Benchmark: reduce vs flat() test

Tests:

reduce + Array.prototype.concat
var params = [[ 1, 2 ], [ "hello", true, 7 ]]; var other = params.reduce((acc, val) => [...acc, ...val], []);
Array.prototype.flat
var params = [[1, 2, params], [ "hello", true, 7 ]]; var other = params.flat();

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
reduce + Array.prototype.concat
Array.prototype.flat

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/105.0.0.0 Safari/537.36

Browser/OS: Chrome 105 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
reduce + Array.prototype.concat	9508511.0 Ops/sec
Array.prototype.flat	1004895.4 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the benchmark and explain what's being tested.

**Benchmark Definition**

The benchmark is defined as "reduce vs flat() test", which compares two different approaches to spreading arrays in JavaScript:

1. `Array.prototype.reduce()` with the spread operator (`...`).
2. The traditional `Array.prototype.concat()` method.

**Options Compared**

Two options are compared:

1. **Spread Operator (new ES6 syntax)**: Using the spread operator (`...`) to create a new array by spreading the elements of an array.
2. **Traditional Concat Method**: Using the `concat()` method to merge arrays.

**Pros and Cons**

**Spread Operator:**

Pros:

* More concise and expressive way to create a new array from an existing one.
* Less memory allocation, as it creates a new array without modifying the original.

Cons:

* May be slower due to the overhead of creating a new array.
* Not supported in older browsers or environments that don't support ES6 syntax.

**Traditional Concat Method:**

Pros:

* Widely supported across various browsers and environments.
* Generally faster, as it uses a built-in method optimized for performance.

Cons:

* More verbose and less readable code.
* Creates a new array every time, which can lead to memory allocation issues in large datasets.

**Other Considerations**

The benchmark doesn't consider other factors that might affect the performance of these two approaches, such as:

* Array size: Larger arrays may lead to different performance characteristics.
* Data type: Different data types (e.g., numbers, strings) may have varying performance characteristics when spread or concatenated.
* Browser optimizations: Some browsers may optimize the `concat()` method for performance.

**Library and Special JS Features**

There are no libraries mentioned in the benchmark definition. However, the use of ES6 syntax (`var params = [[ 1, 2 ], [ \"hello\", true, 7 ]];`) indicates that the benchmark is using a relatively modern JavaScript version that supports this syntax.

**Test Case**

The test case compares two different approaches:

1. `reduce + Array.prototype.concat`: Uses the spread operator to create a new array by reducing an array of arrays and concatenating them with the original array.
2. `Array.prototype.flat`: Uses the traditional `flat()` method to flatten an array of arrays.

**Latest Benchmark Result**

The latest benchmark result shows that Chrome 105, running on a Desktop platform with Mac OS X 10.15.7, has:

* Higher executions per second for `reduce + Array.prototype.concat`.
* Lower executions per second for `Array.prototype.flat`.

This suggests that the spread operator approach might be faster in this specific scenario, but it's essential to note that benchmark results can vary depending on the environment and specific use case.

Related benchmarks:

reduce vs flat() test (version: 0)

Compare the new ES6 spread operator with the traditional concat() method

Comparing performance of: reduce + Array.prototype.concat vs Array.prototype.flat

Created: 2 years ago by: Guest

Jump to the latest result

reduce + Array.prototype.concat

Array.prototype.flat

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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