Benchmark: edit map vs slice no index end

Script Preparation code:

window.arr = new Array(2000).fill({value: 'old'});
arr[1999] = {value: 'toReplace'};

Tests:

map
const newArr = arr.map((item) => item.value === 'toReplace' ? {value: 'new'} : item);
slice
const editIndex = arr.findIndex(item => item.value === 'toReplace'); const newArr = [ ...arr.slice(0, editIndex), {value: 'new'}, ...arr.slice(editIndex + 1), ];

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
map
slice

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 26 days ago):

LLMs can make mistakes. Check important info.

Let's break down the benchmark definition and test cases.

**What is being tested?**

The benchmark measures which approach is faster when replacing an item in an array:

1. Using `Array.prototype.map()` to create a new array with the replaced value.
2. Using `Array.prototype.slice()` to extract parts of the original array, replace the target element, and concatenate the result.

**Options being compared:**

The two options being compared are:

1. **`map()`**: Creates a new array with modified elements. It stops iterating as soon as it encounters an element that matches the callback function's return value.
2. **`slice()` + `concat()`**: Extracts parts of the original array, replaces the target element, and concatenates the result.

**Pros and Cons:**

1. **`map()`**:
	* Pros:
		+ More concise and readable code
		+ Stop iterating as soon as possible
	* Cons:
		+ Creates a new array, which can be memory-intensive for large datasets
		+ May not be suitable for large arrays due to performance concerns
2. **`slice()` + `concat()`**:
	* Pros:
		+ Does not create a new array, reducing memory usage
		+ Can be more efficient for large arrays since it avoids creating a new array
	* Cons:
		+ More verbose and less readable code
		+ May lead to unnecessary copies of elements when concatenating

**Other considerations:**

When choosing between `map()` and `slice()` + `concat()`, consider the trade-off between memory usage and performance. If you're working with large datasets, using `map()` might be more suitable for readability, but it may consume more memory. On the other hand, using `slice()` + `concat()` can reduce memory usage but at the cost of verbosity.

**Library or special JavaScript feature used:**

Neither option explicitly uses a library. However, `map()` and `slice()` are part of the ECMAScript standard, which means they're supported by most modern browsers without any additional libraries.

**Other alternatives:**

If you're looking for alternative approaches, consider:

1. **`filter()`**: While not ideal for replacing an element, `filter()` can be used to create a new array with modified elements.
2. **Using `splice()` directly**: Instead of using `map()` or `slice()` + `concat()`, you can use `splice()` to replace an element in place, but this approach modifies the original array and might not be suitable for all scenarios.

Keep in mind that these alternatives may have their own trade-offs and limitations.

Latest run results:

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

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_14_0) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/79.0.3945.79 Safari/537.36

Browser/OS: Chrome 79 on Mac OS X 10.14.0

View result in a separate tab

Test name	Executions per second
map	96788.4 Ops/sec
slice	96120.7 Ops/sec

Related benchmarks:

edit map vs slice no index end (version: 0)

Which is faster?

Comparing performance of: map vs slice

Created: 4 years ago by: Guest

Jump to the latest result

map

slice

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 26 days ago):