Benchmark: Xor Bench - MeasureThat.net

HTML Preparation code:


<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.5/lodash.min.js'></script>

Script Preparation code:

var arr = [1, 2, 3];

var xor1 = (value, array) => {
    return [...new Set(array.reduce((prevValue, currValue) => {
        if (currValue !== value) {
            prevValue.push(currValue);
        }
        prevValue.push(value);
        return prevValue;
    }, []))];
}

var xor2 = (value, arr) => {
    return arr.includes(value) ? arr.filter(item => item !== value) : arr.concat(value);
}

var xor3 = (value, array) => {
    let isExist = false;
    const result = [];

    for (const item of array) {
        if (item !== value) {
            result.push(item);
        } else {
            isExist = true;
        }
    }

    return [...new Set(isExist ? result : result.concat(value))];
}

Tests:

xor reduce
xor1(4, arr)
xor filter
xor2(4, arr)
xor for
xor3(4, arr)
lodash
_.xor(arr, [4])

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
xor reduce
xor filter
xor for
lodash

Fastest: N/A

Slowest: N/A

Latest run results:

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

LLMs can make mistakes. Check important info.

I'll break down the provided benchmark definition, script preparation code, and individual test cases to explain what's being tested and the pros/cons of each approach.

**Benchmark Definition**

The benchmark tests three different ways to find unique elements in an array:

1. `xor1` function: This function takes two arguments, `value` and `array`. It returns a new array containing only the elements that are not equal to `value`.
2. `xor2` function: This function also takes two arguments, `value` and `arr`. It checks if `value` is in `arr` using the `includes()` method. If it is, it filters out all occurrences of `value` from `arr`, otherwise it concatenates `value` to `arr`.
3. A third implementation using a simple loop (`xor3`) that iterates over `array` and pushes elements not equal to `value` into a result array.

**Script Preparation Code**

The script preparation code includes:

* An array `arr` with initial values `[1, 2, 3]`
* Three function definitions:
	+ `xor1`: The first implementation
	+ `xor2`: The second implementation
	+ `xor3`: The third implementation

**Individual Test Cases**

Each test case is a separate benchmark that tests one of the three implementations:

1. `xor filter` (Test Case 1): This test case uses the `xor2` function with the initial array `arr` and the value `4`.
2. `xor reduce` (Test Case 2): This test case uses the `xor1` function with the initial array `arr` and the value `4`.
3. `xor for` (Test Case 3): This test case uses the `xor3` function with the initial array `arr` and the value `4`.
4. Lodash-based benchmark (Test Case 4): This test case uses the `_xor` function from the Lodash library, which is imported at the top of the script preparation code.

**Pros and Cons**

Here's a brief summary of each approach:

1. **xor1**: Pros:
	* Simple and efficient
	* Uses built-in array methods (`reduce`)
Cons:
	* May not be suitable for large datasets due to its reliance on `reduce`
2. **xor2**: Pros:
	+ Fast and efficient, especially when using modern JavaScript engines that optimize `includes()`
Cons:
	+ More complex than `xor1` due to the use of `includes()` and `filter()`
3. **xor3**: Pros:
	+ Simple and easy to understand
	+ Does not rely on any built-in array methods or libraries
Cons:
	+ Less efficient than `xor2` due to its simple loop implementation

The Lodash-based benchmark provides an alternative implementation that leverages the `_xor` function, which is likely implemented in C++ for performance reasons. This approach may be faster than the other two implementations but requires importing a library.

**Other Alternatives**

Other possible approaches could include:

1. Using `Set` data structure: Creating a set from the initial array and then adding elements to it using the `add()` method would provide an efficient solution.
2. Implementing a custom hash function: A well-designed hash function could be used to efficiently find unique elements in the array.

Keep in mind that these alternatives might not be as simple or elegant as the existing implementations, but they can provide alternative solutions for specific use cases.

Related benchmarks:

Xor Bench (version: 0)

Comparing performance of: xor reduce vs xor filter vs xor for vs lodash

Created: 3 years ago by: Guest

Jump to the latest result

xor reduce

xor filter

xor for

lodash

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):