Benchmark: Factorial math - MeasureThat.net

Tests:

Recursive
function pangkatRec(x, y) { if (y < 0) { return 0 } else if (y == 0) { return 1 } else { return x * pangkatRec(x, y - 1) } } pangkatRec(2, 3)
While loop
function pangkatImperatives(x, y) { if (y < 0) { return 0; } else if (y === 0) { return 1; } else { let result = 1; while (y > 0) { result *= x; y--; } return result; } } pangkatImperatives(2, 3)
While loop (other)
function pangkatImperatives(x, y) { let n = y + 1; // n+1 let result = 0; while (n--) { if (result < 0) { result = 0 } else if (result == 0){ result = 1 } else { result *= x; } } return result } pangkatImperatives(2, 3)

Historical Performance Data aggregated from 5 community runs

Desktop Results:

Chrome 5 runs

While loop

35.4M/s

Recursive

13.9M/s

pHqghUme

1/s

Fastest: While loop (35435228.0x faster)

View exact numbers

✓ While loop: 35,435,228 ops/sec
• Recursive: 13,857,189 ops/sec
• pHqghUme: 1 ops/sec

Results show median performance across all community submissions. Run this benchmark yourself to verify on your device.

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Recursive
While loop
While loop (other)

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 2 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/121.0.0.0 Safari/537.36

Browser/OS: Chrome 121 on Windows

View result in a separate tab

pHqghUme

1/s

pHqghUme

1/s

pHqghUme

1/s

View exact numbers

Test name	Executions per second
✓ pHqghUme	1 Ops/sec
✓ pHqghUme	1 Ops/sec
✓ pHqghUme	1 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

LLMs can make mistakes. Check important info.

I'll break down the provided benchmark and explain what's being tested, compared, and its implications.

**Benchmark Definition**

The benchmark definition consists of a single test case, which is a mathematical function `pangkatRec` or one of its variants (`pangkatImperatives`). The function calculates the power of a number using recursion or loops. There are three versions:

1. Recursive version (`pangkatRec`)
2. Imperative version with a while loop (`pangkatImperatives (first variant)`)
3. Imperative version with another while loop structure (`pangkatImperatives (second variant)`)

**What is being tested?**

The benchmark tests the performance of each version of the `pangkat` function, measuring how many executions per second it can handle on a specific device (in this case, Chrome 121 on Windows).

**Options compared**

The benchmark compares three different approaches:

1. **Recursive approach**: This approach uses recursive function calls to calculate the power.
2. **Imperative approach with while loop 1**: This approach uses a traditional while loop to iterate from `y` down to 0, multiplying the result by `x` in each iteration.
3. **Imperative approach with while loop 2**: This approach has a slightly different structure for the while loop compared to the first variant.

**Pros and Cons**

Here are some pros and cons of each approach:

1. Recursive approach:
	* Pros: Easy to implement, no explicit loop required.
	* Cons: Can lead to stack overflow errors if `y` is too large, can be less efficient due to repeated function calls.
2. Imperative approach with while loop 1:
	* Pros: Typically more efficient than recursive approaches, as it avoids repeated function calls and uses a simple loop structure.
	* Cons: May require more manual memory management and loop optimizations.
3. Imperative approach with while loop 2:
	* Pros: Similar to the first variant, but with a slightly different loop structure (no clear advantage).
	* Cons: Same as the previous variant.

**Library usage**

There is no explicit library mentioned in the benchmark definition or test cases.

**Special JS features or syntax**

None of the provided benchmarks explicitly use special JavaScript features like async/await, generators, or decorators. The focus seems to be on comparing different algorithmic approaches for calculating powers.

**Other alternatives**

If you were to implement a similar benchmark for other mathematical functions, you might consider exploring:

* Iterative approaches (e.g., using `for` loops or bitwise operations)
* Dynamic programming techniques
* Memoization or caching to reduce redundant calculations
* Using specialized libraries or hardware acceleration (if applicable)

Keep in mind that the choice of approach depends on the specific problem and performance requirements.

Factorial math (version: 3)

Comparing performance of: `Recursive vs While loop vs While loop (other)`

Created: 2 years ago by: Registered User

Go to the latest result

Recursive

While loop

While loop (other)

Historical Performance Data aggregated from 5 community runs

Desktop Results:

Chrome 5 runs

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

Factorial math (version: 3)

Comparing performance of: Recursive vs While loop vs While loop (other)

Created: 2 years ago by: Registered User

Go to the latest result

Recursive

While loop

While loop (other)

Historical Performance Data aggregated from 5 community runs

Desktop Results:

Chrome 5 runs

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

Related benchmarks

Comparing performance of: `Recursive vs While loop vs While loop (other)`