⚡️ Speed up method Algorithms.fibonacci by 13%

[codeflash-ai]

📄 13% (0.13x) speedup for Algorithms.fibonacci in code_to_optimize/java/src/main/java/com/example/Algorithms.java

⏱️ Runtime : 5.60 milliseconds → 4.97 milliseconds (best of 5 runs)

📝 Explanation and details

The optimized code achieves a 12% runtime improvement (5.60ms → 4.97ms) through three complementary optimizations to the fast doubling Fibonacci algorithm:

1. Simplified bit mask initialization:
Replaced 31 - Integer.numberOfLeadingZeros(n) followed by 1 << highestBit with a direct call to Integer.highestOneBit(n). This eliminates one arithmetic operation and one bit shift per function call, computing the same mask value more efficiently.

2. Streamlined loop structure:

• Removed the unused loop counter i and the redundant highestBit variable
• Changed to unsigned right-shift (>>>=) directly on the mask
• Simplified the loop header from for (int i = highestBit; mask != 0; i--, mask >>= 1) to for (; mask != 0; mask >>>= 1)

This reduces per-iteration overhead by eliminating unnecessary variable updates and using the more efficient unsigned shift operator.

3. Eliminated intermediate variable:
Removed the twoBMinusA temporary variable, computing (twoB - a) inline within the multiplication: a * (twoB - a). This reduces memory pressure and allows the JIT compiler to better optimize the arithmetic sequence, potentially keeping values in registers rather than memory.

Why this improves runtime:
These changes reduce the instruction count in the hot loop that executes O(log n) times. Each iteration now performs fewer operations (no extra variable assignments, no extra loop counter decrement), which compounds across iterations. The JVM's JIT compiler can also better optimize the tighter loop structure, improving instruction pipelining and register allocation. For Fibonacci calculations of large numbers where the loop iterates many times, these micro-optimizations accumulate into measurable performance gains.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	✅ 12 Passed
🌀 Generated Regression Tests	🔘 None Found
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	No coverage data found for fibonacci

⚙️ Click to see Existing Unit Tests

To edit these changes git checkout codeflash/optimize-Algorithms.fibonacci-mlbfivys and push.