Benchmark: for let - MeasureThat.net

Script Preparation code:

var list = Array.from(Array(1000).keys());

Tests:

let for
let i = 0; for(i=0; i<list.length; i++){}
for with let
for(let i=0; i<list.length; i++){}

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
let for
for with let

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

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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 definition, test cases, and latest benchmark results to help explain what's being tested.

**Benchmark Definition**

The JSON represents a JavaScript microbenchmark with two main components:

1. **Script Preparation Code**: `var list = Array.from(Array(1000).keys());`. This code generates an array of 1000 unique indices (from 0 to 999) using the `Array.from()` method and `Array(1000).keys()`. The purpose of this script preparation code is to initialize a large dataset that will be used in subsequent test cases.

2. **Html Preparation Code**: `null`. This field is empty, which means no additional HTML setup is required for the benchmark.

**Individual Test Cases**

There are two individual test cases:

1. **"let i = 0; for(i=0; i<list.length; i++){}"`: This test case uses a traditional variable declaration `let` and assigns an initial value to the variable `i`. The loop then increments `i` using the traditional increment operator (`i++`) inside the loop condition.

2. **"for(let i=0; i<list.length; i++){}"`: This test case uses an immediately invoked `for...of` loop, where a new variable `i` is declared and initialized to 0 within the loop itself using `let`. The loop then iterates over the length of the list.

**Options Compared**

The two test cases compare different approaches to iterating over a large dataset:

* **Traditional Variable Declaration (`let i = 0; for(i=0; ...)`)**: This approach is straightforward and widely supported by JavaScript engines. It uses a traditional variable declaration and assigns an initial value to the loop counter.
* **Immediately Invoked `for...of` Loop (`for(let i=0; ...){}`)**: This approach is more concise and efficient, as it avoids the need for explicit incrementation of the loop counter. However, some older JavaScript engines might not support this syntax.

**Pros and Cons**

* **Traditional Variable Declaration**:
	+ Pros: Wide support across JavaScript engines.
	+ Cons: May introduce performance overhead due to unnecessary variable creation and garbage collection.
* **Immediately Invoked `for...of` Loop**:
	+ Pros: More concise, potentially faster execution, and fewer memory allocations.
	+ Cons: Less widely supported by older JavaScript engines.

**Other Considerations**

When writing microbenchmarks like this one, it's essential to consider the following:

* **Warm-up phase**: The script preparation code is run once before executing any test cases. This can help warm up the engine and improve results.
* **Loop unrolling**: Some modern JavaScript engines may optimize loops by unrolling them (e.g., 16 iterations at a time). However, this optimization might not always be present or enabled.

**Alternative Approaches**

Some alternative approaches to iterating over a large dataset include:

* Using `for...in` instead of `for...of`, although this can lead to slower performance and more memory allocations.
* Employing specialized iteration libraries like `Array.prototype.forEach()` or `Array.prototype.map()`.
* Utilizing SIMD instructions (e.g., using a library that generates a loop that can be executed in parallel).

Keep in mind that the best approach will depend on the specific use case, target JavaScript engine, and performance requirements.

Related benchmarks:

for let (version: 0)

Comparing performance of: let for vs for with let

Created: 5 years ago by: Guest

Jump to the latest result

let for

for with let

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

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