⚡️ Speed up method BubbleSort.bubbleSort by 60%

[codeflash-ai]

📄 60% (0.60x) speedup for BubbleSort.bubbleSort in code_to_optimize/java/src/main/java/com/example/BubbleSort.java

⏱️ Runtime : 23.4 milliseconds → 14.6 milliseconds (best of 319 runs)

📝 Explanation and details

Runtime improvement (primary): The optimized version reduces end-to-end runtime from ~23.4 ms to ~14.6 ms (≈60% speedup). Line-profiles show total function time falling from 0.1823 s to 0.1346 s.

What changed (specific optimizations):

• Replaced the manual element-by-element copy loop with System.arraycopy(arr, 0, result, 0, arr.length). This moves the copy into a native, highly optimized bulk memory operation.
• Rewrote the bubble sort to the common "last-swap" optimization: on each pass track the index of the last swap (newN) and set the next pass boundary to that index (n = newN). The inner loop is arranged as for (j = 1; j < n; j++) comparing result[j-1] and result[j].
• Switched to a while (n > 1) outer loop that terminates early when the array is already sorted.

Why this speeds things up:

• System.arraycopy is implemented in native code and uses low-level memory copies; it is much faster than a Java-level for loop assigning each element one at a time. The profiler shows the manual copy dominated a (small) portion of the original time; moving it to arraycopy removes that interpreter/bytecode overhead.
• The last-swap optimization reduces the number of inner-loop iterations and comparisons significantly when parts of the array become sorted before the algorithm finishes. The profiler data shows the inner-loop executions drop from ~5,000,422 iterations (original) to ~2,495,789 (optimized) — roughly half — which directly reduces the number of comparisons and swaps executed and therefore CPU time.
• Early termination: instead of always doing n full passes, the algorithm now stops once no swaps occur (n becomes 0), which avoids unnecessary passes on already- or partially-sorted inputs.

Behavioral and correctness notes:

• The optimized version preserves the original behavior (returns a new sorted array in ascending order). It only changes how quickly the algorithm detects sorted tails and copies the input.
• There is no regression in correctness and no other metrics (e.g., memory usage) materially regressed; the only trade-off is a slightly more complex loop structure, which is negligible compared to the runtime benefit.

When this matters (impact on workloads/tests):

• Best impact on partially-sorted or random inputs where sorted suffixes appear early: those cases benefit most because the inner-loop boundary shrinks quickly.
• For worst-case inputs (e.g., reverse-sorted), complexity remains O(n^2), but the reduced overhead from arraycopy and the lower constant factor in the inner loop still yields gains.
• If this function is in a hot path (called frequently), these savings multiply: cutting inner-loop iterations and using native array copy gives consistent per-call improvements that scale with call volume.

Evidence from profilers/tests:

• Wall-clock runtimes: 23.4 ms → 14.6 ms (60% speedup).
• Line profiler: large reduction in total time and roughly halving of inner-loop iterations (5.0M → 2.5M), plus the time previously spent in the Java-level copy loop disappears in favor of a fast native copy.

Summary:
The speedup comes from two concrete, low-risk changes: using System.arraycopy for the input copy (native, faster bulk copy) and applying the standard last-swap bubble sort optimization (reduces unnecessary comparisons/passes and enables early exit). Together they significantly reduce CPU work and wall-clock time while preserving correctness.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 28 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

🌀 Click to see Generated Regression Tests

To edit these changes git checkout codeflash/optimize-BubbleSort.bubbleSort-mm31nv6w and push.