Benchmark: Math.max with nested slice vs iife tracking max (size comp)

Script Preparation code:

var numbers1000 = [...Array(1000)].map((_, i) => Math.floor(Math.random() * (i + 10)))
var numbers10000 = [...Array(10000)].map((_, i) => Math.floor(Math.random() * (i + 10)))

Tests:

Math.max(slice()) 1000
var result = numbers1000.map((v, i, a) => Math.max(v, ...a.slice(0, i)))
iife Math.max 1000
var result = ((prev) => numbers1000.map((v) => prev = Math.max(v, prev)))(-Infinity)
Math.max(slice()) 10000
var result = numbers10000.map((v, i, a) => Math.max(v, ...a.slice(0, i)))
iife Math.max 10000
var result = ((prev) => numbers10000.map((v) => prev = Math.max(v, prev)))(-Infinity)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Math.max(slice()) 1000
iife Math.max 1000
Math.max(slice()) 10000
iife Math.max 10000

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

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

LLMs can make mistakes. Check important info.

**Benchmark Overview**

MeasureThat.net is a website that allows users to create and run JavaScript microbenchmarks. The provided benchmark measures the performance of `Math.max` with different approaches: using a traditional loop (`slice()`), an immediately invoked function expression (IIFE) with accumulator, and varying array sizes.

**Test Cases**

The benchmark consists of four test cases:

1. **`Math.max(slice()) 1000`**: Measures the performance of `Math.max` with a traditional loop using `slice()`.
2. **`iife Math.max 1000`**: Measures the performance of `Math.max` using an IIFE with accumulator.
3. **`Math.max(slice()) 10000`**: Measures the performance of `Math.max` with a traditional loop using `slice()` for a larger array size.
4. **`iife Math.max 10000`**: Measures the performance of `Math.max` using an IIFE with accumulator for a larger array size.

**Approach Comparison**

The benchmark compares the performance of two approaches:

1. **Traditional Loop (`slice()`)**: Uses the spread operator (`...`) to extract a slice of the array, and then uses `Math.max` to compare elements.
2. **Immediately Invoked Function Expression (IIFE) with Accumulator**: Uses an IIFE to define a function that takes an accumulator as an argument. The function iterates over the array, comparing each element with the accumulator, and updates the accumulator using `prev = Math.max(v, prev)`.

**Pros and Cons of Each Approach**

1. **Traditional Loop (`slice()`)**:
	* Pros: Simple to understand and implement.
	* Cons: Can be slow due to the overhead of creating a new array slice.
2. **IIFE with Accumulator**:
	* Pros: Avoids the need to create a new array slice, reducing overhead.
	* Cons: Requires defining an IIFE function, which can add complexity.

**Library and Special Features**

None of the test cases use any external libraries. However, it's worth noting that the spread operator (`...`) is a modern JavaScript feature introduced in ECMAScript 2015 (ES6).

**Other Considerations**

* The benchmark uses Chrome 102 as the browser and Mac OS X 10.15.7 as the operating system.
* The test cases use arrays of different sizes to vary the performance impact.
* The benchmark measures executions per second, which provides a good indication of performance.

**Alternatives**

If you were to optimize this benchmark, you could consider:

1. Using a just-in-time (JIT) compiler or a JavaScript engine that optimizes loops.
2. Using a more efficient data structure, such as a sparse array or a heap.
3. Reducing the number of allocations by reusing existing arrays or using a streaming approach.

Keep in mind that these optimizations would depend on the specific use case and requirements of your application.

Related benchmarks:

Math.max with nested slice vs iife tracking max (size comp) (version: 0)

Comparing performance of: Math.max(slice()) 1000 vs iife Math.max 1000 vs Math.max(slice()) 10000 vs iife Math.max 10000

Created: 3 years ago by: Guest

Jump to the latest result

Math.max(slice()) 1000

iife Math.max 1000

Math.max(slice()) 10000

iife Math.max 10000

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):