Benchmark: for loop array caching with mutations II

Script Preparation code:

var arr = Array.from({length: 10000}, (_, i) => i);

Tests:

mutate without length caching
for (let i = 0; i < arr.length; i++) { arr[i] = arr[i] % 7; }
mutate with length caching
for (let i = 0, l = arr.length; i < l; i++) { arr[i] = arr[i] % 7; }
separate array without length caching
const arr1 = []; for (let i = 0; i < arr.length; i++) { arr1[i] = arr[i] % 7; } arr = arr1;
separate array with length caching
const arr1 = []; for (let i = 0, l = arr.length; i < l; i++) { arr1[i] = arr[i] % 7; } arr = arr1;

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
mutate without length caching
mutate with length caching
separate array without length caching
separate array with length caching

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 4 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/87.0.4280.66 Safari/537.36

Browser/OS: Chrome 87 on Windows

View result in a separate tab

Test name	Executions per second
mutate without length caching	189.0 Ops/sec
mutate with length caching	270.7 Ops/sec
separate array without length caching	254.4 Ops/sec
separate array with length caching	495.7 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down what's being tested in the provided benchmark.

**Overview**

The benchmark compares different approaches to iterating over an array and modifying its elements. The test cases are designed to measure the performance differences between various methods, allowing users to compare and optimize their own code.

**Benchmarked options**

There are four test cases:

1. **Mutate without length caching**: This approach iterates over the entire array using a traditional `for` loop and assigns the new value directly to each element (`arr[i] = arr[i] % 7;`).
2. **Mutate with length caching**: In this approach, the iteration variable `l` is cached before the loop starts, allowing the loop to start from an offset without recalculating it on each iteration.
3. **Separate array without length caching**: This test creates a new array (`arr1`) and copies elements from the original array into it using another traditional `for` loop.
4. **Separate array with length caching**: Similar to option 2, this approach caches the length of the array before the loop starts.

**Pros and cons**

Here's a brief summary of each approach:

* **Mutate without length caching**: Pros: simple, easy to understand. Cons: potentially slower due to repeated array lookups.
* **Mutate with length caching**: Pros: can be faster since the iteration variable is cached. Cons: may require more complex loop setup and understanding of iteration variables.
* **Separate array without length caching**: Pros: avoids modifying the original array, which can be beneficial for code organization and maintainability. Cons: potentially slower due to repeated array copying.
* **Separate array with length caching**: Similar pros and cons as option 2.

**Library usage**

None of the test cases use any external libraries or frameworks that require special consideration.

**Special JS features or syntax**

There are no specific JavaScript features or syntaxes being tested in this benchmark. The focus is on comparing different iteration approaches, which is a fundamental aspect of programming.

**Other alternatives**

If you're interested in exploring alternative approaches to iterating over arrays, here are some additional options:

* Using `forEach()`, `map()`, and `reduce()` methods, which can be more concise but may have performance implications depending on the specific use case.
* Leveraging modern JavaScript features like `async/await` or `generators` for more efficient iteration, especially in certain scenarios.
* Considering alternative data structures, such as linked lists or arrays with built-in caching capabilities, if speed and memory efficiency are critical.

Keep in mind that these alternatives might not be directly comparable to the benchmarked options, as they often involve different trade-offs between performance, code readability, and maintainability.

Related benchmarks:

for loop array caching with mutations II (version: 0)

Comparing performance of: mutate without length caching vs mutate with length caching vs separate array without length caching vs separate array with length caching

Created: 4 years ago by: Guest

Jump to the latest result

mutate without length caching

mutate with length caching

separate array without length caching

separate array with length caching

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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