Benchmark: Math.max with nested slice vs iife tracking max.

Script Preparation code:

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

Tests:

Math.max(slice());
var result = numbers.map((v, i, a) => Math.max(v, ...a.slice(0, i)))
iife Math.max
var result = ((prev) => numbers.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());
iife Math.max

Fastest: N/A

Slowest: N/A

Latest run results:

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

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Let's break down the provided benchmark definition and explain what is being tested.

**Benchmark Definition**

The benchmark measures the performance of two different approaches to find the maximum value in an array:

1. **Math.max with nested slice**: This approach uses the `map()` method to iterate over the array, and for each element, it extracts a slice of the array up to the current index using `a.slice(0, i)`. It then finds the maximum value between the current element and this slice.
2. **IIFE (Immediately Invoked Function Expression) with Math.max**: This approach uses an IIFE to create a closure that keeps track of the maximum value seen so far. The function takes an initial value of `-Infinity` and maps over the array, updating the maximum value on each iteration.

**Options Compared**

The benchmark compares two options:

1. **Math.max with nested slice**: This is the traditional approach to finding the maximum value in an array.
2. **IIFE with Math.max**: This approach uses a closure to keep track of the maximum value seen so far, which can be more efficient for large arrays.

**Pros and Cons**

* **Math.max with nested slice**:
	+ Pros: Simple and easy to understand.
	+ Cons: Can lead to unnecessary array slicing, which can create temporary objects that need to be garbage collected.
* **IIFE with Math.max**:
	+ Pros: Can avoid creating temporary arrays and objects, making it more efficient for large datasets.
	+ Cons: Can be less intuitive to read and understand, especially for developers not familiar with IIFEs.

**Other Considerations**

* The benchmark does not account for other factors that might affect performance, such as array size, data distribution, or hardware characteristics.
* The `numbers` array is created with a random value between 0 and `(i + 10)`, which means the values will increase incrementally. This may not be representative of all use cases where `Math.max` is used.

**Library Usage**

There is no explicit library usage mentioned in the benchmark definition. However, it's worth noting that `Array.prototype.map()` is a built-in method for arrays, so there's no external library dependency.

**Special JS Feature/Syntax**

There are two special features/syntax:

1. **IIFE**: The `((prev) => numbers.map((v) => prev = Math.max(v, prev)))(-Infinity)` expression is an IIFE that creates a closure to keep track of the maximum value seen so far.
2. **Template literals**: The `"var result = numbers.map((v, i, a) => Math.max(v, ...a.slice(0, i)))"` line uses template literals (the `...` syntax) to create an interpolated string.

**Alternatives**

If you're looking for alternative approaches to find the maximum value in an array, some options might include:

1. **Linear search**: Iterating over the array one element at a time until finding the maximum value.
2. **Binary search**: Using binary search algorithms like quickselect or partition sort to find the maximum value efficiently.
3. **External libraries**: Utilizing external libraries like `lodash` or `underscore` that provide optimized implementations of array methods.

Keep in mind that these alternatives may have different performance characteristics and trade-offs compared to the benchmarked approaches.

Related benchmarks:

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

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

Created: 3 years ago by: Guest

Jump to the latest result

Math.max(slice());

iife Math.max

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):