Benchmark: array vs set index deletion

Tests:

array
const arr = new Array(10000).fill(Math.floor(Math.random() * 1000)); const s = new Set(arr); for (let i = 0; i < arr.length; i++) { const idx = arr.indexOf(i); if (i !== -1) { arr.splice(idx, 1); } }
set
const arr = new Array(10000).fill(Math.floor(Math.random() * 1000)); const s = new Set(arr); for (let i = 0; i < arr.length; i++) { if (s.has(i)) { s.delete(i); } }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
array
set

Fastest: N/A

Slowest: N/A

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

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**Benchmark Overview**

The provided JSON represents a benchmark test on MeasureThat.net, which compares the performance of two approaches for removing elements from an array and a Set data structure in JavaScript.

**Test Cases**

There are two individual test cases:

1. **Array Approach**: This test case creates an array of 10,000 random integers and a new Set instance containing these integers. It then iterates through the array, finds the index of each element using `indexOf()`, and removes the element from the array using `splice()` if the index is valid.
2. **Set Approach**: Similar to the Array approach, this test case creates an array of 10,000 random integers and a new Set instance containing these integers. However, it uses the `has()` method to check if each element exists in the Set before deleting it using `delete()`.

**Comparison**

The benchmark compares the performance of these two approaches under various browsers (Chrome 88) on different devices (Desktop) and operating systems (Windows).

**Options Compared**

Two options are compared:

1. **Array Approach**: Uses the `splice()` method to remove elements from the array.
2. **Set Approach**: Uses the `delete()` method to remove elements from the Set.

**Pros and Cons of Each Approach**

*   **Array Approach:**
    *   Pros:
        *   More familiar syntax for developers (using `indexOf()` and `splice()`)
        *   Less memory overhead compared to Sets
    *   Cons:
        *   Slower lookup times due to the linear search in `indexOf()`
        *   May lead to performance issues if the array is very large or frequently updated
*   **Set Approach:**
    *   Pros:
        *   Faster lookup times due to the O(1) time complexity of `has()` and `delete()`
        *   Less memory overhead compared to arrays (since Sets store unique values)
    *   Cons:
        *   Unfamiliar syntax for developers (using `has()` and `delete()`)
        *   May lead to higher memory usage if the Set grows large

**Library Used**

The Set data structure is a built-in JavaScript data type that stores unique values. It provides fast lookup, insertion, and deletion operations.

**Special JS Features or Syntax**

Neither of these approaches uses special JS features or syntax. They rely on standard JavaScript methods and syntax.

**Other Considerations**

When choosing between the Array approach and the Set approach, consider the following:

*   **Performance**: If speed is critical, the Set approach might be a better choice due to its faster lookup times.
*   **Memory Efficiency**: If memory usage is a concern, both approaches can be efficient since they use either arrays or sets, which have relatively low overhead compared to other data structures.

**Alternatives**

Other alternatives for removing elements from an array or set include:

*   Using `filter()` or `map()` to create a new array with the desired elements.
*   Using `reduce()` to iterate through the array and accumulate the results in a new array.
*   Using specialized libraries or frameworks that provide optimized data structure operations (e.g., MongoDB for large-scale data storage).

Keep in mind that each alternative has its own trade-offs, such as additional memory usage or computational complexity.

Related benchmarks:

array vs set index deletion (version: 0)

Comparing performance of: array vs set

Created: 5 years ago by: Guest

Jump to the latest result

array

set

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

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