#7 Foundation and Architecture: Language Implementation Project Structure -> Project Structure for a Programming Language Interpreter.

github : https://github.com/ForgeLang/LearnSeries

Designing a modern interpreter for a new programming language requires a well-thought-out and scalable project structure from the outset. A clean architecture not only enables faster iteration during development but also improves maintainability, testing, extensibility, and onboarding for contributors. With the capabilities introduced in C++20 and C++23, we can now structure our interpreter using powerful modern features such as modules, concepts, constexpr evaluation, and std::variant-based ASTs, avoiding legacy pitfalls like monolithic headers, excessive preprocessor usage, and rigid class hierarchies.

This section provides a focused exploration of a professional, modular project structure for implementing our language interpreter in modern C++, targeting clarity, correctness, and long-term sustainability.

1. Overview: Goals of a Good Project Structure

The primary goals behind a good interpreter project structure are:

• Separation of concerns between lexing, parsing, semantic analysis, runtime, and user interface

• Incremental compilation and improved build times using C++20 modules

• Extensibility to allow future components like a bytecode VM or JIT

• Testability at every level: lexer, parser, type checker, evaluator

• Toolchain compatibility, ensuring clean builds across platforms

Each part of the interpreter pipeline must be represented as an isolated subsystem communicating through well-defined interfaces and type-safe structures.

2. High-Level Project Layout

A recommended directory and module structure for our interpreter:

x
/ForgeLang
│
├── /src
│   ├── /core          → Core utilities, error system, memory abstractions
│   ├── /lexer         → Tokenization and source preprocessing
│   ├── /parser        → AST construction and syntax grammar
│   ├── /semantics     → Type checking and static validation
│   ├── /runtime       → Execution engine and built-in standard library
│   ├── /stdlib        → Language-defined standard functions (print, math)
│   ├── /vm            → (optional) Future bytecode or stack machine backend
│   └── /main          → CLI, REPL, and entry point
│
├── /include           → Public headers (if needed by tooling)
├── /tests             → Unit and integration tests for each subsystem
├── /examples          → Example programs written in our new language
├── /docs              → Auto-generated and written documentation
└── /build             → Out-of-source CMake build folder

This directory layout supports modular builds, isolated testing, and gradual expansion without cross-component contamination.

3. Core Interpreter Modules and Responsibilities

Each subdirectory represents a self-contained C++ module or namespace. Below is a breakdown of each major component:

a. /core — Foundation Utilities

Contains:

• SourceManager: manages file loading, line/column mapping

• ErrorReporter: structured diagnostics with error codes and hints

• ArenaAllocator: optional custom allocator for AST and runtime

• Utility types: string views, IDs, file paths, hash maps

C++ Features:

• std::string_view, std::expected, std::source_location (C++20/23)

• Custom diagnostic formatting via std::format

b. /lexer — Lexical Analyzer

Contains:

• TokenType: enum class defining all tokens

• Token: structure with type, value, span

• Lexer: class/function that scans source and emits tokens

Design:

• Use std::variant for token value storage (e.g., string, int, float)

• Return std::vector<Token> or token stream iterator

• Support comments, whitespace control, and source span tracking

C++ Features:

• Ranges and iterators

• Unicode support via char8_t and std::u8string_view if required

c. /parser — Abstract Syntax Tree Construction

Contains:

• AST Nodes: Expr, Stmt, Decl, etc. implemented via std::variant

• Parser class: consumes tokens and produces typed AST nodes

• Grammar implementation using recursive descent

Design:

• Each AST node as a struct with a unique tag

• Use std::visit to process or transform AST nodes

• Error recovery strategies for invalid syntax

C++ Features:

• std::variant, std::optional, and pattern matching (C++23)

• concepts to constrain node processing

d. /semantics — Type Checking and Analysis

Contains:

• Symbol table, scopes, and identifier resolution

• Static type checker and trait verifier

• Compile-time evaluation of const fn

Design:

• Use std::map or custom hash maps for scope chaining

• Rich error types returned via std::expected

• Trait system modeled with concepts or structural typing rules

C++ Features:

• constexpr and consteval for internal simulation

• Strong typing with enum class and tagged unions

e. /runtime — Evaluation Engine

Contains:

• Evaluator or Interpreter class that runs AST nodes

• Built-in runtime functions (print, input, arithmetic)

• Memory stack and function call frames

Design:

• Separate call stack and value stack

• Environment model for scoped variable binding

• Optional tail-call optimization

C++ Features:

• Thread-local storage, lambdas for closures

• Coroutines or continuations if advanced control flow is desired

f. /stdlib — Standard Library Functions

Contains:

• Native functions implemented in C++ and exposed to the interpreter

• Standard math, string, and I/O functions

• Ability to register external functions to the language

Design:

• Internal registry of functions keyed by name or ID

• C++ functions mapped to native call interface

4. Build System and Tooling

The project uses CMake with full C++20/23 support:

• Each module has its own CMakeLists.txt

• Compile flags enforce modern standards: -std=c++23, -Wall, -Wextra, -Werror

• Modular build using add_library(MODULE_NAME MODULE) and target_link_libraries

• Optional Clang modules support for dependency isolation

• Precompiled headers for faster build in larger projects

5. Modern Development Practices

Version Control: Git repository with submodules (for third-party or future bytecode engine)

Testing:

• Unit tests for lexer, parser, and evaluator using Catch2 or doctest

• Integration tests using language snippets in /examples

• Static analysis using Clang-Tidy and -fsanitize=address

CI/CD:

• GitHub Actions or similar pipeline to validate builds on Linux, Windows, macOS

• Separate jobs for unit tests, style checks, and benchmarks

6. Advantages of Using Modern C++20/23

• Modules allow fast and scalable builds without excessive includes

• Concepts ensure that interpreter components (e.g., visitors, type checkers) are valid at compile time

• std::variant and std::visit enable safe and expressive AST traversal

• consteval/constexpr allow building parts of the interpreter that validate or simulate code at compile-time

• Thread-safe execution and std::jthread for future concurrency in the interpreter

• Pattern matching (C++23) simplifies AST and token processing

Conclusion

This initial structure is designed to support the full life cycle of a modern language interpreter, from early experimentation to production-grade tools. Built on modern C++ standards, it promotes readability, modularity, type safety, and performance. Each module is intentionally decoupled, allowing independent testing and iteration.

By establishing a scalable and maintainable structure now, we ensure that future chapters—on parsing, execution, error handling, and concurrency—are built on solid, modern foundations. This architecture reflects a 2020s-era mindset of system programming: precise, modular, and maintainable—without sacrificing performance or expressiveness.