Benchmark: Math.max() without spread vs reduce vs apply

Script Preparation code:

var values = new Array(5000);

for (let i = 0; i < values.length; ++i) {
    values[i] = i % 20;
}

Tests:

Math.max
return Math.max(values);
Reduce
return values.reduce((a, b) => Math.max(a, b), -Infinity);
Apply
function getMaxOfArray(numArray) { return Math.max.apply(null, numArray); } return getMaxOfArray(values);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Math.max
Reduce
Apply

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark definition and test cases.

**What is being tested?**

The benchmark tests three different ways to find the maximum value in an array:

1. `Math.max()`: using the built-in `max` function
2. `Array.prototype.reduce()` with a custom callback function: finding the maximum value by reducing the array to a single value.
3. `Function.apply(null, ...)`: using the `apply` method to call a function with an array of arguments.

**Options compared**

The benchmark compares the performance of these three approaches:

* `Math.max()`: a simple and efficient way to find the maximum value in an array.
* `Array.prototype.reduce()` with a custom callback function: a more complex approach that involves iterating over the array to find the maximum value.
* `Function.apply(null, ...)`: a dynamic approach that uses the `apply` method to call a function with an array of arguments.

**Pros and Cons**

Here are some pros and cons for each approach:

1. **Math.max()**:
	* Pros: simple, efficient, and widely supported.
	* Cons: may not be suitable for very large arrays or arrays with non-numeric values.
2. **Array.prototype.reduce()` with a custom callback function:
	* Pros: can be used to perform more complex operations on the array.
	* Cons: may have performance overhead due to the iteration and callback function invocation.
3. **Function.apply(null, ...)**:
	* Pros: dynamic and flexible approach that can handle arrays of different lengths and data types.
	* Cons: may have higher performance overhead due to the `apply` method call.

**Library**

None of these approaches rely on external libraries.

**Special JS features or syntax**

The benchmark uses some special JavaScript features:

1. **Function.apply()**: the `apply` method is used to call a function with an array of arguments.
2. **Array.prototype.reduce()**: this method is used to reduce the array to a single value by iterating over its elements.

**Other considerations**

When choosing between these approaches, consider the specific requirements of your use case:

* If you need a simple and efficient way to find the maximum value in an array, `Math.max()` is likely the best choice.
* If you need to perform more complex operations on the array or handle non-numeric values, `Array.prototype.reduce()` with a custom callback function may be a better option.
* If you need a dynamic approach that can handle arrays of different lengths and data types, `Function.apply(null, ...)` may be suitable.

**Other alternatives**

Some other alternatives to these approaches include:

1. Using the `Math.max()` function with multiple arguments (e.g., `Math.max(...values)`).
2. Using a library like Lodash or Ramda, which provide more functional programming-style functions for working with arrays.
3. Implementing your own custom algorithm using loops and conditional statements.

I hope this explanation helps! Let me know if you have any further questions.

Latest run results:

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

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/17.6 Safari/605.1.15

Browser/OS: Safari 17 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
Math.max	16023.4 Ops/sec
Reduce	1698.1 Ops/sec
Apply	65571.8 Ops/sec

Related benchmarks:

Math.max() without spread vs reduce vs apply (version: 0)

Comparing performance of: Math.max vs Reduce vs Apply

Created: 3 months ago by: Guest

Jump to the latest result

Math.max

Reduce

Apply

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):