Benchmark: Performance Test

Script Preparation code:

let testData = [1, 2, 3, 4, 5];

Tests:

slice
let testData = [1, 2, 3, 4, 5]; let testResult = testData.slice();
splice
let testData = [1, 2, 3, 4, 5]; let testResult = testData.splice(0);
concat
let testData = [1, 2, 3, 4, 5]; let testResult = testData.concat();
for loop
let testData = [1, 2, 3, 4, 5]; let testResult = []; for (let i = 0; i < testData.length; i++) { testResult.push(testData[i]); }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
slice
splice
concat
for loop

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 29 days ago):

LLMs can make mistakes. Check important info.

Let's break down the provided JSON data and explain what's being tested in each benchmark.

**Benchmark Overview**

The provided JSON data represents a set of benchmarks for measuring performance in JavaScript. Each benchmark is defined by a script preparation code, which contains the test case being measured. The test cases are:

1. `slice`
2. `splice`
3. `concat`
4. `for loop`

**Options Being Compared**

Each benchmark is comparing different approaches to achieve the same result. Here's what's being tested in each benchmark:

1. **`slice()`**: Measures the performance of using the `slice()` method to create a shallow copy of an array.
2. **`splice()`**: Measures the performance of using the `splice()` method to remove elements from an array and return them as an array.
3. **`concat()`**: Measures the performance of using the `concat()` method to concatenate two arrays.
4. **`for loop`**: Measures the performance of manually iterating over an array using a `for` loop.

**Pros and Cons of Each Approach**

Here are some pros and cons of each approach:

1. **`slice()`**:
	* Pros: Creates a shallow copy of the original array, doesn't modify it.
	* Cons: Can be slower than other methods if the array is large.
2. **`splice()`**:
	* Pros: Returns an array of removed elements, can be useful for certain use cases.
	* Cons: Can be slower than other methods if the array is large, modifies the original array.
3. **`concat()`**:
	* Pros: Creates a new array and returns it, doesn't modify the original arrays.
	* Cons: Can be slower than other methods if the arrays are large.
4. **`for loop`**:
	* Pros: Allows for manual control over the iteration process.
	* Cons: Can be slower than other methods due to the overhead of manual iteration.

**Libraries Used**

None of the benchmarks use any external libraries.

**Special JavaScript Features or Syntax**

None of the benchmarks use any special JavaScript features or syntax, such as ES6 modules, async/await, or generators.

**Other Alternatives**

Some alternative approaches that could be tested in these benchmarks include:

1. **Using `Array.prototype.reduce()`**: Instead of using a `for` loop, you could use the `reduce()` method to achieve the same result.
2. **Using `Array.prototype.map()`**: You could also use the `map()` method to create a new array without modifying the original one.
3. **Using a custom implementation**: You could implement your own custom algorithm for each benchmark to see if it performs better than the built-in methods.

Overall, these benchmarks provide a good starting point for measuring performance in JavaScript and can help developers understand which approaches are most efficient in different scenarios.

Latest run results:

Run details: (Test run date: 5 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.102 Safari/537.36 OPR/57.0.3098.106

Browser/OS: Opera 57 on Windows

View result in a separate tab

Test name	Executions per second
slice	73009648.0 Ops/sec
splice	5609076.0 Ops/sec
concat	8566590.0 Ops/sec
for loop	32098160.0 Ops/sec

Related benchmarks:

Performance Test (version: 0)

Comparing performance of: slice vs splice vs concat vs for loop

Created: 5 years ago by: Guest

Jump to the latest result

slice

splice

concat

for loop

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 29 days ago):