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[fix] fix typos in user_case document.
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doc/user_case.en.md

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# Use Cases
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## Querying Code Features
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Little-Developer wants to know which String type variables are used in Repo A, so he writes a Gödel script as follows and submits it to the CodeFuse-Query system for results.
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A developer wants to know which String type variables are used in Repo A, so he writes a Gödel script as follows and submits it to the CodeFuse-Query system for results.
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```rust
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// script
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use coref::java::*
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```
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Similar needs: querying for classes, functions, variables, return values, call graphs, class inheritance, etc.
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## Code Rule Checker
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Little-TL found that the team always wrote many bugs similar to Bug A. **He wanted to establish a code rule for Bug A and its checker** and do a check at the CodeReview stage. Through writing a query analysis on the CodeFuse-Query platform, and after testing it on the platform to meet the requirements, he solidified this analysis query as a code rule and launched it to the CodeReview/CI stage. Since then, this bug has never happened again.
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A team leader found that the team always wrote many bugs similar to Bug A. **He wanted to establish a code rule for Bug A and its checker** and do a check at the CodeReview stage. Through writing a query analysis on the CodeFuse-Query platform, and after testing it on the platform to meet the requirements, he solidified this analysis query as a code rule and launched it to the CodeReview/CI stage. Since then, this bug has never happened again.
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Similar needs: writing static defect scanning rules for code risk interception.
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## Obtaining Statistical Data
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Little-Researcher found that traditional code complexity metrics are difficult to accurately measure code complexity. By learning from international advanced experience and a stroke of genius, he designed a set of complexity metrics and algorithms. After implementing it with Gödel, **he found that without much optimization, the performance was already very high**, and it was quickly applied to more than 10 languages and over 110,000 repositories. He immediately had an in-depth understanding of the overall complexity of code repositories. Compared to the past, when he had to parse code and analyze syntax trees himself, and interface with systems, **it's hard to know how much more convenient it has become**.
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A researcher found that traditional code complexity metrics are difficult to accurately measure code complexity. By learning from international advanced experience and a stroke of genius, he designed a set of complexity metrics and algorithms. After implementing it with Gödel, **he found that without much optimization, the performance was already very high**, and it was quickly applied to more than 10 languages and over 110,000 repositories. He immediately had an in-depth understanding of the overall complexity of code repositories. Compared to the past, when he had to parse code and analyze syntax trees himself, and interface with systems, **it's hard to know how much more convenient it has become**.
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Similar needs: code statistics, code metrics, algorithm design, academic research.
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# Application Fields
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- Analyze the affected objects based on the code changes (file + line number): methods, entry points (http entry, hsf entry), call routes (all call routes from entry to changed method), database operations (table, operation type)
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- Combined with the online dynamic call route (method route), CodeFuse-Query static analysis call route impact surface precise analysis capability, improve the effectiveness and preparation rate of change analysis impact surface
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Up to now, Youku has integrated all core applications through CodeFuse-Query, collected static analysis data, and built a complete server-side code knowledge base and traffic knowledge base.
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Up to now, Youku has integrated all core applications through CodeFuse-Query and has built a comprehensive server-side code knowledge base and network traffic knowledge base based on static analysis.

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