Linux Kernel Module Generation Using an F# DSL

Overview

This project explores an interesting systems-programming idea:

Instead of writing Linux kernel modules directly in C, we use a small F#-based Domain Specific Language (DSL) to generate kernel C code automatically.

The generated C source is then compiled into a Linux kernel module (.ko) and loaded into the kernel for execution.

The project serves as a learning exercise in:

• Linux kernel programming
• Memory management (kmalloc, kfree)
• DSL design
• Intermediate Representations (IR)
• Compiler construction
• Code generation
• Systems architecture

---

Project Architecture

The current implementation follows a compile-time code generation model.

F# DSL (IR)
      ↓
kernel_ir.fsx
      ↓
Generate C Source
      ↓
kmalloc_demo.c
      ↓
Kernel Build System
      ↓
kmalloc_demo.ko
      ↓
Linux Kernel

The F# script acts as a tiny compiler.

The Linux kernel module is generated output.

There is no runtime dependency between F# and the kernel module.

---

Why Build a DSL?

A DSL allows us to describe system behavior declaratively instead of manually writing repetitive kernel C code.

Benefits:

• Faster experimentation
• Repeatable code generation
• Cleaner abstractions
• Foundation for future compiler work
• Easier verification and optimization

Example philosophy:

Instead of writing:

ptr = kmalloc(128, GFP_KERNEL);

we eventually want to describe:

allocate buffer size 128

and let the compiler generate the kernel code.

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Two Types of DSLs

1. Compile-Time DSL (Recommended)

This is the model used by the Linux kernel itself.

Examples:

Macros

#define MAX_SIZE 1024

X-Macros

#define DEVICE_LIST \
    X(dev1)         \
    X(dev2)

Header-Based DSL

DECLARE_DRIVER(net_driver)

Advantages:

• Zero runtime cost
• Hot-path safe
• Compiler optimized
• Production friendly

---

2. Runtime DSL

Runtime DSLs parse instructions while the program is running.

Example:

ALLOCATE 128
FREE buffer

Advantages:

• Flexible
• Dynamic

Disadvantages:

• Parsing overhead
• Additional complexity
• Not suitable for performance-critical kernel paths

---

Hot Path Safety

For kernel development, avoiding runtime overhead is critical.

Technique	Hot Path Safe
Macros	Yes
Inline Functions	Yes
Static Structures	Yes
Runtime Parsing	No
String DSL	No

Compile-time expansion is generally preferred inside kernels.

---

Current State of the Project

The current implementation uses a simple string-based generator.

kernel_ir.fsx
       ↓
Generate text
       ↓
kmalloc_demo.c

This works well for learning but does not yet provide compiler-like guarantees.

---

Future Compiler Architecture

A more complete compiler pipeline would look like:

Frontend DSL
       ↓
Parser
       ↓
AST
       ↓
Semantic Analyzer
       ↓
Kernel IR
       ↓
Verification Passes
       ↓
Optimization Passes
       ↓
Backend Code Generator
       ↓
Linux Kernel C Module

---

Compiler Components

Parser

Converts DSL text into structured syntax.

Example:

allocate 128

becomes:

AllocateNode(128)

---

AST (Abstract Syntax Tree)

Represents the structure of the DSL program.

Example:

Program
 └── AllocateNode
      └── 128

---

Semantic Analyzer

Validates program correctness.

Examples:

• Invalid sizes
• Undefined symbols
• Type mismatches

---

Kernel IR

The IR (Intermediate Representation) acts as a stable internal model.

Example:

AllocateBuffer
Size = 128
Flags = GFP_KERNEL

The backend generates C from the IR rather than directly from the parser.

---

Verification Passes

Verification ensures generated kernel code follows rules.

Potential checks:

• Allocation size validation
• Resource ownership validation
• Missing cleanup detection
• Locking correctness
• Memory leak detection

---

Optimization Passes

Potential future optimizations:

• Dead allocation removal
• Constant folding
• IR simplification
• Resource lifetime optimization

---

Architectural Approaches

Approach 1: DSL-Driven Compiler

F# DSL
    ↓
IR
    ↓
C Code Generator
    ↓
Kernel Module

Characteristics:

• F# acts as a compiler
• No runtime coupling
• Generated C is final output

Best for:

• Fast iteration
• DSL experimentation
• Compiler learning

---

Approach 2: Control Plane / Data Plane

F# Control Plane
        ↓
Configuration
        ↓
C Data Plane

Characteristics:

• F# makes decisions
• C executes them
• Communication happens at runtime

Examples:

• Kubernetes
• SDN Controllers
• Distributed systems

Best for:

• Systems architecture
• Policy separation
• Runtime control

---

Approach 3: Pure C

Kernel C Code
       ↓
Kernel Module

Characteristics:

• No abstraction layers
• Direct kernel API usage

Best for:

• Kernel mastery
• Driver development
• Networking internals

---

Choosing the Right Approach

Fast Iteration

Use:

DSL → IR → C Generation

Benefits:

• Rapid experimentation
• Easier refactoring
• Compiler-driven development

---

Deep Kernel Learning

Use:

Pure C

Benefits:

• Understand actual kernel behavior
• Learn memory management
• Learn synchronization primitives

---

Compiler and DSL Learning

Use:

AST → IR → Verification → Codegen

Benefits:

• Learn compiler architecture
• Learn language design
• Learn optimization techniques

---

Build and Execute

Generate C Source

dotnet fsi kernel_ir.fsx

---

Build Kernel Module

make

---

Sign Module

Required when Secure Boot is enabled.

sudo /usr/src/linux-headers-$(uname -r)/scripts/sign-file \
sha256 \
~/kernel_keys/MOK.key \
~/kernel_keys/MOK.crt \
kmalloc_demo.ko

---

Load Module

sudo insmod kmalloc_demo.ko

---

View Kernel Logs

dmesg | tail

---

Unload Module

sudo rmmod kmalloc_demo

---

Learning Outcomes

By completing this project you gain exposure to:

• Linux kernel modules
• Memory allocation internals
• kmalloc and kfree
• DSL design
• AST construction
• Intermediate representations
• Verification pipelines
• Code generation
• Compiler architecture
• Systems design patterns
• Control plane vs data plane concepts

---

Final Thought

There is no single "best" architecture.

Choose the abstraction level that matches your goal:

• Speed of development → DSL and code generation
• Deep systems knowledge → Pure C
• Compiler and architecture skills → AST, IR, verification, and code generation

In real-world systems, all three approaches often coexist.