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maryamfatima25/pascal-mini-compiler

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App README

Pascal Mini Compiler

A fully integrated compiler for a custom Pascal-like language, featuring a Lexical Analyzer, Semantic Analyzer, Recursive Descent Parser (AST builder), Predictive LL(1) Parser, and a Canonical LR(1) Parser.

The project also includes a rich, web-based UI Dashboard to visualize the pipeline, traces, abstract syntax trees, and error handling.

Requirements

Backend / C++ Compiler

  • —g++ (Compiler with C++17 support)
  • —make (for building the project)
  • —Linux / WSL (Recommended for standard building)

Frontend / Dashboard

  • —python3 (for running the local web server)

1. Building the Compiler

To build the compiler executable, open your terminal (e.g., WSL or Linux shell), navigate to this project folder, and run:

bash
make

This will compile the src/*.cpp files and generate an executable named mini_compiler.

To clean the compiled binaries:

bash
make clean

2. Running the Compiler (Terminal / Command Line)

Once compiled, you can run the compiler against any Pascal source file.

Basic Run:

bash
./mini_compiler test/valid_nested.pascal

Run Multiple Files:

bash
./mini_compiler test/valid_nested.pascal test/duplicate_same_scope.pascal

Run with LR Parser trace enabled: The LR parser trace can be very long. To enable it alongside the default parsers, use the --with-lr flag:

bash
./mini_compiler --with-lr test/valid_nested.pascal

Generate Documentation (Grammar, Tables, etc.):

bash
./mini_compiler --dump-docs

This will generate first_follow.txt, ll1_table.txt, lr_table.txt, and grammar_bnf.txt in the docs/ folder.

3. Running the Dashboard (Web UI)

The project comes with a beautiful web-based interface that allows you to write custom code or load test files, and view the entire compiler pipeline trace, visual AST trees, and semantic symbol table dumps.

To launch the dashboard:

  1. 1.Open a terminal in the project root directory.
  2. 2.Navigate to the ui/ directory:
bash
   cd ui
  1. 1.Run the Python server:
bash
   python3 server.py
  1. 1.Open your web browser and go to: http://localhost:7860

From the dashboard, you can click "Run sample" or write code in the editor and click "Run custom". Explore the Trace, AST Tree, Final Results, and Docs tabs.