{"url":"/dataset/multi-lingual-bug-reports","name":"Multi Lingual Bug Reports","full_name":null,"description_markdown":"## Dataset Description\r\n\r\nThe dataset used in this study comprises bug reports extracted from the Visual Studio Code GitHub repository, specifically focusing on those labeled with the english-please tag. This label indicates that the original submission was written in a language other than English, providing a clear signal for multilingual content. The dataset spans a five-year period (March 2019--June 2024), ensuring a diverse representation of bug types, user environments, and technical contexts.\r\n\r\n### Characteristics\r\nThe dataset contains **1,381** multilingual bug reports, each consisting of:\r\n- The **original bug report** written in a non-English language.\r\n- A **translated version** in English.\r\n- Metadata such as issue number, creation date, labels, and status.\r\n- Categorization into **functional, UI, and performance-related** issues based on the content.\r\n\r\n### Motivation & Summary\r\nThis dataset is motivated by the need to **improve multilingual bug tracking and translation evaluation**. Given the increasing globalization of software development, developers and QA teams frequently encounter bug reports in languages they do not understand. By providing a structured corpus of translated bug reports, this dataset facilitates:\r\n- **Comparative translation evaluation** (e.g., ChatGPT vs AWS Translate vs DeepL).\r\n- **Linguistic analysis** of technical bug reporting across different languages.\r\n- **Insights into common software issues** encountered by diverse users.\r\n- **Improving multilingual issue tracking** through automated labeling and categorization.\r\n\r\n### Potential Use Cases\r\nThis dataset can be beneficial for various research and development applications, including:\r\n- **Machine Translation Benchmarking**: Evaluating the performance of translation models in a technical domain.\r\n- **Natural Language Processing (NLP) Tasks**: Training classifiers to categorize bug reports based on their content.\r\n- **Software Engineering Research**: Understanding trends in bug reporting, issue resolution, and localization challenges.\r\n- **Automated Bug Triage**: Developing AI-driven solutions for assigning and prioritizing bug reports in multilingual repositories.","description_withheld":null,"homepage":"https://github.com/av9ash/gitbugs/blob/main/multilingual/README.md","introduced_date":"2025-02-20","introduced_date_note":null,"introduced_by":{"paper":"/paper/english-please-evaluating-machine-translation","title":"English Please: Evaluating Machine Translation with Large Language Models for Multilingual Bug Reports","first_author":"Avinash Patil","url":null},"license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Texts","url":"/datasets/modality/texts"},{"name":"Graphs","url":"/datasets/modality/graphs"}],"tasks":[{"name":"Machine Translation","url":"/task/machine-translation","datasets_with_task":"/datasets/task/machine-translation"},{"name":"Zero-Shot Machine Translation","url":"/task/zero-shot-machine-translation","datasets_with_task":"/datasets/task/zero-shot-machine-translation"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["Multi Lingual Bug Reports"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/machine-translation-on-multi-lingual-bug","task":"Machine Translation","dataset_variant":"Multi Lingual Bug Reports","rows":1,"metrics":["BERTScore"],"first_row_in_archive_order":{"model":"ChatGPT","paper":"/paper/english-please-evaluating-machine-translation","metrics":{"BERTScore":"79"},"code_links":[{"title":"av9ash/English-Please","url":"https://github.com/av9ash/English-Please"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/english-please-evaluating-machine-translation","title":"English Please: Evaluating Machine Translation with Large Language Models for Multilingual Bug Reports","date":"2025-02-20","rows_on_this_dataset":1,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}