⚡️ Speed up function fibonacci by 217,795%#1089
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The optimized code achieves a **2,177x speedup** (from 60.5 ms to 27.8 μs) by replacing the exponential-time recursive algorithm with two optimized paths: ## Key Optimizations **1. Integer Fast Path (O(n) iterative)** - For integer inputs, uses a simple iterative loop instead of recursion - Maintains only two variables (`a`, `b`) rather than exponentially many stack frames - The original recursive implementation has O(2^n) time complexity due to redundant recalculations—for example, `fibonacci(30)` makes over 2.6 million function calls - The iterative version makes exactly `n-1` iterations with constant memory **2. Memoized Recursion for Non-Integers** - For fractional/non-integer inputs (e.g., `fibonacci(1.5)`), preserves the original recursive semantics but caches intermediate results in a `Map` - Prevents redundant recalculations while maintaining correct behavior for edge cases like fractional values **3. V8 Engine Optimization Hint** - Caches loop boundary (`len = n`) to help the JavaScript engine optimize the loop iteration ## Why This Matters The test results show this optimization excels across all categories: - **Basic functionality tests** (fibonacci(0) through fibonacci(10)) now execute near-instantaneously - **Performance tests** with larger inputs (n=15, 20, 25, 30) that would timeout or take seconds with the naive implementation now complete in microseconds - **Batch operations** (computing fibonacci(0..30) in a loop) benefit enormously since each call is O(n) instead of O(2^n) The massive speedup is because the original algorithm's exponential growth becomes catastrophic even for moderate values—fibonacci(30) has ~2^30 recursive calls vs. 30 iterations. All test cases pass because the mathematical results remain identical; only the computation strategy changed.
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📄 217,795% (2,177.95x) speedup for
fibonacciincode_to_optimize_js/fibonacci.js⏱️ Runtime :
60.5 milliseconds→27.8 microseconds(best of250runs)📝 Explanation and details
The optimized code achieves a 2,177x speedup (from 60.5 ms to 27.8 μs) by replacing the exponential-time recursive algorithm with two optimized paths:
Key Optimizations
1. Integer Fast Path (O(n) iterative)
a,b) rather than exponentially many stack framesfibonacci(30)makes over 2.6 million function callsn-1iterations with constant memory2. Memoized Recursion for Non-Integers
fibonacci(1.5)), preserves the original recursive semantics but caches intermediate results in aMap3. V8 Engine Optimization Hint
len = n) to help the JavaScript engine optimize the loop iterationWhy This Matters
The test results show this optimization excels across all categories:
The massive speedup is because the original algorithm's exponential growth becomes catastrophic even for moderate values—fibonacci(30) has ~2^30 recursive calls vs. 30 iterations. All test cases pass because the mathematical results remain identical; only the computation strategy changed.
✅ Correctness verification report:
🌀 Click to see Generated Regression Tests
To edit these changes
git checkout codeflash/optimize-fibonacci-mkhavbpuand push.