⚡️ Speed up method Fibonacci.fibonacci by 200,955%

[codeflash-ai]

📄 200,955% (2,009.55x) speedup for Fibonacci.fibonacci in code_to_optimize/java/src/main/java/com/example/Fibonacci.java

⏱️ Runtime : 169 milliseconds → 84.2 microseconds (best of 349 runs)

📝 Explanation and details

Runtime improvement (primary): The optimized version cuts execution time from ~169 ms to ~84.2 µs — a ~200k% speedup — by replacing the exponential recursive routine with an O(log n) iterative algorithm.

What changed (specific optimizations)

• Replaced naive recursion: removed fibonacci(n-1)+fibonacci(n-2) which performs an exponential number of function calls and repeated work.
• Implemented the fast-doubling method iteratively: processes the bits of n (highest to lowest) and computes F(2k) and F(2k+1) via closed-form recurrences in a tight loop.
• Eliminated recursion and allocations: uses two long locals (a, b) and simple arithmetic and bit operations (<<, >>, &), with no extra objects or call-stack growth.
• Minimizes loop iterations by computing the highest set bit once (Integer.numberOfLeadingZeros) and looping only ~log2(n) times.

Why this yields the big speedup

• Algorithmic complexity: original is exponential in n (lots of redundant subcalls); fast-doubling runs in O(log n) arithmetic steps. For moderate/large n (tests use up to n=30 and beyond), that change dominates runtime.
• Removes call overhead and duplicate computation: the profiler shows the original version incurred tens of millions of line hits (huge call/return traffic). The optimized version does only a small constant number of operations per bit of n, so total operations collapse dramatically.
• CPU-friendly operations: arithmetic and bitwise operations are fast and branch-predictable; the loop body has a small fixed amount of work and straightforward branches, which modern JITs optimize well.

Behavioral/compatibility notes (key impacts)

• Correctness preserved for inputs in the same long-typed semantics: negative input still throws; base cases n <= 1 return immediately.
• Stack-safety: recursion is gone — no risk of deep recursion or stack overflow for large n.
• Overflow semantics unchanged: the function still returns long and will overflow in the same way as the original recursive version for very large n (no change in numeric range handling).
• No new dependencies or allocations introduced; the function remains self-contained and lightweight.

Where this matters (workloads/tests)

• Hot paths and repeated calls: any code that repeatedly computes Fibonacci numbers (e.g., per-request, inside loops, or batch processing) will see large throughput and latency wins because per-call cost is tiny.
• Larger n and performance-guarded tests: annotated tests (e.g., n=30, performance/timeouts) show the biggest wins — the optimized version runs orders of magnitude faster and easily satisfies timeouts.
• Small n still fast: base cases are checked early, so there’s no regression for tiny inputs; tests for n=0..10 show microsecond or sub-microsecond times.

Trade-offs and cautions

• No regression in runtime; this change was accepted specifically for runtime improvement.
• Keep the same numeric type expectations: if callers relied on detecting overflow by observing negative/wrapped long results, behavior remains the same so tests remain valid.
• The implementation uses int bit operations to iterate bits of n; since n is an int, the loop bounds are correct and base cases handle n==0/1.

Line-profiler evidence

• Original profiler: huge total time and tens of millions of line hits caused by recursion.
• Optimized profiler: total time collapsed to microseconds and line hits are small and concentrated in the iterative loop lines, matching the expected O(log n) behavior.

Bottom line: this replaces an exponential-time recursive implementation with an iterative fast-doubling algorithm, producing the dramatic runtime improvement shown by the profiler and tests while preserving semantics and removing recursion-related risks.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	✅ 22 Passed
🌀 Generated Regression Tests	🔘 None Found
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

⚙️ Click to see Existing Unit Tests

To edit these changes git checkout codeflash/optimize-Fibonacci.fibonacci-mm335ysu and push.