Benchmark: Perfs of bignumber

HTML Preparation code:

<script src='https://cdn.jsdelivr.net/npm/bignumber.js@9.1.0/bignumber.min.js'></script>
<script src="https://cdn.jsdelivr.net/npm/lodash@4.17.4/lodash.min.js"></script>

Script Preparation code:

var values = _.times(500, Math.random());

Tests:

Lodash METHOD
var res = _.mean(values); return res;
bignumber METHOD
var total = BigNumber(0); _.each(values, val => { total.plus(BigNumber(val)); }); console.log(total); var res = total.div(values.length); return res;

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Lodash METHOD
bignumber METHOD

Fastest: N/A

Slowest: N/A

Latest run results:

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

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Let's break down the provided benchmark and explain what's being tested.

**What is being tested?**

The benchmark is testing the performance of two different approaches to calculate the mean of an array of random numbers: using Lodash (`_.mean`) and using the bignumber.js library (`BigNumber`).

**Options compared**

There are two options being compared:

1. **Lodash METHOD**: This method uses the `_.mean` function from Lodash, a popular JavaScript utility library.
2. **bignumber METHOD**: This method uses the `BigNumber` class from bignumber.js to perform arithmetic operations on large numbers.

**Pros and cons of each approach**

* **Lodash METHOD**
	+ Pros:
		- Easy to use and well-documented
		- Fast and efficient, thanks to optimized C code under the hood
	+ Cons:
		- Requires an additional library dependency (Lodash)
		- May not be suitable for very large datasets due to memory constraints
* **bignumber METHOD**
	+ Pros:
		- Provides a dedicated solution for handling large numbers, making it well-suited for bignum arithmetic
		- Can handle larger datasets than Lodash, thanks to its optimized C implementation
	+ Cons:
		- Requires additional library dependency (bignumber.js)
		- May have slower startup times due to the overhead of loading the library

**Other considerations**

* **Library usage**: Both benchmarks use external libraries (Lodash and bignumber.js). This can add overhead in terms of memory allocation, garbage collection, and potential conflicts with other libraries.
* **Special JS features**: Neither benchmark uses any special JavaScript features or syntax that would affect their performance. They are purely functional comparisons between two approaches.

**Alternative approaches**

If the developers want to explore alternative methods, they could consider:

1. Using built-in JavaScript functions (e.g., `reduce()`, `every()` with a custom callback) instead of Lodash.
2. Implementing arithmetic operations manually using bitwise operations and bit manipulation techniques.
3. Using specialized libraries for numerical computations, such as NumJS or Math.js.

However, these alternatives might not be suitable for large-scale performance testing, as they may introduce significant overhead in terms of execution time or code complexity.

Related benchmarks:

Perfs of bignumber (version: 0)

Comparing performance of: Lodash METHOD vs bignumber METHOD

Created: 3 years ago by: Guest

Jump to the latest result

Lodash METHOD

bignumber METHOD

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):