Benchmark: filter + findIndex

Tests:

filter + findIndex
const childNodes = [ { nodeId: 1, type: 'element' }, { nodeId: 2, type: 'comment' }, { nodeId: 3, type: 'element' }, { nodeId: 4, type: 'element' } ] const index = childNodes .filter(node => node.type === 'element') .findIndex(node => node.nodeId === 3) console.log(index)
while loop
const childNodes = [ { nodeId: 1, type: 'element' }, { nodeId: 2, type: 'comment' }, { nodeId: 3, type: 'element' }, { nodeId: 4, type: 'element' } ] let i = 0 let index = 0 while(childNodes[i].nodeId !== 3) { if(childNodes[i].type === 'element') { index++ } i++ } console.log(index)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
filter + findIndex
while loop

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 information and explain what's being tested, compared, and the pros/cons of each approach.

**Benchmark Overview**

The provided benchmark is testing two individual test cases: "filter + findIndex" and "while loop". The benchmarks aim to measure the performance of different approaches for finding a specific element in an array.

**Filter + FindIndex Approach**

The first test case, "filter + findIndex", uses the `Array.prototype.filter()` and `Array.prototype.findIndex()` methods. Here's what's being tested:

* Creating an array of objects with node IDs and types
* Filtering the array to only include elements with a specific type (in this case, 'element')
* Finding the index of the first element that matches a specific condition (node ID 3)
* Logging the result to the console

**Pros:**

1. Efficient and concise: The `filter()` and `findIndex()` methods are optimized for performance and readability.
2. JavaScript standard library: Using built-in methods reduces the risk of implementation-specific variations.

**Cons:**

1. Method calls overhead: Creating and calling methods on an array can introduce additional overhead compared to a simple loop.
2. Function call stack usage: Each method call creates a new function call stack frame, which can impact performance.

**While Loop Approach**

The second test case, "while loop", uses a traditional `while` loop to iterate through the array:

* Creating an array of objects with node IDs and types
* Initializing indices (i and index) for iteration
* Iterating until the condition is met (node ID 3)
* Incrementing the index when an element matches the type
* Logging the result to the console

**Pros:**

1. Loop control overhead: While loops can be optimized for performance, as they don't create additional method call stacks.
2. No dependency on JavaScript standard library methods.

**Cons:**

1. Readability and maintainability: While loops can become complex and harder to read for larger datasets or more complex logic.
2. Potential for integer arithmetic issues (e.g., overflow).

**Library Used:**

In both test cases, the `Array.prototype` is used, which is a part of the JavaScript standard library.

**Other Alternatives:**

For similar use cases, other alternatives could include:

* Using other array methods like `some()`, `every()`, or `reduce()` for filtering and searching.
* Utilizing libraries like Lodash (specifically `filterBy` and `findIndex`) which provide additional utility functions for filtering and searching arrays.
* Leveraging the browser's built-in performance tools, such as Web Workers or Web Assembly, to optimize performance-critical code.

When choosing an approach, consider factors like readability, maintainability, and the specific requirements of your use case. Both methods have their trade-offs, and selecting the best one depends on your project's needs.

Related benchmarks:

filter + findIndex (version: 0)

Comparing performance of: filter + findIndex vs while loop

Created: 6 years ago by: Guest

Jump to the latest result

filter + findIndex

while loop

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):