Benchmark: 1d to 2d array - for i vs while splice

Script Preparation code:

arr = [];
for (i=0; i<1024; i++) {
  arr.push(i); 
}

arr2 = [];
for (i=0; i<1024; i++) {
  arr2.push(i); 
}

Tests:

for i; += 2
var pairs = []; for (let i = 0; i < arr.length - 1; i += 2) { pairs.push([arr[i], arr[i + 1]]); }
while splice
var pairs = []; while(arr2.length) pairs.push(arr2.splice(0,2));

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
for i; += 2
while splice

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36

Browser/OS: Chrome 133 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
for i; += 2	267900.2 Ops/sec
while splice	137850464.0 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks and explore what's being tested in this specific benchmark.

**Benchmark Definition**

The provided JSON represents a JavaScript microbenchmark that tests two different approaches for iterating over a 2D array:

1. **For loop with increment (`+= 2`)**: This approach uses a traditional `for` loop to iterate over the array, incrementing the loop variable by 2 in each iteration.
2. **While loop with `splice()`**: This approach uses a `while` loop to iterate over the array, using the `splice()` method to remove and return elements from the array on each iteration.

**Options Compared**

The benchmark compares two different approaches for iterating over the 2D array:

* **For loop with increment (`+= 2`)**: This approach is more straightforward and efficient, as it allows the JavaScript engine to optimize the loop better.
* **While loop with `splice()`**: This approach uses a `while` loop, which can be slower due to the overhead of checking the length of the array on each iteration. Additionally, using `splice()` can lead to performance issues if not implemented carefully.

**Pros and Cons**

Here are some pros and cons of each approach:

* **For loop with increment (`+= 2`)**:
	+ Pros: More straightforward, efficient, and easier to optimize.
	+ Cons: May require manual memory management (e.g., keeping track of indices).
* **While loop with `splice()`**:
	+ Pros: Can be used for more complex iterations or when the array's length changes frequently.
	+ Cons: Slower due to the overhead of checking the length, and may lead to performance issues if not implemented carefully.

**Library Usage**

The benchmark uses the following library:

* None explicitly mentioned in the provided JSON. However, it is likely that the benchmark utilizes the `Array.prototype` methods (e.g., `length`, `splice`) which are built-in to JavaScript.

**Special JS Feature/Syntax**

There are no special JavaScript features or syntax used in this benchmark.

**Alternative Approaches**

Other alternative approaches for iterating over a 2D array could include:

* **Using an iterator**: JavaScript provides various iterator methods, such as `Array.prototype[Symbol.iterator]`, which can be used to iterate over arrays.
* **Using a library like Loopy**: Loopy is a small library that provides a simple way to iterate over arrays and other data structures in a more efficient manner.

In summary, this benchmark tests two different approaches for iterating over a 2D array: a traditional `for` loop with increment (`+= 2`) and a `while` loop with `splice()`. The benchmark compares the performance of these two approaches to provide insights into the most efficient way to iterate over 2D arrays in JavaScript.

Related benchmarks:

1d to 2d array - for i vs while splice (version: 0)

Comparing performance of: for i; += 2 vs while splice

Created: 7 years ago by: Guest

Jump to the latest result

for i; += 2

while splice

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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