# AC Language - Future Improvements

## ✅ Completed Features

- [x] Cache system with bytecode (.acc files)
- [x] GUI library with widgets
- [x] CLI interface (`ac mycode.ac`)
- [x] Native binary compilation (AC->BNY)
- [x] Multiple backend targets (11 total)
- [x] Assembly generation (AC->ASM)

---

## 🚀 High Priority Improvements

### 1. IR Finalization & Optimization Pipeline

**Goal:** Complete the Intermediate Representation system for optimization and portability

**Current Status:** IR infrastructure exists but not active in production

**Plan:**
```
AC Source → AST → IR → Optimizations → Backend
```

**Benefits:**
- Platform-independent optimizations
- Easier to add new backends
- Better code quality across all targets
- Foundation for advanced features

**Phases:**
1. ✅ Phase 1: Add IRRef typed references (DONE)
2. ⏳ Phase 2: Update IR generator to use typed operands
3. ⏳ Phase 3: Pattern recognition for control flow
4. ⏳ Phase 4: Optimization passes (constant folding, DCE, etc.)

**Time Estimate:** 6-8 hours focused work

---

### 2. Cross-Platform Binary Compilation

**Goal:** Compile AC code to native binaries for multiple architectures

**Current Status:** x86-64 Linux only (AC->BNY)

**Proposed Pipeline:**
```
AC → IR → C → Clang/GCC → Native Binary
```

**Why this approach:**
- Leverage existing C compilers for all platforms
- Clang supports: x86-64, ARM, RISC-V, WASM, NVIDIA PTX
- GCC supports: x86-64, ARM, PowerPC, MIPS, etc.
- Automatic optimization from mature compilers
- Cross-compilation built-in

**Target Platforms:**

#### Tier 1 (High Priority)
- [x] **x86-64 Linux** (current BNY backend)
- [ ] **x86-64 Windows** (PE executable via MinGW/Clang)
- [ ] **x86-64 macOS** (Mach-O via Clang)
- [ ] **ARM64 Linux** (Raspberry Pi, servers)
- [ ] **ARM64 macOS** (Apple Silicon)

#### Tier 2 (Medium Priority)
- [ ] **ARM32 Linux** (embedded systems)
- [ ] **RISC-V** (emerging architecture)
- [ ] **WebAssembly** (browser execution)

#### Tier 3 (Future/Experimental)
- [ ] **NVIDIA PTX** (GPU compute via Clang)
- [ ] **AMD GCN** (GPU compute)
- [ ] **PowerPC** (legacy systems)
- [ ] **MIPS** (embedded systems)

**Implementation Strategy:**

**Option A: IR → C → Clang (RECOMMENDED)**
```cpp
// New backend: AC->CBIN
std::string generateCBin(const ASTNode& ast) {
    // 1. Generate C code
    std::string cCode = generateC(ast);
    
    // 2. Write to temp file
    writeFile("/tmp/ac_temp.c", cCode);
    
    // 3. Compile with Clang for target platform
    std::string target = getTargetTriple(); // e.g., "x86_64-pc-linux-gnu"
    system("clang -O2 -target " + target + " /tmp/ac_temp.c -o output.acb");
    
    // 4. Return binary
    return readBinary("output.acb");
}
```

**Option B: Direct ASM for each architecture**
- Requires implementing codegen_asm_arm.cpp, codegen_asm_riscv.cpp, etc.
- More control but much more work
- Only feasible for x86-64 (already done)

**Option C: LLVM Backend**
- Generate LLVM IR instead of C
- LLVM handles all architectures
- Most flexible but complex to implement
- Best long-term solution

**Recommended Approach:**
1. **Short-term:** Use Option A (IR → C → Clang)
2. **Long-term:** Migrate to Option C (LLVM backend)

---

### 3. GPU Compilation (NVIDIA/AMD)

**Goal:** Compile AC code to run on GPUs for parallel computation

**Current Status:** Not implemented, cannot test (no NVIDIA GPU available)

**Proposed Approach:**

**For NVIDIA (CUDA/PTX):**
```
AC → IR → C/CUDA → nvcc → PTX → GPU Binary
```

**For AMD (ROCm/GCN):**
```
AC → IR → C/HIP → hipcc → GCN → GPU Binary
```

**Alternative (Portable):**
```
AC → IR → C → Clang → PTX/GCN
```

**Use Cases:**
- Parallel array operations
- Matrix multiplication
- Image processing
- Scientific computing
- Machine learning inference

**Example AC Code:**
```ac
AC->GPU

Make vectorAdd func(a, b, n)
    * This would run on GPU *
    FOR i in range(n)
        result[i] = a[i] + b[i]
    return result
```

**Challenges:**
- Memory management (host ↔ device)
- Kernel launch configuration
- Thread synchronization
- No GPU available for testing

**Status:** Future improvement, needs hardware access

---

## 📚 Standard Library Expansion

### Core Libraries Needed

1. **Math Library**
   - Trigonometry (sin, cos, tan)
   - Logarithms (log, ln)
   - Powers and roots (sqrt, pow)
   - Constants (pi, e)

2. **String Library**
   - String manipulation (split, join, replace)
   - Pattern matching (regex)
   - Formatting (sprintf-style)

3. **File I/O Library**
   - Read/write files
   - Directory operations
   - Path manipulation

4. **Network Library**
   - HTTP client/server
   - Sockets (TCP/UDP)
   - WebSocket support

5. **Data Structures Library**
   - Hash maps
   - Sets
   - Queues/Stacks
   - Trees

6. **Audio Library** (like PyAudio)
   - Audio playback
   - Audio recording
   - Audio processing
   - Format conversion

### Library Import System

**Proposed Syntax:**
```ac
* Internal library (ships with AC) *
use ilib math

* External library (user-installed) *
use elib numpy

* Computer library (system-level) *
use clib opengl
```

**Implementation:**
- `ilib` → Bundled with compiler in `library/` folder
- `elib` → User-installed packages (like pip/npm)
- `clib` → System libraries (OpenGL, SDL, etc.)

---

## 🎨 GUI Improvements

### Current Status
- ✅ Basic widget system working
- ✅ Event listeners implemented
- ✅ Key bindings functional

### Needed Improvements

1. **Tkinter-style API**
   ```ac
   use ilib.gui
   
   window = GUI.Window(800, 600)
   button = GUI.Button($Click Me$)
   button.onClick = handleClick
   window.add(button)
   window.show()
   ```

2. **More Widget Types**
   - Text input fields
   - Checkboxes
   - Radio buttons
   - Sliders
   - Dropdown menus
   - Tables/Grids
   - Canvas for drawing

3. **Layout Management**
   - Grid layout
   - Flow layout
   - Absolute positioning
   - Responsive design

---

## 🔧 Compiler Improvements

### Error Messages
- [ ] Better error messages with line numbers
- [ ] Syntax highlighting in errors
- [ ] Suggestions for common mistakes
- [ ] Warning system (unused variables, etc.)

### Debugging Support
- [ ] Generate debug symbols (DWARF)
- [ ] GDB integration
- [ ] Breakpoint support
- [ ] Variable inspection

### Performance
- [ ] Parallel compilation
- [ ] Incremental compilation
- [ ] Link-time optimization (LTO)
- [ ] Profile-guided optimization (PGO)

### Language Features
- [ ] Modules/namespaces
- [ ] Generics/templates
- [ ] Interfaces/traits
- [ ] Pattern matching
- [ ] Async/await
- [ ] Closures/lambdas

---

## 📦 Package Management

### AC Package Manager (acpm)

**Proposed Commands:**
```bash
acpm install numpy        # Install package
acpm search audio         # Search packages
acpm list                 # List installed
acpm update               # Update packages
acpm publish mylib        # Publish package
```

**Package Structure:**
```
mypackage/
├── ac.toml              # Package manifest
├── src/
│   └── mylib.ac         # Source code
├── tests/
│   └── test_mylib.ac    # Tests
└── README.md            # Documentation
```

**ac.toml Example:**
```toml
[package]
name = "mylib"
version = "1.0.0"
authors = ["Your Name"]
license = "MIT"

[dependencies]
math = "2.1.0"
strings = "1.5.0"
```

---

## 🛠️ Backend Installation System

### npm Backend Installer

**Status:** ✅ Implemented

**Features:**
- Automated installation of all backend compilers/interpreters
- Cross-platform support (Linux, macOS, Windows)
- Smart detection of already-installed backends
- Detailed error messages with manual installation instructions

**Usage:**
```bash
# After installing aclang via npm
npx install-backends

# Or from project root
npm run install-backends
```

**Installed Backends:**
- Python 3
- Node.js
- GCC (C/C++)
- Rust
- Go
- Java (OpenJDK 17)
- V

**Installation Script:** `scripts/install-backends.js`

**Features:**
- Platform-specific install commands
- Verification after installation
- Summary report of installed/failed backends
- Fallback to manual installation instructions

**Manual Installation:**
Users can also install backends manually using the commands in README.md

---

## 🌐 Web Platform Support

### WebAssembly Backend
```
AC → IR → WASM → Browser
```

**Benefits:**
- Run AC code in browsers
- Near-native performance
- Portable across platforms
- No installation needed

### Web Framework
```ac
AC->WASM

use ilib.web

app = Web.App()
app.route($/$, handleHome)
app.route($/api/data$, handleAPI)
app.listen(8080)
```

---

## � Language Server Protocol (LSP) Implementation

**Goal:** Create an LSP server for AC that provides IDE features like syntax highlighting, autocomplete, and error detection

**Features:**
- Syntax highlighting (keywords, functions, strings, comments)
- Error detection and diagnostics
- Autocomplete suggestions
- Go to definition
- Find references
- Hover documentation
- Code formatting

**Implementation:**
- Use Python with `pylsp` or `pylsp-server`
- Parse AC syntax and build AST
- Implement LSP protocol methods
- Generate diagnostics for syntax errors

**LSP Methods to Implement:**
- `textDocument/didOpen` - Notify of new document
- `textDocument/didChange` - Notify of changes
- `textDocument/completion` - Autocomplete suggestions
- `textDocument/hover` - Show documentation on hover
- `textDocument/definition` - Go to definition
- `textDocument/references` - Find all references
- `textDocument/diagnostics` - Error/warning reporting

**Client Integration:**
- VS Code: Extension using `vscode-languageclient`
- Kiro: Built-in LSP support
- Vim/Neovim: `coc.nvim` or `lspconfig`
- Emacs: `lsp-mode`

---

## 📦 Package Management

### IR-Level Optimizations
- [ ] Constant folding
- [ ] Dead code elimination
- [ ] Common subexpression elimination
- [ ] Loop unrolling
- [ ] Inlining
- [ ] Tail call optimization

### Backend-Specific Optimizations
- [ ] Register allocation (graph coloring)
- [ ] Instruction scheduling
- [ ] Peephole optimization
- [ ] SIMD vectorization

---

## 🎯 IDE Integration

### Language Server Protocol (LSP)
- [ ] Autocomplete
- [ ] Go to definition
- [ ] Find references
- [ ] Hover documentation
- [ ] Syntax checking
- [ ] Refactoring support

### Editor Plugins
- [ ] VS Code extension
- [ ] Vim/Neovim plugin
- [ ] Emacs mode
- [ ] Sublime Text package

---

## �️ AC REPL (Interactive Shell)

**Goal:** Create a Python-based interactive shell for AC, similar to Python's IDLE

**Features:**
- Interactive prompt for AC code
- Parse and execute AC code line-by-line
- Display results immediately
- Compile to Python backend, run, then clean up (.acc, .lir, .acb files)
- Multi-line input support
- History navigation (arrow keys)
- Clear screen command

**Implementation:**
```python
# ac_repl.py
import subprocess
import tempfile
import os
import readline
import atexit

def clean_temp_files():
    # Remove .acc, .lir, .acb files from current directory
    pass

def run_ac_code(code):
    # Write code to temp file
    # Compile with ac compiler
    # Run generated Python
    # Clean up temp files
    pass

def main():
    print("AC Language REPL - Type 'exit' to quit")
    while True:
        try:
            line = input("ac> ")
            if line.strip() == "exit":
                break
            run_ac_code(line)
        except EOFError:
            break
        except KeyboardInterrupt:
            print("\nUse 'exit' to quit")

if __name__ == "__main__":
    main()
```

**Usage:**
```bash
ac-repl
ac> print($Hello World$)
ac> x = 5
ac> print(x * 2)
```

---

## �📱 Mobile Platform Support

### Android
```
AC → IR → Java/Kotlin → APK
```

### iOS
```
AC → IR → Swift → IPA
```

---

## 🎮 Game Development Support

### Game Engine Integration
- [ ] Unity plugin (via C#)
- [ ] Godot integration (via GDScript)
- [ ] Custom AC game engine

### Graphics Libraries
- [ ] OpenGL bindings
- [ ] Vulkan bindings
- [ ] DirectX bindings (Windows)
- [ ] Metal bindings (macOS/iOS)

---

## 🔐 Security Features

### Memory Safety
- [ ] Bounds checking
- [ ] Null pointer checks
- [ ] Buffer overflow protection
- [ ] Use-after-free detection

### Sandboxing
- [ ] Capability-based security
- [ ] Resource limits
- [ ] Safe foreign function interface

---

## 📊 Profiling & Analysis

### Performance Profiling
- [ ] CPU profiling
- [ ] Memory profiling
- [ ] Call graph generation
- [ ] Hotspot detection

### Static Analysis
- [ ] Type checking
- [ ] Linting
- [ ] Code complexity metrics
- [ ] Security vulnerability scanning

---

## 🌍 Internationalization

### Multi-Language Support
- [ ] Unicode string handling
- [ ] Localization framework
- [ ] Right-to-left text support
- [ ] Date/time formatting

---

## Priority Ranking

### Must Have (Next 6 months)
1. IR finalization and optimization
2. Cross-platform binary compilation (Windows, macOS)
3. Better error messages
4. Standard library expansion (math, strings, file I/O)

### Should Have (6-12 months)
1. Package manager
2. WebAssembly backend
3. IDE integration (LSP)
4. Debugging support

### Nice to Have (12+ months)
1. GPU compilation (NVIDIA/AMD)
2. Mobile platform support
3. LLVM backend
4. Game engine integration

---

## 🎯 Immediate Next Steps

1. **Finalize IR System** (6-8 hours)
   - Complete Phase 2: Update IR generator
   - Add pattern recognition
   - Implement basic optimizations

2. **Cross-Platform Binaries** (4-6 hours)
   - Implement IR → C → Clang pipeline
   - Test on Windows (MinGW)
   - Test on macOS (Clang)

3. **Standard Library** (ongoing)
   - Start with math library
   - Add string utilities
   - Implement file I/O

4. **Documentation** (2-3 hours)
   - API reference
   - Tutorial series
   - Example programs

---

**Total Estimated Time for High Priority Items:** ~20-30 hours

**Status:** Ready to proceed with IR finalization and cross-platform support

