Benchmark: SPlICE + UNSHIFT vs SORT (10000 items) with Filter

Script Preparation code:

var arr = [...Array(10000)].map((_,i) => i)

Tests:

SPLICE + UNSHIFT: array 10000 items; itemIndex - 10000
let newArr = [...arr] const item = 9999 const filteredItem = newArr.filter((x) => x === 3) const itemIndex = newArr.findIndex((x) => x === filteredItem) console.log('SPLICE + UNSHIFT [0] before', newArr[0]) console.log('SPLICE + UNSHIFT length before', newArr.length) newArr.splice(itemIndex, 1) newArr.unshift(filteredItem) console.log('SPLICE + UNSHIFT [0] after', newArr[0]) console.log('SPLICE + UNSHIFT length after', newArr.length)
SORT: array 10000 items; itemIndex - 10000
let newArr = [...arr] const item = 9999 const itemIndex = newArr.findIndex((x) => x === item) console.log('SORT [0] before', newArr[0]) console.log('SORT length before', newArr.length) newArr = newArr.sort((a, b) => { if (a === item) { return -1 } if (b === item) { return 1 } return 0 }) console.log('SORT [0] after', newArr[0]) console.log('SORT length after', newArr.length)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
SPLICE + UNSHIFT: array 10000 items; itemIndex - 10000
SORT: array 10000 items; itemIndex - 10000

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

Let's dive into the explanation of the provided benchmark.

**Benchmark Definition**

The provided JSON represents a JavaScript microbenchmark, specifically designed to compare two approaches for finding and manipulating an element in an array: using `splice`/`unshift` or sorting the entire array.

**Options being compared**

Two options are being compared:

1. **SPLICE + UNSHIFT**: This approach uses the `splice` method to remove the element at a specific index (`itemIndex`) and then inserts the target element at the beginning of the array using `unshift`.
2. **SORT**: This approach sorts the entire array in ascending order, finds the index of the target element (`itemIndex`), and then removes it.

**Pros and Cons**

**SPLICE + UNSHIFT**

Pros:

* Fast, as it only modifies a small portion of the array.
* Efficient use of memory, as no new arrays are created.

Cons:

* May cause unexpected behavior if the array is modified concurrently or if the `itemIndex` value changes unexpectedly.
* Requires additional code to handle edge cases (e.g., finding the index of an element that doesn't exist in the array).

**SORT**

Pros:

* Simple and straightforward approach, as it only requires sorting the entire array once.
* Handles edge cases elegantly, as the sorted array provides a deterministic order.

Cons:

* O(n log n) time complexity, which can be slower for large arrays.
* Requires additional memory to store the temporary sorted array.

**Other considerations**

* Both approaches assume that the target element (`item`) is unique in the array. If there are multiple occurrences of the same value, this may affect performance and accuracy.
* The `findIndex` method used in the SORT approach can be optimized for better performance on certain browsers or hardware configurations.

**Library usage**

None of the provided benchmark definitions use any external libraries. However, it's worth noting that modern JavaScript engines often rely on internal libraries and optimizations to improve performance.

**Special JS feature/syntax**

The benchmark definition uses a few features specific to JavaScript:

* The `let` keyword for variable declarations.
* Arrow functions (`(x) => x`) for concise function definitions.
* The `const` keyword for constant variables (in this case, `itemIndex` and `filteredItem`).

These features are widely supported in modern JavaScript engines and don't pose any issues with compatibility.

**Alternatives**

Other approaches to find an element in an array include:

1. **Array.prototype.indexOf()**: Similar to `findIndex`, but returns -1 if the element is not found.
2. **Binary search**: A more efficient approach for large arrays, but requires sorting the array first (which can be slow).
3. **Hash tables or maps**: Data structures that store elements with unique keys, allowing for fast lookup and insertion.

These alternatives have varying trade-offs in terms of performance, memory usage, and complexity.

Latest run results:

Run details: (Test run date: 5 months ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/126.0.0.0 Safari/537.36

Browser/OS: Chrome 126 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
SPLICE + UNSHIFT: array 10000 items; itemIndex - 10000	18200.6 Ops/sec
SORT: array 10000 items; itemIndex - 10000	6506.7 Ops/sec

Related benchmarks:

SPlICE + UNSHIFT vs SORT (10000 items) with Filter (version: 0)

Comparing performance of: SPLICE + UNSHIFT: array 10000 items; itemIndex - 10000 vs SORT: array 10000 items; itemIndex - 10000

Created: 5 months ago by: Guest

Jump to the latest result

SPLICE + UNSHIFT: array 10000 items; itemIndex - 10000

SORT: array 10000 items; itemIndex - 10000

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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