Benchmark: test stefaf aasf13123

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/npm/bignumber.js@9.0.1/bignumber.min.js"></script>

Tests:

my
function plus(a, b) { let result = []; const aSplit = String(a).split("."); const bSplit = String(b).split("."); result[0] = [BigInt(aSplit[0]) + BigInt(bSplit[0])]; if(!aSplit[1]) { aSplit[1] = 0; } if(!bSplit[1]) { bSplit[1] = 0; } result[1] = [BigInt(aSplit[1]) + BigInt(bSplit[1])]; if(result[1] > 9) { result[0]++; result[1] = result[1] % 10; } return String(result.join('.')); } plus(0.1,0.3)
BigNumber
var a = new BigNumber("0.1"); var b = new BigNumber("0.2"); a.plus(b).toString();
Native
var a = 0.1; var b = 0.2; ((a + b) * b).toString();

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
my
BigNumber
Native

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 3 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/95.0.4638.69 Safari/537.36

Browser/OS: Chrome 95 on Windows

View result in a separate tab

Test name	Executions per second
my	472437.3 Ops/sec
BigNumber	762559.2 Ops/sec
Native	181596624.0 Ops/sec

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

LLMs can make mistakes. Check important info.

I'll break down the provided benchmark and explain what's being tested, compared, and considered.

**Benchmark Overview**

MeasureThat.net is a website where users can create and run JavaScript microbenchmarks. The provided benchmark measures the performance of three different approaches for calculating the sum of two decimal numbers: "Native", "BigNumber", and "my".

**Script Preparation Code**

The script preparation code includes an external library, `bignumber.js`, which is used in one of the test cases.

```javascript
"<script src=\"https://cdn.jsdelivr.net/npm/bignumber.js@9.0.1/bignumber.min.js\"></script>"
```

This library provides a Big Number data type to handle very large and precise decimal numbers, which is useful for calculations involving big numbers.

**Individual Test Cases**

There are three test cases:

1. **"my"**
This test case uses a custom implementation of the `plus` function, similar to the "Native" approach. However, instead of using arithmetic operators (`+`, `*`) directly on decimal numbers, it splits the decimal number into two parts (separated by a dot), converts them to BigInts, performs the calculation, and then joins the results back together.
2. **"BigNumber"**
This test case uses the Big Number library to perform the calculation. The library provides a `new BigNumber` constructor that creates a new Big Number instance from a string representation of the number, and a `plus` method that adds two Big Numbers together.
3. **"Native"**
This test case uses native JavaScript arithmetic operators (`+`, `*`) directly on decimal numbers.

**Comparison**

The three approaches are compared in terms of their execution speed (in executions per second). The approach with the highest number of executions per second is considered to be the fastest.

Here's a brief summary of each approach:

1. **"my"**: This implementation has some advantages:
	* It avoids the limitations of JavaScript's built-in decimal arithmetic, such as precision and rounding issues.
	* However, it introduces additional complexity due to the need to split and join the numbers.
2. **"BigNumber"**: This library provides a simple and efficient way to perform large-precision calculations:
	* It abstracts away the underlying implementation details, making it easier to switch between different platforms or languages.
	* However, it requires an additional dependency (the Big Number library) and may introduce some overhead due to the library's internal workings.
3. **"Native"**: This approach is simple and straightforward but also has some limitations:
	* It relies on JavaScript's built-in decimal arithmetic, which can lead to precision issues and rounding errors for very large numbers.

**Pros and Cons**

Here are some pros and cons of each approach:

1. **"my"**:
	* Pros: avoids JavaScript's decimal arithmetic limitations, flexible implementation.
	* Cons: introduces additional complexity, may not be as efficient as the other approaches.
2. **"BigNumber"**:
	* Pros: easy to use, abstracts away underlying implementation details, provides precise control over calculations.
	* Cons: requires an additional dependency, may introduce some overhead due to library internal workings.
3. **"Native"**:
	* Pros: simple and straightforward, no additional dependencies required.
	* Cons: relies on JavaScript's built-in decimal arithmetic, can lead to precision issues and rounding errors.

**Other Considerations**

When choosing an approach, consider the following factors:

1. **Precision**: If you need extremely high precision for your calculations, "BigNumber" or a similar library might be the best choice.
2. **Performance**: If speed is critical, "Native" or "my" (with proper optimization) might be more suitable.
3. **Complexity**: If simplicity and ease of use are important, "BigNumber" could be the way to go.

**Alternatives**

Other alternatives for performing large-precision calculations in JavaScript include:

1. **Decimal.js**: A library that provides a decimal arithmetic implementation with precise control over calculations.
2. **JS Number**: A polyfill that provides a precise decimal arithmetic implementation for older browsers or environments without built-in decimal support.
3. **Arbitrary Precision Arithmetic libraries like MPFR (Multiple Precision Floating-Point Representation)**: These libraries provide a more robust and flexible way to perform large-precision calculations, but often require additional dependencies and configuration.

In conclusion, the choice of approach depends on your specific requirements, such as precision, performance, complexity, or ease of use.

Related benchmarks:

test stefaf aasf13123 (version: 0)

Comparing performance of: my vs BigNumber vs Native

Created: 3 years ago by: Guest

Jump to the latest result

my

BigNumber

Native

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):