Benchmark: Spread whole array vs push [JS]

Tests:

spread
let arr = [] for(i=0; i<1000; i++) { arr = [...arr, i] }
push
let arr = [] for(i=0; i<1000; i++) { arr.push(i) }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
spread
push

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/146.0.0.0 Safari/537.36 Edg/146.0.0.0

Browser/OS: Chrome 146 on Windows

View result in a separate tab

Test name	Executions per second
spread	2557.6 Ops/sec
push	30324.0 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark and explain what's being tested, compared, and their pros and cons.

**Benchmark Overview**

The `MeasureThat.net` website provides a platform for users to create and run JavaScript microbenchmarks. The current benchmark measures the performance of two approaches: using the spread operator (`...`) versus pushing elements onto an array (`push`).

**Spread Operator (Spread)**

The first test case uses the spread operator to create a new array by copying the existing array `arr` and appending a new element `i`. This approach is often used when creating a new array with multiple copies of the original data.

Pros:

1. **Conciseness**: The spread operator is a concise way to create a new array, making the code more readable.
2. **Efficiency**: When using the spread operator, JavaScript only needs to allocate memory for the new array and copy the elements from `arr` to it. This can be more efficient than pushing multiple times.

Cons:

1. **Performance overhead**: While generally faster, there might be some performance overhead due to the allocation of memory and copying data.
2. **Memory allocation**: If the original array is large, allocating new memory for the spread operator can lead to increased memory usage.

**Push Operator (Push)**

The second test case uses the `push` method to append a new element to the end of the array `arr`. This approach is often used when adding one or more elements to an existing array without creating a new copy.

Pros:

1. **Efficient appending**: The `push` method is optimized for performance, as it only needs to update the length property and potentially reallocate memory if necessary.
2. **No extra memory allocation**: Using `push` does not require allocating additional memory, making it more memory-efficient.

Cons:

1. **Less concise**: Compared to the spread operator, using `push` requires multiple assignments or method calls, which can make the code less readable.

**Library: None**

Neither of these approaches relies on any external libraries. They are pure JavaScript implementations.

**Special JS feature/ syntax: None**

There are no special JavaScript features or syntax used in these test cases.

**Other alternatives**

If you're looking for alternative ways to create a new array, consider:

1. `concat()`: Similar to the spread operator, but uses the `concat()` method to concatenate arrays.
2. `Array.prototype.slice()`: Creates a shallow copy of an existing array using the `slice()` method.
3. Using a library like Lodash or Ramda for more complex data transformations.

In conclusion, the benchmark measures the performance difference between using the spread operator and pushing elements onto an array. While the spread operator is generally faster due to its conciseness and reduced memory allocation, it might have some performance overhead. The `push` method, on the other hand, is optimized for performance but may require more memory allocations. Ultimately, the choice between these approaches depends on your specific use case and performance requirements.

Related benchmarks:

Spread whole array vs push [JS] (version: 0)

Comparing performance of: spread vs push

Created: 3 years ago by: Guest

Jump to the latest result

spread

push

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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