataset. ☕ Want to help me out? Translating the data with the OpenAI API, and prompt testing, cost me 💸$133.60💸. If you like this dataset, please consider buying… See the full description on the dataset page: https://huggingface.co/datasets/BramVanroy/stackoverflow-chat-dutch.

This dataset is derived from the Stack Overflow Data hosted by kaggle.com and available to query through Kernels using the BigQuery API: https://www.kaggle.com/stackoverflow/stackoverflow

mlfoundations-dev/stackoverflow dataset hosted on Hugging Face and contributed by the HF Datasets community

The dataset contains 60,000 Stack Overflow questions from 2016-2020, classified into three categories:

HQ: High-quality posts without a single edit. LQ_EDIT: Low-quality posts with a negative score, and multiple community edits. However, they still remain open after those changes. LQ_CLOSE: Low-quality posts that were closed by the community without a single edit.

Notes

Questions are sorted according to Question Id. Question body is in HTML format. All dates are in UTC format. The dataset is also accessible at https://www.kaggle.com/imoore/60k-stack-overflow-questions-with-quality-rate

How to cite This is an original dataset, published under MIT License. Please cite the dataset for your usage as the following:

@article{annamoradnejad2022multiview, title={Multi-View Approach to Suggest Moderation Actions in Community Question Answering Sites}, author={Annamoradnejad, Issa and Habibi, Jafar and Fazli, Mohammadamin}, journal = {Information Sciences}, volume = {600}, pages = {144-154}, year = {2022}, issn = {0020-0255}, doi = {https://doi.org/10.1016/j.ins.2022.03.085}, url = {https://www.sciencedirect.com/science/article/pii/S0020025522003127} }

Russian StackOverflow dataset

  Description

Summary: Dataset of questions, answers, and comments from ru.stackoverflow.com. Script: create_stackoverflow.py Point of Contact: Ilya Gusev Languages: The dataset is in Russian with some programming code.

  Usage

Prerequisites: pip install datasets zstandard jsonlines pysimdjson

Loading: from datasets import load_dataset dataset = load_dataset('IlyaGusev/ru_stackoverflow', split="train") for example in dataset:… See the full description on the dataset page: https://huggingface.co/datasets/IlyaGusev/ru_stackoverflow.

This data set contains anonymized data collected from Reddit (via the Pushshift API) and StackOverflow (from Kaggle's dataset).

Each folder includes the data split by trimester. The schema of StackOverflow and Reddit-related files follows:

• Fields from StackOverflow
  • question_id
  • answer_id
  • creation_date - answer creation_date
  • score - score of the question/answer
  • tags - all tags flagged for a question
  • answer_count - number of answers for a question
  • start_question - question's time of creation
  • last_activity_date - last update on the question
  • new_id - hashed id of the answerer
  • q_new_id - hashed id of the questioner
• Fields from Reddit
  • comment_id
  • submission_id
  • score - score of the question/submission
  • subreddit
  • created_utc - time of creation (unrelated to last modified comments)
  • new_id - hashed id

The .txt files represent the structure of the corresponding hypergraphs.

The Stack Overflow dataset, a detailed archive of posts, votes, tags, and badges from the world’s largest programmer community.

Introduction

Stack Overflow Statistics: The 2024 Stack Overflow Developer Survey offers a comprehensive snapshot of the global developer community, compiling insights from 65,437 respondents across 185 countries. Conducted between May 19 and June 20, 2024, the survey had a median completion time of approximately 21 minutes.

A significant 76% of developers reported using or planning to use AI tools in their development processes, marking an increase from 70% in 2023. However, trust in AI tool accuracy remains divided, with only 43% expressing confidence in their outputs. Despite this, 81% of developers identified increased productivity as the primary benefit of integrating AI tools into their workflows.

Educational backgrounds among respondents show that 66% hold a Bachelor's or Master's degree, even though only 49% learned to code through formal education.

Geographically, the United States accounted for 18.9% of respondents, followed by Germany at 8.4% and India at 7.2%, highlighting the survey's extensive international reach.

This year's survey underscores the evolving landscape of software development, emphasizing the growing integration of AI tools, the shift towards self-directed learning, and the diverse global composition of the developer community.

This article will highlight the Stack Overflow statistics and its performance.

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.

Stackoverflow

This is a collection of ~40k QA's in C Language from StackOverflow. The data has been initially cleaned, and each response is with Accepted Answer. All data is <1000 in length. The questions and answers were organized into a one-line format. A sample format is shown below: { "question": "``` FILE* file = fopen(some file)

pcap_t* pd = pcap_fopen_offline(file)

pcap_close(pd)

fclose(file) ```

This code occurs double free error.

Could you explain about this happening?

My… See the full description on the dataset page: https://huggingface.co/datasets/Mxode/StackOverflow-QA-C-Language-40k.

Analysis of ‘Stack Overflow Tags Data’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/isaacwen/stack-overflow-tags-data on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context

A common question for those new and familiar to computer science and software engineering is what is the most best and/or most popular programming language. It is very difficult to give a definitive answer, as there are a seemingly indefinite number of metrics that can define the 'best' or 'most popular' programming language.

One such metric that can be used to define a 'popular' programming language is the number of posts relating to that language on public forums. With Stack Overflow being perhaps the most commonly used forum for questions related to programming languages, analyzing the number of posts and other metrics for specific programming languages on Stack Overflow can be a good indicator for the popularity of a language.

Content

This dataset contains statistics about posts, views, answers, comments, and favorites relating to the 1000 most popular tags on Stack Overflow, including those designated for questions relating to specific programming languages such as 'python' and 'javascript'. The data is from 2008 to 2021, and is sorted into rows for each tag, for each year.

Source

This data was queried and aggregated from BigQuery's public stackoverflow dataset.

--- Original source retains full ownership of the source dataset ---

Context

This is the output of the Stack Rudeness kernel (https://www.kaggle.com/ojwatson/stack-rudeness), as saved in Cell 17.

Content

Stack Overflow answers by the Top 10 r and python users extracted using BigQuery. Also includes data on whether the answer was accepted and some additional data based on sentiment analysis of the answer text.

Acknowledgements

BigQuery and StackOverflow

Dataset with the text of 10% of questions and answers from the Stack Overflow programming Q&A website.

This is organized as three tables:

• Questions contains the title, body, creation date, closed date (if applicable), score, and owner ID for all non-deleted Stack Overflow questions whose Id is a multiple of 10.
• Answers contains the body, creation date, score, and owner ID for each of the answers to these questions. The ParentId column links back to the Questions table.
• Tags contains the tags on each of these questions

Datasets of all R questions and all Python questions are also available on Kaggle, but this dataset is especially useful for analyses that span many languages.

Example projects include:

• Identifying tags from question text
• Predicting whether questions will be upvoted, downvoted, or closed based on their text
• Predicting how long questions will take to answer

License

All Stack Overflow user contributions are licensed under CC-BY-SA 3.0 with attribution required.

The paper discusses the use of multi-objective Bayesian optimization for hyperparameter transfer in topic models.

post tags

Datasets of Time Series of Social Media Activity. It includes 16.2 million YouTube videos, 0.8 million Usenet threads, 4.6 million Stack-Overflow questions and 70 thousands PLOS ONE papers. This data is used in JM Miotto, EG Altmann, 'Predictability of extreme events in social media', arXiv:1403.3616.

Stack Overflow 2022-06 data dump in a SQL Server database # Stack Overflow SQL Server Database - 2022-06 Version For more information and the latest release: Imported from the Stack Exchange Data Dump as of June 2022: Imported using the Stack Overflow Data Dump Importer: This database is in Microsoft SQL Server 2016 format, which means you can attach it to any SQL Server 2016 or newer instance. To keep the size small but let you get started fast: * All tables have a clustered index with page compression on * No nonclustered or full text indexes are included * The log file is small, and you should grow it out if you plan to modify data * It s distributed as an mdf/ldf so you don t need space to restore it * It only includes StackOverflow.com data, not data for other Stack sites As with the original data dump, this is provided under cc-by-sa 4.0 license: