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--- a/README.md
+++ b/README.md
-# The LLVM Compiler Infrastructure
+## 容器创建
+docker run -it unifuzz:2.0 bash
-This directory and its subdirectories contain source code for LLVM,
-a toolkit for the construction of highly optimized compilers,
+## 编译源码工程
-optimizers, and runtime environments.
+**首先在进行以下编译之前，要保证正常情况下是能够编译通过的，也就是工程相关的依赖都已经安装，我们假设工程依赖都已经安装好。**
+我们以vim工程为例，说明下编译流程
-The README briefly describes how to get started with building LLVM.
+- 用AFL编译工程生成用于fuzz的可执行文件（我们称之为fuzz_binary），该编译过程可以参照AFL编译流程，对应的vim编译流程为:
-For more information on how to contribute to the LLVM project, please
+  - $cd /path/to/vim-afl 进入到vim工程源码目录
-take a look at the
+  - $CC=/home/AFL/afl-gcc ./configure
-[Contributing to LLVM](https://llvm.org/docs/Contributing.html) guide.
+  - $make -j20
+  - 完成之后我们可以得到AFL插桩后的可执行文件vim，也就是fuzz_binary
-## Getting Started with the LLVM System
+- 用llvm编译工程生成用于产生精确覆盖率的可执行文件（我们称之为visual_binary）和用于可视化展示的静态分析json文件（我们称之为visual_json），对应的vim编译流程为:
+  - $cd /path/to/vim-llvm 进入到另外一个vim工程源码目录（一般需要将源码压缩文件解压到两个不同的目录中，一个用于AFL的编译，一个用于llvm的编译）
-Taken from https://llvm.org/docs/GettingStarted.html.
+  - $CC="/home/llvm-10-visual-mode-1.0/llvm-build-release-install/bin/clang" CFLAGS="-w -flto -g /home/afl-llvm-rt.o.c.o" CXX="/home/llvm-10-visual-mode-1.0/llvm-build-release-install/bin/clang++" CXXFLAGS="-w -flto -g /home/afl-llvm-rt.o.c.o" LDFLAGS="-L/home/llvm-10-visual-mode-1.0/llvm-build-release-install/lib/clang/10.0.0/lib/linux -lclang_rt.builtins-x86_64" RANLIB=/bin/true AR=/home/llvm-10-visual-mode-1.0/llvm-build-release-install/bin/llvm-ar NM=/home/llvm-10-visual-mode-1.0/llvm-build-release-install/bin/llvm-nm ./configure（该构建命令对应的是Makefile构建系统，如果构建系统是cmake，相应的命令为cmake -DCMAKE_C_COMPILER=/home/llvm-10-visual-mode-1.0/llvm-build-release-install/bin/clang -DCMAKE_CXX_COMPILER=/home/llvm-10-visual-mode-1.0/llvm-build-release-install/bin/clang++ -DCMAKE_C_FLAGS="-w -flto -g /home/afl-llvm-rt.o.c.o" -DCMAKE_CXX_FLAGS="-w -flto -g /home/afl-llvm-rt.o.c.o" -DCMAKE_RANLIB=/bin/true -DCMAKE_AR=/home/llvm-10-visual-mode-1.0/llvm-build-release-install/bin/llvm-ar -DCMAKE_NM=/home/llvm-10-visual-mode-1.0/llvm-build-release-install/bin/llvm-nm .）
+  - Makefile构建系统的工程中，有时候上述configure构建命令会在编译时出现xxx.o: file not recognized: file format not recognized导致编译失败，这时可以用CC="/home/llvm-10-visual-mode-1.0/llvm-build-release-install/bin/clang -w -flto -g /home/afl-llvm-rt.o.c.o" CXX="/home/llvm-10-visual-mode-1.0/llvm-build-release-install/bin/clang++ -w -flto -g /home/afl-llvm-rt.o.c.o" LDFLAGS="-L/home/llvm-10-visual-mode-1.0/llvm-build-release-install/lib/clang/10.0.0/lib/linux -lclang_rt.builtins-x86_64" RANLIB=/bin/true AR=/home/llvm-10-visual-mode-1.0/llvm-build-release-install/bin/llvm-ar NM=/home/llvm-10-visual-mode-1.0/llvm-build-release-install/bin/llvm-nm ./configure构建命令来替代原来的构建命令
-### Overview
+  - $make -j20
+  - 完成之后我们可以得到llvm插桩后的可执行文件vim，也就是visual_binary，还有用于可视化展示的静态分析json文件vim-172825.json，其中172825表示该可执行文件中包含的基本块个数
-Welcome to the LLVM project!
+# 镜像制作
-The LLVM project has multiple components. The core of the project is
+- 用docker cp命令从容器中拷贝fuzz_binary、visual_binary、visual_json三个文件到本地
-itself called "LLVM". This contains all of the tools, libraries, and header
+  - docker cp container-id:/path/to/fuzz_binary /local/path/dir
-files needed to process intermediate representations and converts it into
+  - docker cp container-id:/path/to/visual_binary /local/path/dir
-object files.  Tools include an assembler, disassembler, bitcode analyzer, and
+  - docker cp container-id:/path/to/visual_json /local/path/dir
-bitcode optimizer.  It also contains basic regression tests.
+- 从容器中删除llvm目录和AFL目录（为了使生成的docker镜像尽可能小）
+  - docker exec -it container-id bash
-C-like languages use the [Clang](http://clang.llvm.org/) front end.  This
+  - cd /home && rm -rf llvm-10-visual-mode-1.0 && rm -rf AFL
-component compiles C, C++, Objective C, and Objective C++ code into LLVM bitcode
+- export容器到镜像文件
-- and from there into object files, using LLVM.
+  - docker export -o image_name.tar container-id
+- 用save命令生成镜像文件（原因是目前unifuzz网页系统不支持export命令生成的镜像文件，只支持save命令生成的镜像文件）
-Other components include:
+  - docker import image_name.tar REPOSITORY:TAG
-the [libc++ C++ standard library](https://libcxx.llvm.org),
+  - docker run -it REPOSITORY:TAG bash（假设生成的容器为container-id2）
-the [LLD linker](https://lld.llvm.org), and more.
+  - docker commit container-id2 REPOSITORY1:TAG1
+  - docker save -o image_name2.tar REPOSITORY1:TAG1
-### Getting the Source Code and Building LLVM
+**最终我们生成一个名字为image_name2.tar的镜像文件**
-The LLVM Getting Started documentation may be out of date.  The [Clang
-Getting Started](http://clang.llvm.org/get_started.html) page might have more
+# 测试
-accurate information.
+- 正常的unifuzz测试参照unifuzz使用文档
+- 精确覆盖率测试
-This is an example workflow and configuration to get and build the LLVM source:
+  - 首先在程序管理中找到要被测程序，点击修改
+  - 分别上传分析程序（对应于生成的visual_binary）、源代码（对应于源代码的压缩包）、JSON文件（对应于生成的visual_json）
-1. Checkout LLVM (including related subprojects like Clang):
+  - 在任务管理中找到对应的任务，点击启动按钮进行正常fuzz测试，运行一段时间后，点击“暂停”按钮，再点击“分析”按钮开始做精确覆盖率分析，等待分析完成，点击“详情”按钮，在详情页面点击“精确覆盖率”
-     * ``git clone https://github.com/llvm/llvm-project.git``
-     * Or, on windows, ``git clone --config core.autocrlf=false
-    https://github.com/llvm/llvm-project.git``
-2. Configure and build LLVM and Clang:
-     * ``cd llvm-project``
-     * ``mkdir build``
-     * ``cd build``
-     * ``cmake -G <generator> [options] ../llvm``
-        Some common generators are:
-        * ``Ninja`` --- for generating [Ninja](https://ninja-build.org)
-          build files. Most llvm developers use Ninja.
-        * ``Unix Makefiles`` --- for generating make-compatible parallel makefiles.
-        * ``Visual Studio`` --- for generating Visual Studio projects and
-          solutions.
-        * ``Xcode`` --- for generating Xcode projects.
-        Some Common options:
-        * ``-DLLVM_ENABLE_PROJECTS='...'`` --- semicolon-separated list of the LLVM
-          subprojects you'd like to additionally build. Can include any of: clang,
-          clang-tools-extra, libcxx, libcxxabi, libunwind, lldb, compiler-rt, lld,
-          polly, or debuginfo-tests.
-          For example, to build LLVM, Clang, libcxx, and libcxxabi, use
-          ``-DLLVM_ENABLE_PROJECTS="clang;libcxx;libcxxabi"``.
-        * ``-DCMAKE_INSTALL_PREFIX=directory`` --- Specify for *directory* the full
-          pathname of where you want the LLVM tools and libraries to be installed
-          (default ``/usr/local``).
-        * ``-DCMAKE_BUILD_TYPE=type`` --- Valid options for *type* are Debug,
-          Release, RelWithDebInfo, and MinSizeRel. Default is Debug.
-        * ``-DLLVM_ENABLE_ASSERTIONS=On`` --- Compile with assertion checks enabled
-          (default is Yes for Debug builds, No for all other build types).
-      * Run your build tool of choice!
-        * The default target (i.e. ``ninja`` or ``make``) will build all of LLVM.
-        * The ``check-all`` target (i.e. ``ninja check-all``) will run the
-          regression tests to ensure everything is in working order.
-        * CMake will generate build targets for each tool and library, and most
-          LLVM sub-projects generate their own ``check-<project>`` target.
-        * Running a serial build will be *slow*.  To improve speed, try running a
-          parallel build. That's done by default in Ninja; for ``make``, use
-          ``make -j NNN`` (NNN is the number of parallel jobs, use e.g. number of
-          CPUs you have.)
-      * For more information see [CMake](https://llvm.org/docs/CMake.html)
-Consult the
-[Getting Started with LLVM](https://llvm.org/docs/GettingStarted.html#getting-started-with-llvm)
-page for detailed information on configuring and compiling LLVM. You can visit
-[Directory Layout](https://llvm.org/docs/GettingStarted.html#directory-layout)
-to learn about the layout of the source code tree.
--- a/how_to_compile.txt
+++ b/how_to_compile.txt
-sudo apt install gcc-9-plugin-dev
-if [ $1 == 'debug' ]
-then 
-	cd $2
-	if [ -d "llvm-build-debug" ]
-	then
-		rm -rf llvm-build-debug
-	fi
-	if [ -d "llvm-build-debug-install" ]
-	then
-		rm -rf llvm-build-debug-install
-	fi
-	mkdir llvm-build-debug
-	mkdir llvm-build-debug-install
-	cd llvm-build-debug
-	echo "cmake -DLLVM_ENABLE_RTTI=ON -DCMAKE_EXPORT_COMPILE_COMMANDS=ON -DBUILD_SHARED_LIBS=ON -DCMAKE_BUILD_TYPE=Debug -DLLVM_ENABLE_ASSERTIONS=OFF -DLLVM_USE_SPLIT_DWARF=ON -DLLVM_OPTIMIZED_TABLEGEN=ON -DLLVM_TARGETS_TO_BUILD=host -DLLVM_INCLUDE_EXAMPLES=OFF -DLLVM_INCLUDE_TESTS=OFF -DLLVM_INCLUDE_DOCS=OFF -DCMAKE_CXX_FLAGS=\"-std=c++14 -g\" -DLLVM_ENABLE_PROJECTS=\"clang;polly;compiler-rt;lld\" -DCMAKE_INSTALL_PREFIX=$2/llvm-build-debug-install -DLLVM_BINUTILS_INCDIR=/usr/lib/gcc/x86_64-linux-gnu/9/plugin/include $2/llvm"
-	cmake -DLLVM_INSTALL_UTILS=ON -DLLVM_ENABLE_RTTI=ON -DCMAKE_EXPORT_COMPILE_COMMANDS=ON -DBUILD_SHARED_LIBS=ON -DCMAKE_BUILD_TYPE=Debug -DLLVM_ENABLE_ASSERTIONS=OFF -DLLVM_USE_SPLIT_DWARF=ON -DLLVM_OPTIMIZED_TABLEGEN=ON -DLLVM_TARGETS_TO_BUILD=host -DLLVM_INCLUDE_EXAMPLES=OFF -DLLVM_INCLUDE_TESTS=OFF -DLLVM_INCLUDE_DOCS=OFF -DCMAKE_CXX_FLAGS="-std=c++11 -g" -DLLVM_ENABLE_PROJECTS="clang;polly;compiler-rt;lld" -DCMAKE_INSTALL_PREFIX=$2/llvm-build-debug-install -DLLVM_BINUTILS_INCDIR=/usr/lib/gcc/x86_64-linux-gnu/9/plugin/include $2/llvm
-elif [ $1 == 'release' ]
-then
-	cd $2
-	if [ -d "llvm-build-release" ]
-	then
-		rm -rf llvm-build-release
-	fi
-	if [ -d "llvm-build-release-install" ]
-	then
-		rm -rf llvm-build-release-install
-	fi
-	mkdir llvm-build-release
-	mkdir llvm-build-release-install
-	cd llvm-build-release
-	echo "cmake -DLLVM_ENABLE_RTTI=ON -DCMAKE_EXPORT_COMPILE_COMMANDS=ON -DBUILD_SHARED_LIBS=ON -DCMAKE_BUILD_TYPE=Release -DLLVM_ENABLE_DUMP=ON -DLLVM_ENABLE_ASSERTIONS=OFF -DLLVM_USE_SPLIT_DWARF=ON -DLLVM_OPTIMIZED_TABLEGEN=ON -DLLVM_TARGETS_TO_BUILD=host -DLLVM_INCLUDE_EXAMPLES=OFF -DLLVM_INCLUDE_TESTS=OFF -DLLVM_INCLUDE_DOCS=OFF -DCMAKE_CXX_FLAGS=\"-std=c++14 -O3\" -DLLVM_ENABLE_PROJECTS=\"clang;polly;compiler-rt;lld\" -DCMAKE_INSTALL_PREFIX=$2/llvm-build-release-install -DLLVM_BINUTILS_INCDIR=/usr/lib/gcc/x86_64-linux-gnu/9/plugin/include $2/llvm"
-	cmake -DLLVM_INSTALL_UTILS=ON -DLLVM_ENABLE_RTTI=ON -DCMAKE_EXPORT_COMPILE_COMMANDS=ON -DBUILD_SHARED_LIBS=ON -DCMAKE_BUILD_TYPE=Release -DLLVM_ENABLE_DUMP=ON -DLLVM_ENABLE_ASSERTIONS=OFF -DLLVM_USE_SPLIT_DWARF=ON -DLLVM_OPTIMIZED_TABLEGEN=ON -DLLVM_TARGETS_TO_BUILD=host -DLLVM_INCLUDE_EXAMPLES=OFF -DLLVM_INCLUDE_TESTS=OFF -DLLVM_INCLUDE_DOCS=OFF -DCMAKE_CXX_FLAGS="-std=c++11 -O3" -DLLVM_ENABLE_PROJECTS="clang;polly;compiler-rt;lld" -DCMAKE_INSTALL_PREFIX=$2/llvm-build-release-install -DLLVM_BINUTILS_INCDIR=/usr/lib/gcc/x86_64-linux-gnu/9/plugin/include $2/llvm
-fi
--- a/how_to_use.txt
+++ b/how_to_use.txt
-## 容器创建
-docker run -it unifuzz:2.0 bash
-## 编译源码工程
-**首先在进行以下编译之前，要保证正常情况下是能够编译通过的，也就是工程相关的依赖都已经安装，我们假设工程依赖都已经安装好。**
-我们以vim工程为例，说明下编译流程
- 用AFL编译工程生成用于fuzz的可执行文件（我们称之为fuzz_binary），该编译过程可以参照AFL编译流程，对应的vim编译流程为:
-  - $cd /path/to/vim-afl 进入到vim工程源码目录
-  - $CC=/home/AFL/afl-gcc ./configure
-  - $make -j20
-  - 完成之后我们可以得到AFL插桩后的可执行文件vim，也就是fuzz_binary
- 用llvm编译工程生成用于产生精确覆盖率的可执行文件（我们称之为visual_binary）和用于可视化展示的静态分析json文件（我们称之为visual_json），对应的vim编译流程为:
-  - $cd /path/to/vim-llvm 进入到另外一个vim工程源码目录（一般需要将源码压缩文件解压到两个不同的目录中，一个用于AFL的编译，一个用于llvm的编译）
-  - $CC="/home/llvm-10-visual-mode-1.0/llvm-build-release-install/bin/clang" CFLAGS="-w -flto -g /home/afl-llvm-rt.o.c.o" CXX="/home/llvm-10-visual-mode-1.0/llvm-build-release-install/bin/clang++" CXXFLAGS="-w -flto -g /home/afl-llvm-rt.o.c.o" LDFLAGS="-L/home/llvm-10-visual-mode-1.0/llvm-build-release-install/lib/clang/10.0.0/lib/linux -lclang_rt.builtins-x86_64" RANLIB=/bin/true AR=/home/llvm-10-visual-mode-1.0/llvm-build-release-install/bin/llvm-ar NM=/home/llvm-10-visual-mode-1.0/llvm-build-release-install/bin/llvm-nm ./configure（该构建命令对应的是Makefile构建系统，如果构建系统是cmake，相应的命令为cmake -DCMAKE_C_COMPILER=/home/llvm-10-visual-mode-1.0/llvm-build-release-install/bin/clang -DCMAKE_CXX_COMPILER=/home/llvm-10-visual-mode-1.0/llvm-build-release-install/bin/clang++ -DCMAKE_C_FLAGS="-w -flto -g /home/afl-llvm-rt.o.c.o" -DCMAKE_CXX_FLAGS="-w -flto -g /home/afl-llvm-rt.o.c.o" -DCMAKE_RANLIB=/bin/true -DCMAKE_AR=/home/llvm-10-visual-mode-1.0/llvm-build-release-install/bin/llvm-ar -DCMAKE_NM=/home/llvm-10-visual-mode-1.0/llvm-build-release-install/bin/llvm-nm .）
-  - Makefile构建系统的工程中，有时候上述configure构建命令会在编译时出现xxx.o: file not recognized: file format not recognized导致编译失败，这时可以用CC="/home/llvm-10-visual-mode-1.0/llvm-build-release-install/bin/clang -w -flto -g /home/afl-llvm-rt.o.c.o" CXX="/home/llvm-10-visual-mode-1.0/llvm-build-release-install/bin/clang++ -w -flto -g /home/afl-llvm-rt.o.c.o" LDFLAGS="-L/home/llvm-10-visual-mode-1.0/llvm-build-release-install/lib/clang/10.0.0/lib/linux -lclang_rt.builtins-x86_64" RANLIB=/bin/true AR=/home/llvm-10-visual-mode-1.0/llvm-build-release-install/bin/llvm-ar NM=/home/llvm-10-visual-mode-1.0/llvm-build-release-install/bin/llvm-nm ./configure构建命令来替代原来的构建命令
-  - $make -j20
-  - 完成之后我们可以得到llvm插桩后的可执行文件vim，也就是visual_binary，还有用于可视化展示的静态分析json文件vim-172825.json，其中172825表示该可执行文件中包含的基本块个数
-# 镜像制作
- 用docker cp命令从容器中拷贝fuzz_binary、visual_binary、visual_json三个文件到本地
-  - docker cp container-id:/path/to/fuzz_binary /local/path/dir
-  - docker cp container-id:/path/to/visual_binary /local/path/dir
-  - docker cp container-id:/path/to/visual_json /local/path/dir
- 从容器中删除llvm目录和AFL目录（为了使生成的docker镜像尽可能小）
-  - docker exec -it container-id bash
-  - cd /home && rm -rf llvm-10-visual-mode-1.0 && rm -rf AFL
- export容器到镜像文件
-  - docker export -o image_name.tar container-id
- 用save命令生成镜像文件（原因是目前unifuzz网页系统不支持export命令生成的镜像文件，只支持save命令生成的镜像文件）
-  - docker import image_name.tar REPOSITORY:TAG
-  - docker run -it REPOSITORY:TAG bash（假设生成的容器为container-id2）
-  - docker commit container-id2 REPOSITORY1:TAG1
-  - docker save -o image_name2.tar REPOSITORY1:TAG1
-**最终我们生成一个名字为image_name2.tar的镜像文件**
-# 测试
- 正常的unifuzz测试参照unifuzz使用文档
- 精确覆盖率测试
-  - 首先在程序管理中找到要被测程序，点击修改
-  - 分别上传分析程序（对应于生成的visual_binary）、源代码（对应于源代码的压缩包）、JSON文件（对应于生成的visual_json）
-  - 在任务管理中找到对应的任务，点击启动按钮进行正常fuzz测试，运行一段时间后，点击“暂停”按钮，再点击“分析”按钮开始做精确覆盖率分析，等待分析完成，点击“详情”按钮，在详情页面点击“精确覆盖率”