Benchmark: sparse arrays test

Tests:

no sparse arrays
var s = []; s[0] = 0; s[1] = 1; s[2] = 2; s[3] = 3; s[4] = 4; s[5] = 5;
no sparse arrays with -1 idx
var s = []; s[-1] = 0; s[0] = 1; s[1] = 2; s[2] = 3; s[3] = 4; s[4] = 5;
sparse array
var s = []; s[0] = 0; s[3] = 1; s[5] = 2; s[6] = 3; s[9] = 4; s[20] = 5;

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
no sparse arrays
no sparse arrays with -1 idx
sparse array

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 2 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/121.0.0.0 Safari/537.36

Browser/OS: Chrome 121 on Windows

View result in a separate tab

no sparse arrays

33.3M/s

sparse array

15.2M/s

no sparse arrays with -1 idx

4.6M/s

View exact numbers

Test name	Executions per second
✓ no sparse arrays	33,307,176 Ops/sec
sparse array	15,215,431 Ops/sec
no sparse arrays with -1 idx	4,605,016 Ops/sec

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

LLMs can make mistakes. Check important info.

**Overview of the Benchmark**

MeasureThat.net is a website that allows users to create and run JavaScript microbenchmarks. The provided benchmark definition json represents a simple test case for creating a sparse array in JavaScript.

**Options Compared**

The benchmark compares three different approaches to create a sparse array:

1. **No sparse arrays**: This approach uses the `[]` syntax to create an array with explicit indices (e.g., `s[0] = 0`, `s[1] = 1`, etc.).
2. **No sparse arrays with -1 index**: This approach uses the `[-1]` syntax to create a sparse array with a negative index (e.g., `s[-1] = 0`).
3. **Sparse array**: This approach uses the `[...]` syntax to create an array with optional indices (e.g., `s[0] = 0`, `s[3] = 1`, etc.).

**Pros and Cons of Each Approach**

1. **No sparse arrays**:
	* Pros: Easy to understand, no special syntax required.
	* Cons: Can be less efficient due to the need for explicit indexing.
2. **No sparse arrays with -1 index**:
	* Pros: Allows for more concise code, can be faster than explicit indexing.
	* Cons: May require special handling or consideration when working with this syntax.
3. **Sparse array**:
	* Pros: Can be more efficient and concise than explicit indexing.
	* Cons: Requires the use of optional indices, which may take some getting used to.

**Library and Special JS Features**

There is no library mentioned in the benchmark definition json. However, the `sparse arrays` syntax (`[...]`) is a special feature of JavaScript that allows for optional indices.

**Other Considerations**

The benchmark also considers the device platform (Desktop) and operating system (Windows). This may be relevant if you're running the benchmark on different environments.

**Alternatives**

If you're looking for alternative approaches to creating sparse arrays, you can consider using other libraries or frameworks that provide additional functionality. Some examples include:

* Lodash: Provides a `rest parameter` syntax (`[...args]`) for creating sparse arrays.
* Array.prototype.slice(): Can be used to create a sparse array by calling `slice()` with an empty array and some indices.

Keep in mind that the best approach will depend on your specific use case and requirements.

sparse arrays test (version: 1) Benchmark.js

Comparing performance of: `no sparse arrays vs no sparse arrays with -1 idx vs sparse array`

Created: 2 years ago by: Registered User

Go to the latest result

no sparse arrays

no sparse arrays with -1 idx

sparse array

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

sparse arrays test (version: 1) Benchmark.js

Comparing performance of: no sparse arrays vs no sparse arrays with -1 idx vs sparse array

Created: 2 years ago by: Registered User

Go to the latest result

no sparse arrays

no sparse arrays with -1 idx

sparse array

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

Related benchmarks

Comparing performance of: `no sparse arrays vs no sparse arrays with -1 idx vs sparse array`