⚡️ Speed up function fibonacci by 2,854%#1084
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The optimized code achieves a **2853% speedup** (from 4ms to 135μs) by replacing the exponential-time recursive algorithm with a linear-time iterative approach. **What changed:** - **Eliminated recursion:** The original code uses naive recursion where `fibonacci(n)` calls itself twice (`fibonacci(n-1)` and `fibonacci(n-2)`), creating an exponential tree of duplicate calculations. - **Introduced iterative computation:** The optimized version uses a simple loop with two variables (`prev` and `curr`) to track consecutive Fibonacci numbers, building up to the result. **Why this is faster:** - **Time complexity:** Drops from O(2^n) to O(n). For `fibonacci(35)`, the original makes ~29 million recursive calls, while the optimized version performs just 33 loop iterations. - **No call stack overhead:** Eliminates the cost of creating and destroying function call frames, which is expensive in JavaScript. - **No redundant computation:** Each Fibonacci number is calculated exactly once instead of being recomputed thousands of times across different branches of the recursion tree. **Impact on workloads:** - **Large inputs:** The performance tests show this optimization is critical for inputs like `n=35`, where the original would take seconds (and risk stack overflow at `n=1000`), while the optimized version completes in microseconds. - **Moderate inputs (n=15-25):** Even for smaller values tested, the speedup is substantial and prevents timeouts in CI environments. - **Edge cases preserved:** The optimization maintains identical behavior for base cases (`n ≤ 1`) and supports the same type coercion patterns tested with null and numeric strings. **Test case performance:** The optimized version excels particularly in the "Performance tests" suite, making previously slow or stack-overflow-prone cases (`n=35`, `n=1000`) trivially fast and preventing the deep recursion failures that the original implementation suffered from.
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📄 2,854% (28.54x) speedup for
fibonacciincode_to_optimize_js/fibonacci.js⏱️ Runtime :
4.00 milliseconds→135 microseconds(best of1runs)📝 Explanation and details
The optimized code achieves a 2853% speedup (from 4ms to 135μs) by replacing the exponential-time recursive algorithm with a linear-time iterative approach.
What changed:
fibonacci(n)calls itself twice (fibonacci(n-1)andfibonacci(n-2)), creating an exponential tree of duplicate calculations.prevandcurr) to track consecutive Fibonacci numbers, building up to the result.Why this is faster:
fibonacci(35), the original makes ~29 million recursive calls, while the optimized version performs just 33 loop iterations.Impact on workloads:
n=35, where the original would take seconds (and risk stack overflow atn=1000), while the optimized version completes in microseconds.n ≤ 1) and supports the same type coercion patterns tested with null and numeric strings.Test case performance:
The optimized version excels particularly in the "Performance tests" suite, making previously slow or stack-overflow-prone cases (
n=35,n=1000) trivially fast and preventing the deep recursion failures that the original implementation suffered from.✅ Correctness verification report:
🌀 Click to see Generated Regression Tests
To edit these changes
git checkout codeflash/optimize-fibonacci-mkh4x9anand push.