Benchmark: string based guid generation

Script Preparation code:

function generate_guid(s) {
    var i = 0,
        guid = '',
        n = s && s.length || 0;

    for (; i < 8; i++) {
        guid += (i < n) ? s[i] : '0';
    }

    guid += '-';

    for (i = 8; i < 12; i++) {
        guid += (i < n) ? s[i] : '0';
    }

    guid += '-';

    for (i = 12; i < 16; i++) {
        guid += (i < n) ? s[i] : '0';
    }

    guid += '-';

    for (i = 16; i < 20; i++) {
        guid += (i < n) ? s[i] : '0';
    }

    guid += '-';

    for (i = 20; i < 32; i++) {
        guid += (i < n) ? s[i] : '0';
    }

    return guid;
}

function randomString() {
    return Math.random().toFixed(16).slice(2);
}

function str32() {
    return randomString() + randomString();
}

var repo = new Array(1000).fill(0).map(str32);

Tests:

undefined
generate_guid()
empty string
generate_guid('')
random out of 1000
generate_guid(repo[Math.floor(Math.random() * 1000)])

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
undefined
empty string
random out of 1000

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.

Let's dive into explaining the benchmark.

**What is being tested?**

The benchmark tests three different approaches to generate GUID (Globally Unique Identifier) strings from input strings:

1. **Generate GUID from an empty string**: The `generate_guid('')` function is tested to see how long it takes to execute.
2. **Generate GUID from a variable-length string**: The `generate_guid(repo[Math.floor(Math.random() * 1000)])` function is tested with a random out-of-bounds index of the `repo` array (between 0 and 999). This tests the function's behavior when given an invalid or out-of-range input.
3. **Generate GUID from a string**: The `generate_guid(s)` function is tested with a fixed-length string (`str32()`) repeated twice to simulate a variable-length input.

**Options compared:**

The benchmark compares the execution time of these three approaches:

* **Empty string**: Input is an empty string (`''`)
* **Variable out-of-bounds index**: Input is a random element from the `repo` array (between 0 and 999)
* **Variable length string**: Input is a randomly generated string using `randomString()` repeated twice

**Pros and Cons of each approach:**

1. **Empty string**:
	* Pros: Simplistic input, easy to test
	* Cons: May not reflect real-world scenarios where input strings are often non-empty or variable-length
2. **Variable out-of-bounds index**:
	* Pros: Tests error handling and edge cases
	* Cons: Input is randomly generated, which may not be representative of typical use cases
3. **Variable length string**:
	* Pros: Simulates real-world scenarios where input strings are often variable-length
	* Cons: Requires additional setup to generate random strings

**Library used:**

The `randomString()` function uses the `Math.random()` method, which generates a pseudo-random number between 0 (inclusive) and 1 (exclusive). This is a basic implementation of randomness.

**Special JavaScript features or syntax:**

None are mentioned in this benchmark. The code only uses standard JavaScript features like functions, arrays, loops, and string concatenation.

**Other alternatives:**

If you want to test GUID generation with more realistic inputs, you could use:

* Real-world strings (e.g., URLs, emails, names)
* UUID libraries or implementations
* More sophisticated randomization techniques

Keep in mind that these alternatives may require additional setup and testing to ensure accurate results.

Related benchmarks:

string based guid generation (version: 0)

convert string to guid

Comparing performance of: undefined vs empty string vs random out of 1000

Created: 8 years ago by: Guest

Jump to the latest result

undefined

empty string

random out of 1000

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):