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coref library reference main document will be generated by script
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doc/1_abstract.md

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title: "摘要"
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layout: about
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nav_order: 2
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---
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随着大规模软件开发的普及,对可扩展且易于适应的静态代码分析技术的需求正在加大。传统的静态分析工具,如 Clang Static Analyzer (CSA) 或 PMD,在检查编程规则或样式问题方面已经展现出了良好的效果。然而,这些工具通常是为了满足特定的目标而设计的,往往无法满足现代软件开发环境中多变和多元化的需求。这些需求可以涉及服务质量 (QoS)、各种编程语言、不同的算法需求,以及各种性能需求。例如,安全团队可能需要复杂的算法,如上下文敏感的污点分析,来审查较小的代码库,而项目经理可能需要一种相对较轻的算法,例如计算圈复杂度的算法,以在较大的代码库上测量开发人员的生产力。
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这些多元化的需求,加上大型组织中常见的计算资源限制,构成了一项重大的挑战。由于传统工具采用的是问题特定的计算方式,往往无法在这种环境中实现扩展。因此,我们推出了 CodeQuery,这是一个专为大规模静态分析设计的集中式数据平台。

doc/2_introduction.md

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title: "简介"
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layout: default
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CodeFuse-Query 是一个支持对 **各种编程语言** 进行 **结构化分析****代码数据平台**。核心思想是利用各种语言解析器将所有代码转化为数据,并将其结构化存储到代码数据库中。通过使用自定义查询语言,按照业务需求进行数据分析。如下图所示:
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![image.png](../assets/introduction01.png)
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doc/3_install_and_run.md

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title: "安装、配置、运行"
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layout: page
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# 安装、配置、运行
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## 硬件和软件要求

doc/4_godelscript_language.md

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title: "GödelScript 查询语言"
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layout: default
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# GödelScript 查询语言
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## 目录

doc/5_toolchain.md

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title: "开发插件 (VSCode)"
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layout: default
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# 开发插件(VSCode)
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## 安装
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doc/coref_library_reference.md

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doc/index.md

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## 文档 (Documentation)
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- [引言](1_abstract.html)
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- [概述](2_introduction.html)
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- [安装、配置、运行](3_install_and_run.html)
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- [GödelScript 查询语言介绍](4_godelscript_language.html)
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- [VSCode开发插件](5_toolchain.html)
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- [COREF Library Reference](coref_library_reference.html)
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- [引言](1_abstract.md)
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- [概述](2_introduction.md)
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- [安装、配置、运行](3_install_and_run.md)
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- [GödelScript 查询语言介绍](4_godelscript_language.md)
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- [VSCode开发插件](5_toolchain.md)

doc/tools/generate_markdown.py

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continue
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semantic_dict[file["name"]] = result.stdout.decode("utf-8")
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def dump_reference_main_doc():
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output_file_path = markdown_output_path + "/coref_library_reference.md"
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output_data = "---\n"
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output_data += "title: \"COREF Library Reference\"\n"
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output_data += "layout: default\n"
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output_data += "nav_order: 2\n"
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output_data += "has_children: true\n"
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output_data += "---\n\n"
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output_data += "# COREF Library Reference\n\n"
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for file in input_file_list:
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output_data += "* [coref::" + name_mapper[file["name"]] + "]"
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output_data += "(./" + name_mapper[file["name"]] + "/reference.html)\n"
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open(output_file_path, "w").write(output_data)
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dump_reference_main_doc()
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for file in input_file_list:
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file_full_path = file["path"] + "/" + file["name"]
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print("Generate markdown for " + file_full_path)

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