Benchmark: Optimisation - MeasureThat.net

Script Preparation code:

var a = [{
    subChallenges: [{
        state: "ACCEPTED"
    }, {
        state: false
    }, {
        state: "ACCEPTED"
    }]
}, {
    subChallenges: [{
        state: "ACCEPTED"
    }, {
        state: false
    }, {
        state: false
    }]
}, {
    subChallenges: [{
        state: "ACCEPTED"
    }, {
        state: false
    }, {
        state: false
    }]
}, {
    subChallenges: [{
        state: "ACCEPTED"
    }, {
        state: "ACCEPTED"
    }, {
        state: "ACCEPTED"
    }]
}]

function Function_0(challenges) {
    let count = 0;
    if (challenges) {
        challenges.map((challenge) => {
            if (
                challenge.subChallenges &&
                challenge.subChallenges.filter(
                    (subChallenge) => subChallenge.state !== "ACCEPTED"
                ).length === 0
            )
                count++;
        });
    }
    return count;
}

function Function_1(challenges) {
    let count = 0;
    if (challenges) {
        let i = challenges.length;

        while (i--) {
            let challenge = challenges[i];

            if (!challenge.subChallenges) {
                continue;
            }

            let j = challenge.subChallenges.length,
                truthy = true;

            while (j--) {
                if (challenge.subChallenges.state !== "ACCEPTED") {
                    truthy = false;
                }
            }

            if (truthy) {
                count++
            }
        }
    }

    return count;
}

Tests:

Original
Function_0(a);
Opti
Function_1(a);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Original
Opti

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 3 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36

Browser/OS: Chrome 91 on Windows

View result in a separate tab

Test name	Executions per second
Original	2806771.2 Ops/sec
Opti	5340543.0 Ops/sec

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

LLMs can make mistakes. Check important info.

Measuring performance differences between two approaches is crucial in optimization, and MeasureThat.net provides a valuable platform for benchmarking JavaScript microbenchmarks.

**Benchmark Overview**

The provided JSON defines two benchmark test cases:

1. **Original**: This test case runs the `Function_0` function, which iterates through an array of challenges and increments a counter when no sub-challenge has a state of "ACCEPTED".
2. **Opti**: This test case runs the `Function_1` function, which uses a similar logic but with some optimizations.

**Benchmark Definition**

The benchmark definition is a JSON object that contains the JavaScript code to be executed for each test case. For the **Original** test case:

```javascript
function Function_0(challenges) {
    let count = 0;
    if (challenges) {
        challenges.map((challenge) => {
            if (
                challenge.subChallenges &&
                challenge.subChallenges.filter(
                    (subChallenge) => subChallenge.state !== "ACCEPTED"
                ).length === 0
            )
                count++;
        });
    }
    return count;
}
```

And for the **Opti** test case:

```javascript
function Function_1(challenges) {
    let count = 0;
    if (challenges) {
        let i = challenges.length;

while (i--) {
            let challenge = challenges[i];

if (!challenge.subChallenges) {
                continue;
            }

let j = challenge.subChallenges.length,
                truthy = true;

while (j--) {
                if (challenge.subChallenges.state !== "ACCEPTED") {
                    truthy = false;
                }
            }

if (truthy) {
                count++;
            }
        }
    }

return count;
}
```

**Options Compared**

The two functions, `Function_0` and `Function_1`, differ in the way they iterate through the array of challenges and filter out sub-challenges with a state of "ACCEPTED". The main difference is that:

*   **Original**: Uses the `map()` method to create a new array with filtered elements.
*   **Opti**: Uses two nested loops to directly access and compare the states of individual sub-challenges.

**Pros and Cons**

*   **Original (using map())**:
    *   Pros: Easier to read, maintainable code. This approach is more concise and expressive, as it uses a standard JavaScript method for filtering arrays.
    *   Cons: May be slower due to the creation of a new array with filtered elements, which can result in additional memory allocation and copying.
*   **Opti (using nested loops)**:
    *   Pros: Can be faster because it avoids the overhead of creating a new array. This approach also allows for better control over the iteration process.
    *   Cons: More complex code that may be harder to understand and maintain, especially for developers unfamiliar with this pattern.

**Library**

There is no explicit library mentioned in the benchmark definition. However, the `map()` method is a built-in JavaScript function used for creating new arrays based on an existing array's elements.

**Special JS Features or Syntax**

None are explicitly mentioned in the provided code snippets.

**Other Alternatives**

To optimize performance, developers could consider alternative approaches, such as:

*   Using `Array.prototype.reduce()` to accumulate a counter instead of using a separate variable.
*   Employing memoization techniques to cache results for repeated calls with similar inputs.
*   Leveraging JavaScript engines' built-in optimizations, such as caching or compiling code ahead-of-time (AOT).
*   Utilizing parallel processing or concurrent execution methods to leverage multiple CPU cores.

By understanding the performance differences between various approaches and considering alternative optimization strategies, developers can create more efficient and scalable code.

Related benchmarks:

Optimisation (version: 0)

Comparing performance of: Original vs Opti

Created: 3 years ago by: Guest

Jump to the latest result

Original

Opti

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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