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https://github.com/SineStriker/SJTU-2021-Compilers

Reference of SJTU compilers labs
https://github.com/SineStriker/SJTU-2021-Compilers

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Reference of SJTU compilers labs

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README 

        
# Tiger Compiler Labs in C++



## Contents



- [Tiger Compiler Labs in C++](#tiger-compiler-labs-in-c)

  - [Contents](#contents)

  - [Overview](#overview)

  - [Difference Between C Labs and C++ Labs](#difference-between-c-labs-and-c-labs)

  - [Installing Dependencies](#installing-dependencies)

  - [Compiling and Debugging](#compiling-and-debugging)

  - [Testing Your Labs](#testing-your-labs)

  - [Submitting Your Labs](#submitting-your-labs)

  - [Formatting Your Codes](#formatting-your-codes)

  - [Other Commands](#other-commands)

  - [Contributing to Tiger Compiler](#contributing-to-tiger-compiler)

  - [External Documentations](#external-documentations)



## Overview



We rewrote the Tiger Compiler labs using the C++ programming language because some features in C++ like inheritance and polymorphism

are more suitable for these labs and less error-prone.



We provide you all the codes of all labs at one time. In each lab, you only

need to code in some of the directories.



## Difference Between C Labs and C++ Labs



1. Tiger compiler in C++ uses [flexc++](https://fbb-git.gitlab.io/flexcpp/manual/flexc++.html) and [bisonc++](https://fbb-git.gitlab.io/bisoncpp/manual/bisonc++.html) instead of flex and bison because flexc++ and bisonc++ is more flexc++ and bisonc++ are able to generate pure C++ codes instead of C codes wrapped in C++ files.



2. Tiger compiler in C++ uses namespace for modularization and uses inheritance and polymorphism to replace unions used in the old labs.



3. Tiger compiler in C++ uses CMake instead of Makefile to compile and build the target.



## Installing Dependencies



We provide you a Docker image that has already installed all the dependencies. You can compile your codes directly in this Docker image.



1. Install [Docker](https://docs.docker.com/).



2. Run a docker container and mount the lab directory on it.



```bash

# Run this command in the root directory of the project

docker run -it --privileged -p 2222:22 -v $(pwd):/home/stu/tiger-compiler ipadsse302/tigerlabs_env:latest  # or make docker-run

```



## Compiling and Debugging



There are five makeable targets in total, including `test_slp`, `test_lex`, `test_parse`, `test_semant`,  and `tiger-compiler`.



1. Run container environment and attach to it



```bash

# Run container and directly attach to it

docker run -it --privileged -p 2222:22 \

    -v $(pwd):/home/stu/tiger-compiler ipadsse302/tigerlabs_env:latest  # or `make docker-run`

# Or run container in the backend and attach to it later

docker run -dt --privileged -p 2222:22 \

    -v $(pwd):/home/stu/tiger-compiler ipadsse302/tigerlabs_env:latest

docker attach ${YOUR_CONTAINER_ID}

```



2. Build in the container environment



```bash

mkdir build && cd build && cmake .. && make test_xxx  # or `make build`

```



3. Debug using gdb or any IDEs



```bash

gdb test_xxx # e.g. `gdb test_slp`

```



**Note: we will use `-DCMAKE_BUILD_TYPE=Release` to grade your labs, so make

sure your lab passed the released version**



## Testing Your Labs



Use `make`

```bash

make gradelabx

```

or run the script manually

```bash

./scripts/grade.sh [lab1|lab2|lab3|lab4|lab5|lab6|all] # e.g. `./scripts/grade.sh lab1`

```



You can test all the labs by

```bash

make gradeall

```



## Submitting Your Labs



**Run `make register` and input your name in English and student ID.** You can

check it in the `.info` file generated later.



We are using CI in GitLab to grade your labs automatically. **So please make

sure the `Enable shared runners for this project`

under `Your GitLab repo - Settings - CI/CD` is turned on**.



Push your code to your GitLab repo

```bash

git add somefiles

git commit -m "A message"

git push

```



**Wait for a while and check the latest pipeline (`Your GitLab repo - CI/CD -

Pipelines`) passed. Otherwise, you won't get a full score in your lab.**



## Formatting Your Codes



We provide an LLVM-style .clang-format file in the project directory. You can use it to format your code.



Use `clang-format` command

```

find . \( -name "*.h" -o -iname "*.cc" \) | xargs clang-format -i -style=file  # or make format

```



or config the clang-format file in your IDE and use the built-in format feature in it.



## Other Commands



Utility commands can be found in the `Makefile`. They can be directly run by `make xxx` in a Unix shell. Windows users cannot use the `make` command, but the contents of `Makefile` can still be used as a reference for the available commands.



## Contributing to Tiger Compiler



You can post questions, issues, feedback, or even MR proposals through [our main GitLab repository](https://ipads.se.sjtu.edu.cn:2020/compilers-2021/compilers-2021/issues). We are rapidly refactoring the original C tiger compiler implementation into modern C++ style, so any suggestion to make this lab better is welcomed.



## External Documentations



You can read external documentations on our course website:



- [Lab Assignments](https://ipads.se.sjtu.edu.cn/courses/compilers/labs.shtml)

- [Environment Configuration of Tiger Compiler Labs](https://ipads.se.sjtu.edu.cn/courses/compilers/tiger-compiler-environment.html)