⚡️ Speed up function fibonacci by 26%

[codeflash-ai]

📄 26% (0.26x) speedup for fibonacci in code_to_optimize_js_esm/fibonacci.js

⏱️ Runtime : 134 microseconds → 106 microseconds (best of 5 runs)

📝 Explanation and details

Runtime benefit (primary): the optimized version runs in 106μs vs 134μs for the original — a 26% runtime improvement. This improvement shows up most when the iterative/memoized path is used (the hot path): repeated calls and progressive sequence fills saw the largest gains in the tests (e.g. repeated call ~46.5% faster, progressive samples ~64.5% faster).

What changed

• Cached the module array into a local variable: const arr = _fibArray.
• Kept a local length variable and used local reads (arr[len - 2], arr[len - 1], arr[i]) rather than repeatedly touching the module/global reference.
• Minor loop micro-change: pre-increment (++i) used in the for loop (micro-optimization).

Why this speeds things up

• Fewer global/property lookups: accessing the module-level _fibArray repeatedly requires a property/reference lookup. By aliasing it to a local variable (arr) we replace those lookups with fast local variable accesses, which are much cheaper in JS engines and reduce indexing/property overhead.
• Better JIT/CPU locality: local variables are more likely to be optimized/memoized by the JIT and stay in fast registers/stack slots, producing fewer hidden-shape transitions and less interpreter overhead.
• Reduced indirection in the hot loop: the loop does the minimal work (add two numbers, store result into arr[i], advance local temporaries). That keeps the loop body tight and predictable, which helps the engine generate faster machine code.
• ++i is a trivial micro win for some engines/optimizers (avoids creating a temporary in post-increment), though its contribution is much smaller than the local aliasing.

Behavioral/compatibility notes

• The function’s behavior is unchanged for the iterative path; memoization still persists at module scope.
• There is a tiny regression on one trivial base-case measurement (fibonacci(0) was ~4.4% slower in an isolated timing), which is an acceptable trade-off given the overall runtime and throughput gains across realistic/hot use cases.

When this helps most

• Calls that take the iterative/memoized branch (numeric, integer, n >= existing length) benefit the most — i.e., repeated calls, filling the memo array up to larger n, and bulk computations.
• Recursive fallbacks (non-number or fractional values that trigger recursive calls) are unaffected by this specific micro-optimization.

Summary
The dominant win comes from reducing repeated module/property access by using a local alias for the memo array and tightening the hot loop. That lowers per-iteration overhead, produces better JITted code, and yields the observed ~26% runtime improvement across the measured tests.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	✅ 13 Passed
🌀 Generated Regression Tests	✅ 20 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

⚙️ Click to see Existing Unit Tests

Test File::Test Function	Original ⏱️	Optimized ⏱️	Speedup
fibonacci.test.js::fibonacci returns 0 for n=0	49.2μs	36.3μs	35.3%✅
fibonacci.test.js::fibonacci returns 1 for n=1	2.83μs	1.54μs	83.8%✅
fibonacci.test.js::fibonacci returns 1 for n=2	8.75μs	5.92μs	47.9%✅
fibonacci.test.js::fibonacci returns 233 for n=13	5.00μs	3.46μs	44.6%✅
fibonacci.test.js::fibonacci returns 5 for n=5	7.00μs	4.00μs	75.0%✅
fibonacci.test.js::fibonacci returns 55 for n=10	6.04μs	3.08μs	95.9%✅

🌀 Click to see Generated Regression Tests

// imports
import { fibonacci } from '../fibonacci.js';

// unit tests
describe('fibonacci', () => {
    // Basic Test Cases
    describe('Basic functionality', () => {
        test('should handle normal input (small integers)', () => {
            // Validate fundamental, well-known Fibonacci numbers
            expect(fibonacci(0)).toBe(0);   // F0
            expect(fibonacci(1)).toBe(1);   // F1
            expect(fibonacci(2)).toBe(1);   // F2
            expect(fibonacci(3)).toBe(2);   // F3
            expect(fibonacci(4)).toBe(3);   // F4
            expect(fibonacci(5)).toBe(5);   // F5
            expect(fibonacci(10)).toBe(55); // F10
            expect(fibonacci(20)).toBe(6765); // F20
        });

        test('should be deterministic across repeated calls', () => {
            // Repeated calls should produce identical results (memoized state should not alter correctness)
            const first = fibonacci(15);
            const second = fibonacci(15);
            expect(first).toBe(second);  // 4.33μs -> 2.96μs (46.5% faster)
            // also ensure nearby values are correct (shows state is consistent)
            expect(fibonacci(16)).toBe(987); // F16
        });
    });

    // Edge Test Cases
    describe('Edge cases', () => {
        test('should return the input when n <= 1 (current implementation behaviour)', () => {
            // The implementation returns n directly for any n <= 1 (including non-number values that coerce)
            expect(fibonacci(1)).toBe(1);
            expect(fibonacci(0)).toBe(0);
            expect(fibonacci(0.5)).toBe(0.5); // returns the value itself as it is <= 1
            // null coerces such that null <= 1 is true, so function returns null
            expect(fibonacci(null)).toBeNull();
        });

        test('should handle negative numbers by returning the same negative number (implementation quirk)', () => {
            // For negative n the function's first conditional (n <= 1) returns n directly
            expect(fibonacci(-1)).toBe(-1);
            expect(fibonacci(-10)).toBe(-10);
        });

        test('should accept numeric-like strings via arithmetic coercion', () => {
            // The function falls back to recursive branch when typeof n !== "number".
            // When passed a numeric string, arithmetic (n - 1) coerces to number and the result computes as expected.
            expect(fibonacci('5')).toBe(5);   // '5' -> treated like 5 due to numeric coercion in recursion
            expect(fibonacci('10')).toBe(55); // '10' -> 55
        });

        test('should preserve non-number booleans as returned values for n <= 1', () => {
            // true coerces to 1; since 1 <= 1 the function returns the original value (true)
            expect(fibonacci(true)).toBe(true);
            // false coerces to 0; since 0 <= 1 the function returns the original value (false)
            expect(fibonacci(false)).toBe(false);
        });
    });

    // Large Scale Test Cases
    describe('Performance tests', () => {
        test('should compute a large Fibonacci number correctly for a safe integer (F(78))', () => {
            // F(78) is the largest Fibonacci value that fits within JS integer safe range (2^53-1).
            // Known value: F(78) = 8944394323791464
            expect(fibonacci(78)).toBe(8944394323791464);
        });

        test('should handle large inputs (iteration and memoization path) and return finite positive result', () => {
            // Use a large n that is below iteration limits stated in the prompt (keep iterations < 1000).
            // We choose n = 500 which is large, will be computed by the iterative/memoized path,
            // will be finite (not NaN/Infinity) and should be a positive number.
            const n = 500;
            const result = fibonacci(n);
            expect(typeof result).toBe('number');
            expect(Number.isFinite(result)).toBe(true);
            expect(result).toBeGreaterThan(0);
            // Magnitude check: F(500) is enormous (order of 1e100+). Ensure the result is large.
            expect(result).toBeGreaterThan(1e100);
            // Repeated call should return the same value (memoization must not alter correctness)
            expect(fibonacci(n)).toBe(result);
        });

        test('should compute a sequence of values up to a large n without exceeding reasonable memory counts', () => {
            // This test ensures the function can be used to compute increasing n values in sequence,
            // which relies on the module-level memoization array. We do not access internals;
            // we only confirm correctness of a sampled subsequence.
            const samples = [
                { n: 30, expected: 832040 },     // F30
                { n: 40, expected: 102334155 },  // F40
                { n: 50, expected: 12586269025 } // F50
            ];
            // Compute progressively larger values to simulate growth of memoization structure.
            for (const { n, expected } of samples) {
                expect(fibonacci(n)).toBe(expected);  // 7.54μs -> 4.58μs (64.5% faster)
            }
        });
    });
});

// imports
import { fibonacci } from '../fibonacci.js';

// unit tests
describe('fibonacci', () => {
    // Basic Test Cases
    describe('Basic functionality', () => {
        test('should return 0 for input 0', () => {
            // Base case: zero
            expect(fibonacci(0)).toBe(0);  // 40.8μs -> 42.7μs (4.39% slower)
        });

        test('should return 1 for input 1', () => {
            // Base case: one
            expect(fibonacci(1)).toBe(1);  // 2.54μs -> 1.54μs (64.9% faster)
        });

        test('should compute small fibonacci numbers correctly (n=2, n=10)', () => {
            // Small sequence checks
            expect(fibonacci(2)).toBe(1);   // 0,1,1
            expect(fibonacci(10)).toBe(55); // known value
        });

        test('should compute known medium fibonacci number correctly (n=30)', () => {
            // Medium value exact check to ensure iterative path correctness
            expect(fibonacci(30)).toBe(832040);
        });
    });

    // Edge Test Cases
    describe('Edge cases', () => {
        test('should return the input for negative integers (n <= 1 branch for negatives)', () => {
            // The implementation returns n directly when n <= 1, so negative integers are returned as-is
            expect(fibonacci(-5)).toBe(-5);
            expect(fibonacci(-1)).toBe(-1);
        });

        test('should accept numeric strings (coerced) and compute correctly', () => {
            // Strings that coerce to numbers should produce the numeric fibonacci result
            // '6' -> 8
            expect(fibonacci('6')).toBe(8);
            // Even if passed as a string, subsequent calls with numbers should remain consistent
            expect(fibonacci(6)).toBe(8);
        });

        test('should handle non-integer numeric input via recursive path (example: 2.5 -> 0.5)', () => {
            // The implementation uses recursion for non-integer numbers.
            // fibonacci(2.5) == fibonacci(1.5) + fibonacci(0.5)
            // fibonacci(1.5) == fibonacci(0.5) + fibonacci(-0.5) => 0.5 + (-0.5) == 0
            // fibonacci(2.5) => 0 + 0.5 == 0.5
            expect(fibonacci(2.5)).toBeCloseTo(0.5, 12);
            // Another check: fibonacci(1.5) should equal 0 as reasoned above
            expect(fibonacci(1.5)).toBeCloseTo(0, 12);
        });

        test('should compute a high-but-safe exact fibonacci number (n=78) within IEEE-754 integer range', () => {
            // Up to n=78 the fibonacci numbers are still exact integers within JS Number safe integer range
            // Known value: fib(78) = 8944394323791464
            expect(fibonacci(78)).toBe(8944394323791464);
        });
    });

    // Large Scale Test Cases
    describe('Performance tests', () => {
        test('should handle large inputs efficiently and produce finite results (n=500)', () => {
            // Performance/scale test:
            // - Keep iterations under 1000 (the implementation will iterate up to n internally).
            // - Do not attempt to assert exact integer equality (precision loss past ~n=78).
            // Instead, verify key properties:
            // 1) Result is finite and positive
            // 2) Monotonicity: fib(n) > fib(n-1)
            // 3) Ratio fib(n)/fib(n-1) approximates the golden ratio phi within a reasonable tolerance

            const n = 500;
            const fibN = fibonacci(n);
            const fibNminus1 = fibonacci(n - 1);

            // 1) Finite and positive
            expect(Number.isFinite(fibN)).toBe(true);
            expect(fibN).toBeGreaterThan(0);

            // 2) Monotonicity
            expect(fibN).toBeGreaterThan(fibNminus1);

            // 3) Ratio approximates golden ratio
            const phi = (1 + Math.sqrt(5)) / 2;
            const ratio = fibN / fibNminus1;
            // Use a tolerant epsilon because of floating point rounding for large fibonacci numbers
            expect(ratio).toBeCloseTo(phi, 10); // 10 decimal places tolerance
        });
    });
});

To edit these changes git checkout codeflash/optimize-fibonacci-mkxeijq3 and push.