Benchmark: concat vs spread funcking operator

Script Preparation code:

const a = [1,2,3,4,5,6,7,8,9,1,2,3,4,5,6,7,8,9,1,2,3,4,5,6,7,8,9,0]
const b = ['a','b','c','d','e','f','g','h','i','a','a','a','a','a','a','a','a','a','a','a','a']

Tests:

concat
const a = [1,2,3,4,5,6,7,8,9,1,2,3,4,5,6,7,8,9,1,2,3,4,5,6,7,8,9,0] const b = ['a','b','c','d','e','f','g','h','i','a','a','a','a','a','a','a','a','a','a','a','a'] const result = a.concat(b)
spread
const a = [1,2,3,4,5,6,7,8,9,1,2,3,4,5,6,7,8,9,1,2,3,4,5,6,7,8,9,0] const b = ['a','b','c','d','e','f','g','h','i','a','a','a','a','a','a','a','a','a','a','a','a'] const result = [...a, ...b]

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
concat
spread

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 26 days ago):

LLMs can make mistakes. Check important info.

Let's dive into the benchmark.

**What is being tested?**

The provided JSON represents two JavaScript microbenchmarks that compare the performance of the `concat` and `spread` operators in concatenating arrays.

**Options compared:**

There are two options being compared:

1. **Concatenation using the `concat` operator**: This involves calling the `concat` method on an array, passing another array as an argument.
2. **Concatenation using the spread operator (`...`)**: This involves using the spread operator to concatenate arrays.

**Pros and Cons of each approach:**

1. **Concatenation using the `concat` operator**:
	* Pros:
		+ Simple and straightforward syntax.
		+ Wide support across browsers and platforms.
	* Cons:
		+ Can be slower than other approaches due to the overhead of calling a method on an array.
2. **Concatenation using the spread operator (`...`)**:
	* Pros:
		+ More concise and readable syntax.
		+ Can be faster than `concat` due to the use of a primitive operator (the spread operator is optimized in modern browsers).
	* Cons:
		+ Less intuitive syntax for some developers, especially those familiar with older JavaScript versions.

**Library usage:**

None of the benchmark tests use external libraries. The focus is solely on the JavaScript language and its built-in features.

**Special JS feature or syntax:**

The `concat` operator uses a method call syntax (`array.concat(otherArray)`), which is a common pattern in JavaScript. However, this specific syntax is not necessarily special to modern JavaScript versions; it's more of an older-style way of doing things that still works today.

**Benchmark test cases:**

Each test case defines the input arrays `a` and `b`, followed by the concatenation expression using either the `concat` operator or the spread operator. The goal is to measure the performance difference between these two approaches.

**Other alternatives:**

There are other ways to concatenate arrays in JavaScript, such as:

1. Using the `+` operator: `a + b`
2. Using a loop: `for (let i = 0; i < a.length + b.length; i++) { ... }`

However, these approaches are generally less efficient and less readable than using the `concat` or spread operators.

**Benchmark results:**

The latest benchmark results show that Chrome 70 on a Linux desktop performed:

* 4063537.75 executions per second for the `concat` approach
* 3297120.25 executions per second for the `spread` approach

This suggests that the spread operator is slightly faster in this specific test case, although the difference is relatively small and may not be noticeable in most real-world scenarios.

Latest run results:

Run details: (Test run date: 6 years ago)

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.77 Safari/537.36

Browser/OS: Chrome 70 on Linux

View result in a separate tab

Test name	Executions per second
concat	4063537.8 Ops/sec
spread	3297120.2 Ops/sec

Related benchmarks:

concat vs spread funcking operator (version: 0)

Comparing performance of: concat vs spread

Created: 6 years ago by: Guest

Jump to the latest result

concat

spread

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 26 days ago):