Benchmark: sgdfgdgd - MeasureThat.net

Script Preparation code:

function intersect(arrays) {
    const response = arrays.length === 1 ? [...arrays[0]] : [];
    if (arrays.length > 1) {
        const nOthers = arrays.length - 1;
        let nShortest = arrays[0].length;
        let shortest = 0;
        for (let i = 0; i <= nOthers; i++) {
            const n = arrays[i].length;
            if (n < nShortest) {
                shortest = i;
                nShortest = n;
            }
        }
        let len;
        const obj = {};
        for (let i = 0; i <= nOthers; i++) {
            const n = i === shortest ? 0 : i || shortest; //Read the shortest array first. Read the first array instead of the shortest
            len = arrays[n].length;
            for (let j = 0; j < len; j++) {
                const item = arrays[n][j];
                if (obj[item] === i - 1) {
                    if (i === nOthers) {
                        response[response.length] = item;
                        obj[item] = 0;
                    }
                    else {
                        obj[item] = i;
                    }
                }
                else if (i === 0) {
                    obj[item] = 0;
                }
            }
        }
    }
    return response;
}
n1 = [24005, 18321, 478, 1113369];
n2 = [];
s1 = n1.map(i => `${i}`);
s2 = [];
for (let i = 0; i < 100000; i++) {
    n2.push(i);
    s2.push(`${i}`);
}

Tests:

number
intersect([n1, n2])
string
intersect([s1, s2])

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
number
string

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/126.0.0.0 Safari/537.36

Browser/OS: Chrome 126 on Windows

View result in a separate tab

Test name	Executions per second
number	405.2 Ops/sec
string	369.7 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark definition and explain what is being tested.

**Benchmark Definition**

The benchmark definition is an object with two properties: `Benchmark Definition` and `Script Preparation Code`. The `Benchmark Definition` property defines the test case, which in this case is a JavaScript function call to the `intersect()` function. The `Script Preparation Code` property provides the initial code for the script before running the benchmark.

**What is being tested?**

The benchmark tests two different scenarios:

1. `number`: This test case passes an array of numbers (`n1`) and an empty array (`n2`) to the `intersect()` function.
2. `string`: This test case passes an array of strings (`s1`) and an empty array (`s2`) to the `intersect()` function.

**Options being compared**

In this benchmark, two approaches are compared:

* Approach 1: Using arrays of numbers or strings
* Approach 2: Using maps of characters (by converting each string to a character array)

The benchmark is designed to measure the performance difference between these two approaches.

**Pros and Cons**

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

* **Approach 1: Arrays**
	+ Pros:
		- Simple and efficient
		- Familiar data structure for JavaScript developers
	+ Cons:
		- May not be optimal for string comparisons, as strings are encoded in Unicode
* **Approach 2: Maps of characters**
	+ Pros:
		- Optimized for string comparisons, as it uses the `charCodeAt()` method to access individual characters
	+ Cons:
		- Requires more memory and CPU cycles, as it needs to iterate over each character in the string

**Library**

In this benchmark, no external libraries are used.

**Special JS feature or syntax**

There is a special feature being tested here: `charCodeAt()`. This method returns the Unicode code point for a one-character string. In Approach 2, this method is used to access individual characters in the strings.

**Other considerations**

* **Data size**: The benchmark uses large arrays of numbers and strings (100,000 elements each). This may affect the performance results.
* **Browser-specific optimizations**: The benchmark uses a specific browser version (Chrome 126) and platform (Windows Desktop). Other browsers or platforms may have different performance characteristics.

**Alternatives**

Other alternatives for this type of benchmark could include:

* Using other data structures, such as sets or trees
* Implementing a custom comparison algorithm
* Using a different programming language or framework
* Adding additional test cases, such as edge cases or multi-threaded scenarios

Related benchmarks:

sgdfgdgd (version: 0)

sdfgdfg

Comparing performance of: number vs string

Created: one year ago by: Guest

Jump to the latest result

number

string

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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