Benchmark: foreach overhead

Script Preparation code:

var items = ['abc'];
function do_something(thing) {
  return 'sh' + thing;
}

Tests:

foreach
items.forEach(thing => do_something(thing));
for
for (var i = 0; i < items.length; i++) { do_something(items[i]); }
placebo
do_something(items[0]);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
foreach
for
placebo

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

This benchmark does not have any results yet. Be the first one to run it!

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 Overview**

The benchmark, named "foreach overhead," aims to measure the performance difference between three approaches: using `forEach`, a traditional `for` loop, and a placeholder test. The goal is to determine which approach has the lowest overhead in terms of execution time.

**Script Preparation Code**

The script preparation code defines two functions:

* `do_something(thing)`: This function takes a string as an input and returns a modified string by appending 'sh' to it.
* An array `items` containing a single element: `'abc'`.

**Html Preparation Code**

There is no HTML preparation code, which means that the benchmark only focuses on JavaScript execution time.

**Individual Test Cases**

The benchmark consists of three test cases:

1. **"foreach"`**: This test case executes the `forEach` loop on the `items` array, passing a callback function `do_something(thing)` to it.
2. **"for"`**: This test case uses a traditional `for` loop to iterate over the `items` array and calls `do_something(items[i])` for each iteration.
3. **"placebo"`**: This is the placeholder test, which simply executes `do_something(items[0])`. Its purpose is to serve as a baseline or control group.

**Library Usage**

There is no explicit library usage in this benchmark, but the `forEach` loop uses the ECMAScript 2015 (ES6) specification's `Array.prototype.forEach()` method. This method was introduced to provide a more concise and readable way to iterate over arrays compared to traditional loops.

**Special JS Features/Syntax**

There are no special JavaScript features or syntax used in this benchmark, apart from the ES6 `forEach` loop, which is considered a standard feature at this point.

**Pros and Cons of Different Approaches**

Here's a brief analysis of the pros and cons of each approach:

* **"foreach"`**: Pros:
	+ More concise and readable than traditional loops.
	+ Easier to write and maintain for developers familiar with ES6 syntax.
*   Cons:
	+ May introduce additional overhead due to the use of the `forEach` loop, which might be slower than a traditional loop.

*   **"for"`**: Pros:
	+ Can be faster than the `foreach` loop since it avoids the overhead of the callback function.
	+ More control over iteration variables and loop logic.
*   Cons:
	+ Less readable and maintainable for developers familiar with ES6 syntax.
	+ Requires more manual indexing and type checking.

**Other Alternatives**

If you were to rewrite this benchmark, you might consider using alternative approaches, such as:

* **`map()`**: Instead of using `forEach`, you could use the `Array.prototype.map()` method, which is another concise way to perform array transformations.
*   **`reduce()`**: You could also use the `Array.prototype.reduce()` method to iterate over the array and accumulate a result.

Keep in mind that these alternatives might not provide significant performance differences and should be evaluated based on specific requirements and optimization goals.

Related benchmarks:

foreach overhead (version: 0)

Comparing performance of: foreach vs for vs placebo

Created: 7 years ago by: Guest

Jump to the latest result

foreach

for

placebo

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):