Benchmark: strategy to count

HTML Preparation code:

<!--your preparation HTML code goes here-->

Script Preparation code:

var x1,x2, hue = 192

Tests:

math.abs
x1 = 1 - Math.abs((hue / 60) % 2 - 1);
ternary trunc
(hue/60 - ((hue/60)|0))

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
math.abs
ternary trunc

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/109.0.0.0 Safari/537.36

Browser/OS: Chrome 109 on Windows

View result in a separate tab

ternary trunc

226.2M/s

math.abs

5.0M/s

View exact numbers

Test name	Executions per second
✓ ternary trunc	226,229,648 Ops/sec
math.abs	5,033,727 Ops/sec

Autogenerated LLM Summary (model gpt-4o-mini, generated one year ago):

LLMs can make mistakes. Check important info.

In the provided benchmark setup from MeasureThat.net, we are evaluating the performance of different strategies for calculations involving a variable `hue`. The goal is to compare the execution speed of two distinct methods: one that utilizes `Math.abs()` and the other that employs a ternary truncation method.

### Test Cases Explained

1. **Test Case: `math.abs`**
   - **Benchmark Definition**: `x1 = 1 - Math.abs((hue / 60) % 2 - 1);`
   - **Description**: This approach calculates a transformed value based on the `hue`, which is first divided by 60, then takes the modulus with 2, and finally applies the `Math.abs()` function to compute its absolute difference from 1. The computation involves floating-point arithmetic and uses a built-in JavaScript function.
   - **Pros and Cons**:
     - **Pros**: 
       - `Math.abs()` is a straightforward and easy-to-understand function. 
       - The code is cleaner and can be easier for other developers to read and maintain.
     - **Cons**: 
       - The absolute calculation might add overhead due to the function call, potentially slowing down execution, especially if performance is critical.
  
2. **Test Case: `ternary trunc`**
   - **Benchmark Definition**: `x1 = (hue/60 - ((hue/60)|0));`
   - **Description**: This method breaks down the `hue` by performing a division, then uses bitwise OR with zero to truncate the decimal part, effectively yielding the integer part of the division. The result is then subtracted from the original value to get the fractional part.
   - **Pros and Cons**: 
     - **Pros**: 
       - Using bitwise operations is often faster than function calls in JavaScript, leading to potentially better performance for this specific calculation.
       - The calculation avoids the overhead of a function call, which can accumulate in tight loops or frequent calculations.
     - **Cons**: 
       - The syntax may be less intuitive to developers unfamiliar with bitwise operations, which might hinder readability and maintainability.
       - It might not handle negative numbers or certain edge cases as reliably as `Math.abs()`, depending on the context of its use.

### Benchmark Results

- The benchmark results indicate that the `ternary trunc` approach executed significantly more times per second (226,229,648.0) compared to the `math.abs` approach (5,033,727.0). This stark difference highlights the performance gain achieved through the use of bitwise operations.

### Additional Considerations

- **Special Features/Syntax**: The benchmark does not utilize any unique features or syntax specific to JavaScript beyond the basic arithmetic and bitwise operations. However, the use of bitwise OR (`|`) for truncation is a useful technique that some developers might not be familiar with.
  
- **Alternatives**: Other alternatives for achieving similar results could include:
  - Utilizing `Math.floor()` or `Math.trunc()` functions, which can provide ways to obtain the integer part of a number without directly using bitwise operations.
  - Exploring libraries such as `lodash` for managing complex number manipulations, though this would typically introduce additional overhead.

In summary, the benchmark presents two approaches with notable differences in performance and readability considerations, allowing engineers to choose based on their specific needs and coding style preferences.

strategy to count (version: 1)

faster find

Comparing performance of: `math.abs vs ternary trunc`

Created: one year ago by: Guest

Go to the latest result

math.abs

ternary trunc

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gpt-4o-mini, generated one year ago):

strategy to count (version: 1)

faster find

Comparing performance of: math.abs vs ternary trunc

Created: one year ago by: Guest

Go to the latest result

math.abs

ternary trunc

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gpt-4o-mini, generated one year ago):

Related benchmarks

Comparing performance of: `math.abs vs ternary trunc`