Benchmark: splice VS shift VS splice bulk

Script Preparation code:

var list = [];
for (var i = 0; i < 1000 * 1000; i++) {
  list.push(i);
}

Tests:

splice
list.push('splice'); list.splice(0, 1);
shift
list.push('splice'); list.shift();
splice bulk
list.push('splice'); list.splice(0, 50);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
splice
shift
splice bulk

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/109.0.0.0 Safari/537.36

Browser/OS: Chrome 109 on Windows

View result in a separate tab

Test name	Executions per second
splice	2114.1 Ops/sec
shift	1136.0 Ops/sec
splice bulk	7644.8 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark and its test cases.

**Benchmark Definition**

The benchmark definition is a JSON object that represents the specific test case being measured. In this case, there are three test cases:

1. `splice VS shift VS splice bulk`: This is the main benchmark definition, which compares the performance of three different approaches:
	* `splice`: Replacing an element at a specified index using the `splice()` method.
	* `shift`: Removing and returning the first element from the end of the array using the `shift()` method.
	* `splice bulk`: Replacing multiple elements at once using the `splice()` method with a large number of arguments.
2. The benchmark description explains why these three approaches are being compared: `splice` and `shift` win because they mutate the list, while `slice` (not explicitly mentioned in this case) would create a copy of the list, resulting in 7.5x slower performance.

**Test Cases**

The individual test cases are:

1. `list.push('splice');\nlist.splice(0, 1);`: This test case pushes an element onto the array using `push()` and then removes the first element from the array using `splice()`.
2. `list.push('splice');\nlist.shift();`: This test case pushes an element onto the array using `push()` and then removes and returns the last element from the array using `shift()`.
3. `list.push('splice');\nlist.splice(0, 50);`: This test case pushes an element onto the array using `push()` and then replaces multiple elements at once by removing 50 elements from the beginning of the array using `splice()`.

**Library**

There is no explicit library mentioned in this benchmark. However, it's likely that the `Array.prototype` methods (e.g., `push()`, `splice()`) are part of the built-in JavaScript standard library.

**Special JS Features or Syntax**

There doesn't appear to be any special JavaScript features or syntax used in these test cases.

**Alternatives**

Some alternative approaches for modifying arrays could include:

1. Using a custom implementation with a loop and indexing.
2. Utilizing a library like Lodash, which provides functions for array manipulation (e.g., `lodash.cloneDeep()`).
3. Employing a more functional programming approach using methods like `filter()`, `map()`, or `reduce()`.

Keep in mind that these alternatives might introduce additional overhead or complexity compared to the built-in JavaScript array methods used in this benchmark.

**Pros and Cons of Different Approaches**

Here's a brief summary of the pros and cons for each approach:

1. **Built-in JavaScript array methods (`push()`, `splice()`, `shift()`)**:
	* Pros: Fast, optimized, and widely supported.
	* Cons: May not be suitable for large arrays or complex data structures.
2. **Custom implementation with a loop and indexing**:
	* Pros: Can handle large arrays or complex data structures.
	* Cons: Typically slower than built-in methods, as it involves manual iteration and calculations.
3. **Lodash library**:
	* Pros: Provides a convenient, modular way to manipulate arrays without worrying about implementation details.
	* Cons: Introduces additional overhead due to the library itself and potential performance impact.

Ultimately, the choice of approach depends on the specific use case, performance requirements, and personal preference.

Related benchmarks:

splice VS shift VS splice bulk (version: 0)

100k list splice and shift win, they mutate list slice loose, it creates a copy of list 7.5x slower

Comparing performance of: splice vs shift vs splice bulk

Created: 5 years ago by: Guest

Jump to the latest result

splice

shift

splice bulk

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):