Benchmark: Slice vs deconstruction based copy

Script Preparation code:

var array = Array(100).fill(1);

Tests:

splice
let i = 10000; while(i>0) { const t1 = array.slice() i--; }
deconstruct
let i = 10000; while(i>0) { const t1 = [...array]; i--; }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
splice
deconstruct

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 16 days ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36

Browser/OS: Chrome 130 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
splice	1242.6 Ops/sec
deconstruct	637.9 Ops/sec

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

LLMs can make mistakes. Check important info.

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

**Benchmark Definition**

The benchmark definition is a JavaScript script that defines two test cases: `splice` and `deconstruct`. Both tests measure the performance of creating a copy of an array using different approaches.

**Approaches Compared**

1. **Slice**: The first approach uses the `array.slice()` method to create a copy of the array.
2. **Deconstruction**: The second approach uses destructuring assignment (`const t1 = [...array];`) to create a copy of the array.

**Pros and Cons of Each Approach**

* **Slice**: Pros:
	+ Widely supported by browsers and JavaScript engines.
	+ Simple to implement.
Cons:
	+ May involve more overhead due to the creation of a new object.
* **Deconstruction**: Pros:
	+ Can be faster than `slice()` because it doesn't create a new object, but instead creates an array view into the original array.
	+ More efficient use of memory.
Cons:
	+ May not work in older browsers or JavaScript engines that don't support this syntax.

**Other Considerations**

* The benchmark uses a large array (100 elements) to simulate real-world scenarios where performance is critical.
* Both tests are run in a `while` loop to ensure that the results are consistent across multiple executions.

**Library and Purpose**

There isn't a specific library mentioned in the JSON, but it's likely that the author of the benchmark used the built-in JavaScript features for array manipulation. However, some libraries like Lodash or Ramda might have been used indirectly by importing functions from other modules.

**Special JS Features or Syntax**

The `deconstruct` approach uses a feature called "destructuring assignment", which is a syntax introduced in ECMAScript 2015 (ES6). This feature allows you to extract values from an array into separate variables. The `const t1 = [...array];` expression creates a new array view into the original array, allowing for efficient iteration over the elements.

**Other Alternatives**

If you're interested in exploring alternative approaches or libraries, here are some options:

* **Array.prototype.map()**: You can use `map()` to create a copy of an array by mapping each element to a new value. However, this approach might be slower than `slice()` and deconstruction due to the overhead of function calls.
* **`Array.from()`**: This method creates a new array from an iterable source, which could be used as an alternative to deconstruction.
* **Third-party libraries**: Some popular JavaScript libraries like Lodash or Ramda provide optimized functions for array manipulation, including slicing and creating copies.

Keep in mind that the performance differences between these approaches might not be significant in all scenarios. However, when dealing with large datasets and high-performance requirements, the differences become more pronounced.

Related benchmarks:

Slice vs deconstruction based copy (version: 0)

Comparing performance of: splice vs deconstruct

Created: 4 years ago by: Guest

Jump to the latest result

splice

deconstruct

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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