Benchmark: loop vs recursion

Tests:

recursion
x = function (n){ n++; if (n < 10000){x(n);}; } x(0)
loop
x = function (n){ while(n < 10000){ n++}}; x(0);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
recursion
loop

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

I'd be happy to explain the benchmark and its results.

**Benchmark Overview**

The provided benchmark measures the performance difference between two approaches: recursive function calls versus explicit loops. The goal is to determine which approach is faster for this specific test case.

**Benchmark Definition**

The JSON data defines a single benchmark with two test cases:

1. **Recursion**: A recursive function `x` that increments its input `n` until `n` reaches 10,000. The function calls itself recursively with the incremented value.
2. **Loop**: An explicit loop that increments a variable `n` from 0 to 9,999.

**Options Compared**

The benchmark compares two approaches:

* **Recursive Function Calls (Recursion)**: This approach uses a recursive function to iterate until a condition is met. The benefits of recursion include ease of implementation and potential for parallelization. However, it can lead to:
	+ Increased memory usage due to the call stack.
	+ Potential performance issues with deep recursion.
* **Explicit Loops**: This approach uses a loop to iterate until a condition is met. The benefits of loops include:
	+ Efficient use of resources (memory and CPU).
	+ Easy to implement and maintain.

**Pros and Cons**

* **Recursive Function Calls:**
	+ Pros:
		- Easier to understand and implement for simple cases.
		- Can be parallelized, which can improve performance.
	+ Cons:
		- Increased memory usage due to the call stack.
		- Potential performance issues with deep recursion.
* **Explicit Loops:**
	+ Pros:
		- Efficient use of resources (memory and CPU).
		- Easy to implement and maintain.
	+ Cons:
		- May be more complex to understand and implement for some cases.

**Library Usage**

Neither of the test cases uses a library, so there are no additional dependencies or optimizations to consider.

**Special JS Features/Syntax**

There is no special JavaScript feature or syntax used in this benchmark. The code follows standard JavaScript syntax.

**Other Alternatives**

If you were to run this benchmark on a different platform or with different hardware, the results might vary. However, the fundamental performance difference between recursive function calls and explicit loops should remain consistent.

Some alternative approaches could be:

* **Iterative Function**: Instead of recursion, an iterative approach using a loop would be another option.
* **Closure-based Approach**: Using closures to implement the recursive function could potentially improve performance by avoiding the overhead of creating new stack frames.
* **Async Approach**: Running the benchmark in parallel or using asynchronous programming could also provide insights into the performance differences between these approaches.

Latest run results:

Run details: (Test run date: 4 days ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36

Browser/OS: Chrome 130 on Windows

View result in a separate tab

Test name	Executions per second
recursion	580.2 Ops/sec
loop	150294.6 Ops/sec

Related benchmarks:

loop vs recursion (version: 0)

Comparing performance of: recursion vs loop

Created: 8 years ago by: Guest

Jump to the latest result

recursion

loop

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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