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c9041c5c5e
* preorder, inorder, postorder -> pre-order, in-order, post-order * Bug fixes * Bug fixes * Update what_is_dsa.md * Sync zh and zh-hant versions * Sync zh and zh-hant versions. * Update performance_evaluation.md and time_complexity.md * Add @khoaxuantu to the landing page. * Sync zh and zh-hant versions * Add @ khoaxuantu to the landing page of zh-hant and en versions. * Sync zh and zh-hant versions. * Small improvements * @issue : #1450 (#1453) Fix writing "obsecure" to "obscure" Co-authored-by: Gaya <kheliligaya@gmail.com> * Update the definition of "adaptive sorting". * Update n_queens_problem.md * Sync zh, zh-hant, and en versions. --------- Co-authored-by: Gaya-Khelili <50716339+Gaya-Khelili@users.noreply.github.com> Co-authored-by: Gaya <kheliligaya@gmail.com>
129 lines
6 KiB
Markdown
129 lines
6 KiB
Markdown
# Contributing guidelines for Chinese-to-English
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We are working on translating "Hello Algo" from Chinese to English with the following approach:
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1. **AI translation**: Carry out an initial pass of translations using large language models.
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2. **Human optimization**: Manually refine the machine-generated outputs to ensure authenticity and accuracy.
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3. **Pull request review**: The optimized translation will be double checked by the reviewers through GitHub pull request workflow.
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4. Repeat steps `2.` and `3.` for further improvements.
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## Join us
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We're seeking contributors who meet the following criteria.
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- **Technical background**: Strong foundation in computer science, particularly in data structures and algorithms.
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- **Language skills**: Native proficiency in Chinese with professional-level English, or native English.
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- **Available time**: Dedicated to contributing to open-source projects with a willingness to engage in long-term translation efforts.
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That is, our contributors are computer scientists, engineers, and students from different linguistic backgrounds, and their objectives have different focal points:
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- **Native Chinese with professional working English**: Ensuring translation accuracy and consistency between CN and EN versions.
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- **Native English**: Enhance the authenticity and fluency of the English content to flow naturally and to be engaging.
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Don't hesitate to join us via WeChat `krahets-jyd` or on [Discord](https://discord.gg/nvspS56295)!
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## Translation process
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> [!important]
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> Before diving in, ensure you're comfortable with the GitHub pull request workflow and have read the "Translation standards" and "Pseudo-code for translation" below.
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1. **Self-assignment**: Visit [GitHub projects](https://github.com/users/krahets/projects/2/views/4) to select an unclaimed task and mark it as `In Progress`.
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2. **Translation**: We encourage preserving the original meaning while ensuring the translation is natural and fluent.
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3. **Peer review**: Please carefully check your changes before submitting a Pull Request (PR). After approval by two reviewers, it will be merged into the project.
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## Translation standards
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> [!tip]
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> The "Accuracy" and "Authenticity" are primarily handled by native Chinese speakers and native English speakers, respectively.
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>
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> In some instances, "Accuracy (consistency)" and "Authenticity" represent a trade-off, where optimizing one aspect could significantly affect the other. In such cases, please leave a comment in the pull request for discussion.
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**Accuracy**:
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- Maintain consistency in terminology across translations by referring to the [Terminology](https://www.hello-algo.com/chapter_appendix/terminology/) section.
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- Prioritize technical accuracy and maintain the tone and style of the Chinese version.
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- Always take into account the content and context of the Chinese version to ensure modifications are accurate and comprehensive.
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**Authenticity**:
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- Translations should flow naturally and fluently, adhering to English expression conventions.
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- Always consider the context of the content to harmonize the article.
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- Be aware of cultural differences between Chinese and English. For instance, Chinese "pinyin" does not exist in English.
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- If the optimized sentence could alter the original meaning, please add a comment for discussion.
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**Formatting**:
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- Figures and tables will be automatically numbered during deployment, so DO NOT manually number them.
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- Each PR should cover at least one complete document to ensure manageable review sizes, except for bug fixes.
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**Review**:
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- During the review, prioritize evaluating the changes, consulting the surrounding context as needed.
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- Learning from each other's perspectives can lead to better translations and more cohesive results.
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## Translation pseudo-code
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The following pseudo-code models the steps in a typical translation process.
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```python
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def optimize_translation(markdown_texts, lang_skill):
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"""Optimize the translation"""
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for sentence in markdown_texts:
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"""Accuracy is handled primarily by native Chinese speakers"""
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if lang_skill is "Native Chinese + Professional working English":
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if is_accurate_Chinese_to_English(sentence):
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continue
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# Optimize the accuracy
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result = refine_accuracy(sentence)
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"""
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Authenticity is handled primarily by native English speakers
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and secondarily by native Chinese speakers
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"""
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if is_authentic_English(sentence):
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continue
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# Optimize the authenticity
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result = refine_authenticity(sentence)
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# Add comments in the PR if it may break consistency
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if break_consistency(result):
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add_comment(description)
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pull_request = submit_pull_request(markdown_texts)
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# The PR will be merged after approved by >= 2 reviewers
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while count_approvals(pull_request) < 2:
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continue
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merge(pull_request)
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```
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The following pseudo-code is for the reviewers:
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```python
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def review_pull_requests(pull_request, lang_skill):
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"""Review the PR"""
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# Loop through all the changes in the PR
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while is_anything_left_to_review(pull_request):
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change = get_next_change(pull_request)
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"""Accuracy is handled primarily by native Chinese speakers"""
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if lang_skill is "Native Chinese + Professional working English":
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# Check the accuracy(consistency) between CN and EN versions
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if is_accurate_Chinese_to_English(change):
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continue
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# Optimize the accuracy(consistency)
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result = refine_accuracy(change)
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# Add comments in the PR
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add_comment(result)
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"""
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Authenticity is handled primarily by native English speakers
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and secondarily by native Chinese speakers
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"""
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if is_authentic_English(change):
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continue
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# Optimize the authenticity if it is not authentic English
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result = refine_authenticity(change)
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# Add comments in the PR
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add_comment(result)
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approve(pull_request)
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```
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