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The recursive implementation was replaced with an iterative fast-doubling algorithm that computes Fibonacci(n) in O(log n) time by processing the bits of n and applying matrix-exponentiation doubling formulas (F(2k) = F(k)*(2*F(k+1) - F(k)) and F(2k+1) = F(k+1)² + F(k)²), eliminating the exponential O(2^n) recursive call tree that dominated original runtime at 32.5% per the profiler. This cuts execution time from 3.81 ms to 179 µs (20× speedup) by avoiding redundant subproblem recomputation and deep call stacks. The optimization incurs no regressions in correctness, maintains identical exception behavior, and scales to larger n values that would timeout under naive recursion.
The optimization replaced the naive recursive `fibonacci(i)` call inside the loop (which recomputed overlapping subproblems exponentially) with an iterative approach that builds the sequence in a single forward pass, reusing `result[i-1]` and `result[i-2]`. The original profiler shows `result[i] = fibonacci(i)` consumed 94% of runtime at ~37 µs per call due to exponential tree traversal; the optimized version computes each element in constant time by direct addition. Runtime improved 27% (230 µs → 181 µs) with no correctness regressions across all test cases.
…ci.fibonacciSequence-mnqqzpp4 ⚡️ Speed up method `Fibonacci.fibonacciSequence` by 27%
…ci.fibonacci-mnqq81k5 ⚡️ Speed up method `Fibonacci.fibonacci` by 2,036%
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