Benchmark: Include vs Binary search in sorted array vs Map.has() vs Object[] (25 elements)

Script Preparation code:

var array = [];
var map = new Map();
var obj = {};

for (var i = 0; i < 25; i++){
  array.push(Math.floor(Math.random()* 100));
  map.set(i,true);
  obj[i]=true;
}
var sorted = array.sort()

function binaryIndexOf(searchElement) {

 
    var minIndex = 0;
    var maxIndex = this.length - 1;
    var currentIndex;
    var currentElement;
 
    while (minIndex <= maxIndex) {
        currentIndex = (minIndex + maxIndex) / 2 | 0;
        currentElement = this[currentIndex];
 
        if (currentElement < searchElement) {
            minIndex = currentIndex + 1;
        }
        else if (currentElement > searchElement) {
            maxIndex = currentIndex - 1;
        }
        else {
            return currentIndex;
        }
    }
 
    return -1;
}

Tests:

Includes
sorted.includes(5)
binary
binaryIndexOf.call(sorted, 5)
Map.has()
map.has(5);
Obj[]
obj[5]

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Includes
binary
Map.has()
Obj[]

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/103.0.0.0 Safari/537.36

Browser/OS: Chrome 103 on Linux

View result in a separate tab

Test name	Executions per second
Includes	8918908.0 Ops/sec
binary	4040358.5 Ops/sec
Map.has()	7991231.0 Ops/sec
Obj[]	8964382.0 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the provided JSON and explain what is tested, the options compared, their pros and cons, and other considerations.

**Benchmark Definition:**
The benchmark measures the performance of different ways to search for an element in a sorted array:

1. **Includes**: Using the `includes()` method on the sorted array.
2. **Binary search**: Implementing a binary search algorithm within the array itself.
3. **Map.has()**: Using the `has()` method on a Map instance, where each key is an index into the original array.
4. **Obj[]**: Directly accessing an element of an Object by its key (index).

**Options Compared:**

*   Includes: A built-in method for checking if an element is present in an array.
*   Binary search: An algorithm that finds the position of a target value within a sorted array.
*   Map.has(): A method for checking if a key exists in a Map instance. In this case, each key corresponds to an index into the original array.
*   Obj[]: Directly accessing an element of an Object by its key (index).

**Pros and Cons:**

1.  **Includes**: Pros:
    *   Easy to implement and understand
    *   Built-in method for arrays
    *   Fast, as it only checks if the element is present in the array
    *   Cons:
    *   May not be optimized for performance, especially for large arrays
2.  **Binary search**: Pros:
    *   Efficient for finding specific elements within a sorted array
    *   Can be implemented quickly and accurately
    *   Cons:
    *   More complex to implement than `includes()`
    *   Requires the array to be sorted initially, which may not always be the case
3.  **Map.has()**: Pros:
    *   Fast and efficient for looking up elements in a Map instance
    *   Can be used with any type of data (not limited to numbers or strings)
    *   Cons:
    *   May require more memory, as it stores each key-value pair in the Map
    *   Not applicable to an array without a corresponding Map instance
4.  **Obj[]**: Pros:
    *   Direct access to elements by index can be convenient and fast for simple cases
    *   Cons:
    *   May not be efficient or scalable for large arrays, as it relies on direct indexing

**Library Usage:**
In this benchmark, the following libraries/libraries-like- constructs are used:

*   **Array.prototype.includes()**: A built-in method for checking if an element is present in an array.
*   **Map**: Used to create a Map instance, where each key corresponds to an index into the original array.

**Special JavaScript Features/Syntax:**
The benchmark utilizes several advanced JavaScript features, including:

*   **Arrow functions**: Used within `binaryIndexOf()` for concise and readable code
*   **Template literals**: Not explicitly used in this example, but could be useful in other scenarios

Overall, this benchmark provides a comprehensive comparison of different methods for searching an element in a sorted array, allowing users to understand the trade-offs between simplicity, efficiency, and scalability.

**Other Alternatives:**

*   For finding specific elements within a large array, you may want to consider using data structures like Binary Search Trees (BSTs) or Hash Tables.
*   If working with JSON data, you could also explore methods for efficiently searching and manipulating JSON arrays, such as using the `JSON.parse()` method with the `Array.prototype.indexOf()` function.

In summary, this benchmark offers a straightforward comparison of various methods for searching an element in a sorted array, providing valuable insights into performance, efficiency, and scalability considerations.

Related benchmarks:

Include vs Binary search in sorted array vs Map.has() vs Object[] (25 elements) (version: 0)

Comparing performance of: Includes vs binary vs Map.has() vs Obj[]

Created: one year ago by: Guest

Jump to the latest result

Includes

binary

Map.has()

Obj[]

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):