Benchmark: Slice + reverse vs manual picking array indexes

Script Preparation code:

var input = [1,2,3,4,5,6,7,8,9,10,11,12,13];
var inputLength = input.length;

Tests:

Manual pick
const result = [ input[inputLength - 1], input[inputLength - 2], input[inputLength - 3], input[inputLength - 4], input[inputLength - 5], input[inputLength - 6], input[inputLength - 7]]
slice + reverse
input.slice(inputLength-7, inputLength).reverse()

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Manual pick
slice + reverse

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 24 days ago):

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark and explain what is tested, compared, and other considerations.

**Benchmark Definition**

The benchmark defines two test cases:

1. "Slice + reverse vs manual picking array indexes"
2. "Manual pick"

Both test cases use the same input data, which is an array of 13 integers.

**What is being tested?**

In both test cases, the goal is to retrieve a subset of elements from the input array and return them as a new array. The difference lies in how this is achieved:

* "Manual pick" uses manual indexing to access the desired elements: `input[inputLength - 1], input[inputLength - 2], ...`
* "Slice + reverse" uses the `slice()` method to extract a subset of the array and then reverses the order using the `reverse()` method.

**Options compared**

The two approaches compare:

* Performance of manual indexing vs using built-in methods (`slice()` and `reverse()`)
* Efficiency of reversing an array vs accessing elements in reverse order

**Pros and cons of each approach:**

**Manual pick:**

Pros:

* No additional memory allocations or function calls
* Can be optimized for small arrays with tight loop bounds

Cons:

* Requires explicit indexing, which can lead to slower performance due to branch prediction penalties
* More prone to errors if the array length changes

**Slice + reverse:**

Pros:

* Efficient and concise way to extract a subset of an array
* Reversing an array is often faster than accessing elements in reverse order using manual indexing

Cons:

* Requires additional memory allocations (for the slice object)
* Can be slower for very large arrays due to overhead of `slice()` and `reverse()`

**Other considerations:**

* The use of `inputLength` as a variable instead of hardcoding it may affect performance, especially if the array length is frequently changing.
* The `input` array is defined in both test cases, which ensures consistency between the two approaches.

**Library/Language features used:**

* JavaScript (ECMAScript)

There are no special JavaScript features or syntaxes mentioned in this benchmark. However, it's worth noting that ECMAScript 2015+ introduced some features like `let` and `const` for variable declarations, which may not be compatible with older browsers.

**Alternatives:**

For this specific use case, other alternatives to the "Slice + reverse" approach could include:

* Using a library like Lodash or Ramda, which provide optimized array functions
* Implementing a custom loop using bitwise operations or bit manipulation
* Utilizing WebAssembly (WASM) for performance-critical code

Keep in mind that these alternatives may not be as straightforward to implement and might require more significant changes to the codebase.

Latest run results:

Run details: (Test run date: 2 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/96.0.4664.110 Safari/537.36

Browser/OS: Chrome 96 on Windows

View result in a separate tab

Test name	Executions per second
Manual pick	1260586.0 Ops/sec
slice + reverse	5363041.5 Ops/sec

Related benchmarks:

Slice + reverse vs manual picking array indexes (version: 0)

Comparing performance of: Manual pick vs slice + reverse

Created: 2 years ago by: Guest

Jump to the latest result

Manual pick

slice + reverse

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 24 days ago):