Benchmark: Mapping a ranged value array v1

Script Preparation code:

var array_length = 30;

Tests:

Original jobsity code
const results = [...Array(array_length + 1).keys()].map(i => { number: i }); results.shift();
Simplified
const results = [...Array(array_length).keys()].map(i => { number: i + 1 });
FOR loop
const results = []; for (let number = 1; number <= array_length; number++) { results.push({ number }); }
Creating the array with the desired numbers as initial values
const results= Array.from( { length: array_length }, (elem, idx) => idx + 1 ).map(i => { number: i })

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Original jobsity code
Simplified
FOR loop
Creating the array with the desired numbers as initial values

Fastest: N/A

Slowest: N/A

Latest run results:

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

LLMs can make mistakes. Check important info.

I'll provide an explanation of the benchmark, its options, and considerations.

**Benchmark Overview**

The benchmark is designed to measure the performance of JavaScript code that creates an array of objects based on a specific range of values. The script preparation code is provided for each test case, which defines an array length variable (`array_length`) with a value of 30.

**Test Cases**

There are four test cases:

1. **Original jobsity code**: This implementation uses the `Array.prototype.map()` method to create the array of objects.
2. **Simplified**: This implementation creates the array using the spread operator and an arrow function.
3. **FOR loop**: This implementation uses a traditional `for` loop to push objects into an array.
4. **Creating the array with the desired numbers as initial values**: This implementation uses the `Array.from()` method with an initial value.

**Options Compared**

The benchmark compares the performance of four different approaches:

* `map()`
* Spread operator and arrow function
* Traditional `for` loop
* `Array.from()` with initial value

**Pros and Cons**

Here's a brief summary of the pros and cons for each approach:

1. **Map()**: Pros: concise, expressive code; Cons: may incur additional overhead due to function invocation.
2. **Spread operator and arrow function**: Pros: concise, expressive code; Cons: may not be as readable as other approaches.
3. **FOR loop**: Pros: control over iteration order; Cons: verbose, may lead to performance issues if not optimized properly.
4. **Array.from() with initial value**: Pros: concise, efficient code; Cons: requires knowledge of `Array.from()` API.

**Library/Functionality**

None of the test cases use a library or external function that affects the benchmark results. However, it's worth noting that some JavaScript engines may have specific optimizations for certain built-in functions like `map()`, which could impact performance.

**Special JS Features/Syntax**

There are no special JavaScript features or syntax used in this benchmark.

**Other Alternatives**

If you're interested in exploring alternative approaches to this problem, consider the following:

* Using `reduce()` instead of `map()` for creating arrays.
* Utilizing web workers or other parallel computing techniques to take advantage of multi-core processors.
* Experimenting with different data structures, such as `Set` or `Map`, for storing and processing the array elements.

Keep in mind that these alternatives may not be directly related to the specific problem being benchmarked, but they could provide interesting performance trade-offs or optimization opportunities.

Related benchmarks:

Mapping a ranged value array v1 (version: 2)

Creates objects based on a specific range of values, to be used as values within the mapped object.

Comparing performance of: Original jobsity code vs Simplified vs FOR loop vs Creating the array with the desired numbers as initial values

Created: 2 years ago by: Registered User

Jump to the latest result

Original jobsity code

Simplified

FOR loop

Creating the array with the desired numbers as initial values

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

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