Benchmark: test benchmark for large slice

Script Preparation code:

var test = Array.from({
    length: 100000
}, () => ({
    "lat": 0,
    "lon": 0,
    "metadata": {
        "name": "test"
    }
}))

Tests:

1
test.slice(10, 20)
2
test.slice(100, 200)
3
test.slice(1000, 20000)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
1
2
3

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (iPhone; CPU iPhone OS 16_4 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) CriOS/113.0.5672.121 Mobile/15E148 Safari/604.1

Browser/OS: Chrome Mobile iOS 113 on iOS 16.4

View result in a separate tab

Test name	Executions per second
1	23639682.0 Ops/sec
2	9213137.0 Ops/sec
3	92523.0 Ops/sec

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

LLMs can make mistakes. Check important info.

Measuring performance of JavaScript benchmarks can be a complex task, and there are various approaches to achieve this.

**Benchmark Setup**

The provided benchmark setup uses two main scripts:

1. `Script Preparation Code`: This script creates an array of 100,000 objects with latitude (lat), longitude (lon), and metadata properties.
2. `Html Preparation Code` is not used in this case, but it's likely intended to set up the HTML environment for the benchmark.

**Options Compared**

The provided benchmarks compare different slicing options:

1. **test.slice(10, 20)**: This benchmark tests slicing a subset of 10 elements out of an array of 100,000 elements.
2. **test.slice(100, 200)**: This benchmark tests slicing a subset of 100 elements out of the same array.
3. **test.slice(1000, 20000)**: This benchmark tests slicing a subset of 1,000 elements out of the same array.

These benchmarks test how different browsers and devices perform when dealing with large arrays and slicing operations.

**Pros and Cons**

Here are some pros and cons for each approach:

* **Fastest execution**: Slicing from the beginning of the array (e.g., `test.slice(10, 20)` or `test.slice(100, 200)`) is likely to be faster because it requires less work to access elements that are already stored in memory.
* **Worst-case scenario**: Slicing from the middle or end of the array (e.g., `test.slice(1000, 20000)`) might be slower because it may require more CPU cycles to access and retrieve elements from further away in memory.

**Library Use**

The benchmark uses the `Array.prototype.slice()` method, which is a built-in JavaScript function. This method creates a new array containing only the specified elements of the original array.

**Special JS Features or Syntax**

There are no special JavaScript features or syntax used in this benchmark that would require explanation beyond basic JavaScript concepts.

**Other Considerations**

When measuring performance of JavaScript benchmarks, consider the following factors:

* **Memory allocation**: The amount of memory allocated for each benchmark can impact performance. Large arrays and frequent slicing operations can lead to increased memory usage.
* **CPU cycles**: Different browsers and devices may execute CPU instructions differently, leading to variations in performance.
* **Cache effects**: Modern CPUs often use caching mechanisms to improve performance. Different browsers and devices might have varying cache sizes and behaviors.

**Alternatives**

If you're looking for alternatives to MeasureThat.net or want to explore other benchmarking tools:

1. **Benchmark.js**: A popular benchmarking library for Node.js that allows you to write custom benchmarks.
2. **JSPerf**: A well-known benchmarking tool specifically designed for JavaScript performance testing.
3. **Benchmarking frameworks**: Many web frameworks, such as React and Angular, include built-in benchmarking tools or modules that can be used for performance testing.

When choosing a benchmarking tool, consider the specific requirements of your project and the type of performance characteristics you want to measure (e.g., page load times, DOM manipulation, or CPU-bound operations).

Related benchmarks:

test benchmark for large slice (version: 0)

Comparing performance of: 1 vs 2 vs 3

Created: one year ago by: Guest

Jump to the latest result

1

2

3

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):