Benchmark: toSorted vs slice&sort

Script Preparation code:


var arr = Array.from({ lenght: 1000 }).map((_, i) => Math.floor(Math.random() * 10000));
var sortedArr = null;

Tests:

toSorted
sortedArr = arr.toSorted()
slice&sort
sortedArr = arr.slice().sort()

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
toSorted
slice&sort

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/135.0.0.0 Safari/537.36

Browser/OS: Chrome 135 on Windows

View result in a separate tab

Test name	Executions per second
toSorted	6400906.0 Ops/sec
slice&sort	8404766.0 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated 6 months ago):

LLMs can make mistakes. Check important info.

I'd be happy to explain the benchmark and its options.

The provided JSON represents a JavaScript microbenchmarking test case on MeasureThat.net. The test aims to compare the performance of two different approaches: `toSorted` and `slice&sort`.

**Approach 1: `toSorted`**

The `toSorted` method is likely an implementation of a sorting algorithm, such as merge sort or insertion sort, that is built into the JavaScript engine. This approach uses the native sorting capabilities provided by the engine.

Pros:

* Native performance, optimized for the specific JavaScript engine.
* Typically faster than implementing a custom sorting algorithm from scratch.

Cons:

* May not be compatible with all JavaScript engines or versions.
* Limited control over the implementation details.

**Approach 2: `slice&sort`**

The `slice&sort` approach involves creating a copy of the original array using the `Array.prototype.slice()` method and then sorting the resulting array using the `Array.prototype.sort()` method. This approach requires manual memory allocation and copying of the array elements.

Pros:

* More control over the implementation details, such as the choice of sorting algorithm.
* Can be more efficient for large datasets or specific use cases.

Cons:

* Slower than native implementations due to the overhead of creating a copy of the array.
* May not be compatible with all JavaScript engines or versions.

**Other considerations**

* **Memory allocation**: The `slice&sort` approach requires manual memory allocation, which can lead to performance issues if not done correctly. Native implementations typically handle memory allocation internally.
* **Algorithmic complexity**: The choice of sorting algorithm used by the `toSorted` method may impact performance. For example, merge sort is generally faster than insertion sort for large datasets.

**Library usage**

In this test case, no external libraries are explicitly mentioned. However, it's worth noting that some JavaScript engines or frameworks might use internal libraries to implement certain features, such as sorting algorithms.

**Special JS feature/syntax**

There are no special JavaScript features or syntax used in this benchmarking test case. The code is straightforward and uses standard JavaScript syntax.

**Alternatives**

If you're looking for alternative ways to benchmark sorting performance, consider the following options:

1. **Native sort implementations**: Implement your own native sorting algorithm using a language like C++ or Rust, which can be compiled to machine code and provide optimal performance.
2. **Third-party libraries**: Utilize established third-party libraries that specialize in sorting algorithms, such as [Fast Sort](https://github.com/MarkKarpelès/fast-sort) or [Quicksort](https://github.com/lucascampanacci/quicksort-js).
3. **Benchmarking frameworks**: Leverage specialized benchmarking frameworks like [Benchpress.js](https://github.com/ben-eb bach/benchpress.js) or [benchmarking-library](https://github.com/cupcake-brownies/benchmarking-library), which provide a simple and efficient way to write and run benchmarks.

Keep in mind that each alternative approach has its own trade-offs, and the best choice depends on your specific requirements and constraints.

Related benchmarks:

toSorted vs slice&sort (version: 0)

Comparing performance of: toSorted vs slice&sort

Created: one year ago by: Registered User

Jump to the latest result

toSorted

slice&sort

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 6 months ago):