Benchmark: Math.max.apply vs Math.max in Reduce

Script Preparation code:

var arr = [];

for (var i = 0; i < 100; i++){
  arr.push({x: i});
}

Tests:

Math.max
Math.max.apply(arr.slice(0, 5).map(function(item){return item.x;}));
Reduce
arr.slice(0, 5).reduce(function(accu, next){ return Math.max(accu, next.x);}, 0);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Math.max
Reduce

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

Let's dive into explaining the benchmark.

**What is being tested?**

MeasureThat.net is testing two approaches for finding the maximum value in an array: `Math.max.apply()` and `Array.prototype.reduce()`. The test case creates an array of objects with increasing `x` values, simulating a scenario where you need to find the maximum value in the data.

**Options compared**

The benchmark compares the performance of two methods:

1. **`Math.max.apply()`**: This method applies the `Math.max()` function to the entire array at once.
2. **`Array.prototype.reduce()`**: This method accumulates values from an array and applies a callback function to each value, effectively finding the maximum value in the process.

**Pros and Cons**

* **`Math.max.apply()`**:
	+ Pros: Simple and straightforward, no need for additional library or function creation.
	+ Cons: May not be optimized for large arrays, as it has to apply `Math.max()` to every element individually.
* **`Array.prototype.reduce()`**:
	+ Pros: Optimized for large arrays, as it can accumulate values in a single pass. It also allows for more flexible processing of the data.
	+ Cons: Requires a callback function to specify how to combine elements, which may add complexity.

**Library and its purpose**

The `Array.prototype.reduce()` method is part of the JavaScript standard library, making it accessible without any additional imports or libraries.

**Special JS feature or syntax**

There are no special features or syntax used in this benchmark. It's a straightforward test case that relies on the built-in methods and array operations.

**Other alternatives**

If you wanted to implement this comparison yourself, here are alternative approaches:

1. Using a `for` loop with an index variable: This approach would iterate over each element individually, similar to `Math.max.apply()`.
2. Implementing a custom `max()` function using recursion or iteration: This approach would allow for more flexibility in processing the data, but might be less efficient than `Array.prototype.reduce()`.
3. Using a different array method, such as `map()` and `then()` with a callback function: This approach would involve more complex operations, potentially slower performance.

For this specific benchmark, using `Array.prototype.reduce()` is likely to be the most efficient approach due to its optimized implementation for large arrays.

Related benchmarks:

Math.max.apply vs Math.max in Reduce (version: 2)

Comparing performance of: Math.max vs Reduce

Created: 6 years ago by: Registered User

Jump to the latest result

Math.max

Reduce

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):