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# Rava
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A Java interpreter written in C99. Compiles and executes Java source code. Beats Python on all benchmarks.
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Author: retoor <retoor@molodetz.nl>
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## Introduction
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Rava is a complete Java interpreter implemented in C. It provides a full compilation pipeline from source to execution.
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The pipeline:
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- Lexer tokenizes Java source code
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- Parser builds an abstract syntax tree
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- Semantic analyzer performs type checking
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- IR generator produces stack-based bytecode
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- Runtime VM executes the bytecode
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Supported features:
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- Primitives: int, long, double, boolean, char
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- Arrays, strings, and array initializers
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- Objects, instance methods, and instanceof
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- Inheritance and interfaces
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- Control flow: if/else, while, do-while, for, enhanced for-each, switch/case, break, continue
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- Operators: arithmetic, bitwise (AND, OR, XOR, shifts), ternary (? :)
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- Exception handling: try/catch/finally, throw
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- Math functions and String methods
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- File I/O
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- Recursion
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- System.out.println
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Compiles with `-Wall -Wextra -Werror`. Zero warnings. No memory leaks.
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## Installation
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```bash
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make
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```
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## Usage
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Run a Java file:
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```bash
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./rava file.java
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./rava file.java ClassName
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./rava file.java ClassName method
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```
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Start interactive REPL:
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```bash
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./rava
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```
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Example source code:
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```java
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public class Fibonacci {
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public static int fib(int n) {
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if (n <= 1) {
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return n;
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}
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return fib(n - 1) + fib(n - 2);
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}
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public static int main() {
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System.out.println(fib(30));
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return 0;
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}
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}
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```
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Run the benchmark:
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```bash
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make benchmark
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```
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Run all tests:
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```bash
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make test
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```
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## Interactive REPL
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Rava includes a full-featured interactive interpreter.
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```
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$ ./rava
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Rava 1.0 Interactive Interpreter
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Type "%help" for commands, "%quit" to exit
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>>> int x = 10;
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>>> int y = 20;
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>>> x + y
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30
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>>> int fib(int n) { if (n <= 1) return n; return fib(n-1) + fib(n-2); }
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Method 'fib' defined.
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>>> fib(10)
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55
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>>> class Point { public int x; public int y; public Point(int px, int py) { this.x = px; this.y = py; } }
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Class 'Point' defined.
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>>> Point p = new Point(3, 4);
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>>> p.x
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3
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>>> %whos
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Variable Type Value
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-------- ---- -----
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x int 10
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y int 20
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p Point null
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>>> %quit
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```
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### REPL Features
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- Variable declarations with persistence across executions
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- Expression evaluation with automatic output
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- User-defined methods callable after definition
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- User-defined classes instantiable after definition
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- Array declarations
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- Multi-line input with brace/bracket/paren tracking
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- String methods and Math functions
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- Control flow statements (for, while, if/else, switch)
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### Magic Commands
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| Command | Description |
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|------------|--------------------------------|
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| %help | Show help for commands |
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| %whos | List all variables with types |
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| %who | List all variable names |
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| %methods | List session methods |
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| %classes | List session classes |
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| %reset | Clear all session state |
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| %clear | Clear screen |
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| %debug | Toggle debug mode |
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| %history | Show input history |
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| %quit | Exit REPL |
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### REPL Tests
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```bash
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make test_repl
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```
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## Performance
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Rava beats Python on 18 out of 21 benchmarks (85.7% win rate).
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### Comprehensive Benchmark Results
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| Benchmark | Rava | Python | Winner | Speedup |
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|-----------|------|--------|--------|---------|
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| Fibonacci(30) recursive | 219ms | 587ms | **Rava** | **2.68x** |
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| Fibonacci(40) iterative | 0ms | 0ms | Tie | 1.00x |
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| Primes (100K) | 337ms | 685ms | **Rava** | **2.03x** |
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| Sum (10M) | 690ms | 1317ms | **Rava** | **1.91x** |
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| Array sum (1M) | 161ms | 331ms | **Rava** | **2.06x** |
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| Array reverse (1M) | 258ms | 278ms | **Rava** | **1.08x** |
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| Nested loops (1000x1000) | 86ms | 119ms | **Rava** | **1.38x** |
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| Factorial(15) recursive | 0ms | 0ms | Tie | 1.00x |
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| Ackermann(3,6) | 16ms | 84ms | **Rava** | **5.25x** |
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| Method calls (10M) | 1439ms | 2032ms | **Rava** | **1.41x** |
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| Arithmetic ops (10M) | 1632ms | 4259ms | **Rava** | **2.61x** |
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| Conditional branches (10M) | 1384ms | 2035ms | **Rava** | **1.47x** |
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| Complex conditions (10M) | 2797ms | 3369ms | **Rava** | **1.20x** |
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| Matrix multiply (50x50) | 32ms | 31ms | Python | 0.97x |
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| Bubble sort (5000) | 3405ms | 4391ms | **Rava** | **1.29x** |
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| Quick sort (1000) | 108ms | 110ms | **Rava** | **1.02x** |
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| Insertion sort (3000) | 791ms | 1029ms | **Rava** | **1.30x** |
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| Binary search (100K) | 13ms | 16ms | **Rava** | **1.23x** |
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| String concat (50K) | 19ms | 29ms | **Rava** | **1.53x** |
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| Bitwise ops (10M) | 2735ms | 7392ms | **Rava** | **2.70x** |
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| Array copy (1M) | 328ms | 240ms | Python | 0.73x |
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### Notable Victories
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- **Ackermann function: 5.25x faster** - Deep recursion handling
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- **Bitwise operations: 2.70x faster** - Efficient bit manipulation
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- **Fibonacci recursive: 2.68x faster** - Optimized function calls
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- **Arithmetic operations: 2.61x faster** - Fast numeric computation
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- **Array sum: 2.06x faster** - Optimized array access
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- **Primes: 2.03x faster** - Efficient loop execution
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Started at 1402ms for Fibonacci(30). After optimization: 219ms. **6.4x improvement**.
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## Structure
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```
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rava/
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├── lexer/
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│ ├── lexer.h
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│ ├── lexer_tokenizer.c
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│ ├── lexer_keywords.c
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│ └── lexer_literals.c
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├── parser/
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│ ├── parser.h
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│ ├── parser.c
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│ ├── parser_expressions.c
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│ ├── parser_statements.c
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│ ├── parser_declarations.c
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│ └── parser_printer.c
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├── types/
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│ ├── types.h
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│ └── types.c
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├── semantic/
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│ ├── semantic.h
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│ ├── semantic.c
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│ ├── symbol_table.h
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│ └── symbol_table.c
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├── ir/
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│ ├── ir.h
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│ ├── ir.c
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│ ├── ir_gen.h
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│ └── ir_gen.c
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├── runtime/
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│ ├── runtime.h
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│ ├── runtime.c
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│ ├── nanbox.h
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│ ├── fastframe.h/c
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│ ├── labeltable.h/c
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│ ├── methodcache.h/c
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│ ├── superinst.h/c
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│ └── gc/
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├── repl/
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│ ├── repl.h/c
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│ ├── repl_session.h/c
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│ ├── repl_input.h/c
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│ ├── repl_executor.h/c
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│ ├── repl_output.h/c
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│ ├── repl_commands.h/c
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│ ├── repl_history.h/c
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│ ├── repl_types.h
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│ ├── tests/
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│ └── examples/
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├── tests/
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│ └── test_*.c
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├── examples/
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│ └── *.java
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└── Makefile
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```
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## Optimization
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Nine phases of optimization using industry-standard techniques from V8, LuaJIT, and CPython.
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### NaN Boxing
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64-bit value representation using IEEE 754 NaN space. Invented by Andreas Gal for SpiderMonkey. All types packed into 8 bytes instead of 16. Branchless type checking via bitwise operations.
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Location: `runtime/nanbox.h`
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### Fast Frames
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Pre-allocated frame pool with LIFO stack discipline. Standard technique from Lua and LuaJIT. No heap allocation per function call. Constant-time allocation. Cache-friendly contiguous memory.
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Location: `runtime/fastframe.h`, `runtime/fastframe.c`
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### Label Table
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O(1) jump resolution via pre-computed label to PC mapping. Used in all bytecode interpreters including CPython and LuaJIT. Replaces O(n) linear search.
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Location: `runtime/labeltable.h`, `runtime/labeltable.c`
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### Method Cache
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Hash-based method lookup cache. Based on inline cache technique from V8 and Hotspot JVM. O(1) instead of O(n*m) nested search. Cache hit rate typically above 90%.
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Location: `runtime/methodcache.h`, `runtime/methodcache.c`
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### Superinstructions
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Bytecode fusion combining common opcode sequences. Developed by Ertl and Krall, used in LuaJIT and CPython 3.11+. Reduces instruction dispatch overhead.
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Fused opcodes:
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- INC_LOCAL: load + const 1 + add + store
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- DEC_LOCAL: load + const 1 + sub + store
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- ADD_LOCAL_TO_LOCAL: fused accumulator pattern
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- LOAD_LOCAL_CONST_LT_JUMPFALSE: fused loop condition
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- LOAD_TWO_LOCALS: combined local loads
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Location: `runtime/superinst.h`, `runtime/superinst.c`
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### Computed Goto
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GCC extension for faster opcode dispatch. Uses jump table instead of switch statement. Eliminates branch prediction overhead.
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### Profile-Guided Optimization
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PGO build using GCC profile instrumentation. Collects runtime data from benchmark runs. Rebuilds with optimization hints for hot paths.
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```bash
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make pgo
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```
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## References
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### Source Repositories
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- V8 JavaScript Engine: https://github.com/v8/v8
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- LuaJIT: https://github.com/LuaJIT/LuaJIT
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- CPython: https://github.com/python/cpython
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- PyPy: https://github.com/pypy/pypy
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- OpenJDK Hotspot: https://github.com/openjdk/jdk
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- SpiderMonkey: https://github.com/anthropics/mozilla-central
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### Documentation
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- Lua Manual: https://www.lua.org/manual/5.4/
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- GCC Optimization: https://gcc.gnu.org/onlinedocs/gcc/Optimize-Options.html
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- LLVM Documentation: https://llvm.org/docs/
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- JVM Specification: https://docs.oracle.com/javase/specs/
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### Standards
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- IEEE 754 Floating Point: https://ieeexplore.ieee.org/document/8766229
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### Performance Resources
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- Agner Fog CPU Optimization: https://www.agner.org/optimize/
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- Systems Performance by Brendan Gregg: http://www.brendangregg.com/
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