Benchmark: dsadsadas - MeasureThat.net

HTML Preparation code:

<script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.5/lodash.core.js"></script>

Tests:

NOEMl
var a = [{c: 2}, {c:1}]; var b = a.find(item => item.c === 1);
los
var a = [{c: 2}, {c:1}]; var b = _.find(a, item => item.c === 1);
loddddd
var a = [{c: 2}, {c:1}]; var b = _.find(a, {c:1});

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
NOEMl
los
loddddd

Fastest: N/A

Slowest: N/A

Latest run results:

No previous 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 the world of JavaScript microbenchmarks!

**Benchmark Definition JSON**

The provided JSON represents a benchmark definition, which is a set of instructions that defines how to create and run a microbenchmark on MeasureThat.net.

**What is tested?**

In this case, we're testing three different ways to find an item in an array using the `find()` method. The tests are comparing the performance of:

1. Vanilla JavaScript (using only built-in methods)
2. Lodash.js (a popular utility library that provides a lot of useful functions for working with data structures)
3. Lodash.js with a specific function signature (using `_find()` instead of `find()`)

**Options compared**

The three options being compared are:

1. **Vanilla JavaScript**: Using the built-in `find()` method to search for an item in the array.
2. **Lodash.js**: Using the `_find()` method provided by Lodash.js to achieve the same result.
3. **Lodash.js with specific function signature**: Using Lodash.js's `_find()` method, but with a specific function signature that differs from the vanilla JavaScript implementation.

**Pros and Cons of each approach**

Here are some pros and cons for each approach:

1. **Vanilla JavaScript**:
	* Pros: Easy to understand and implement, no dependencies required.
	* Cons: May not be as efficient or scalable as other approaches.
2. **Lodash.js**:
	* Pros: Provides a convenient and efficient way to perform common tasks, especially for larger datasets.
	* Cons: Introduces an additional dependency, which may impact performance in some cases.
3. **Lodash.js with specific function signature**:
	* Pros: May offer better performance due to optimized implementation or caching.
	* Cons: Requires knowledge of Lodash.js's internal workings and function signatures.

**Library explanation**

In this benchmark, we're using Lodash.js (a utility library for functional programming in JavaScript). The `_find()` method is a high-performance implementation that searches the array from start to finish, returning the first element that matches the provided callback function. This approach is more efficient than the vanilla JavaScript `find()` method because it uses an optimized algorithm and avoids unnecessary iterations.

**Special JS feature or syntax**

In this benchmark, we're not using any special JavaScript features or syntax beyond what's already covered by the standard library (Lodash.js in this case).

**Other alternatives**

If you're interested in exploring alternative approaches to this benchmark, here are a few options:

1. **ES6+ array methods**: You could try implementing the same test cases using newer ES6+ array methods like `filter()` or `reduce()`.
2. **Caching and memoization**: Some libraries, like Lodash.js, offer caching and memoization mechanisms to optimize performance-critical functions.
3. **Parallel testing**: MeasureThat.net also allows you to run multiple benchmark tests in parallel, which can help demonstrate differences in performance between various approaches.

Keep in mind that the optimal approach will depend on your specific use case, dataset size, and performance requirements. Feel free to experiment with different methods to find what works best for your needs!

Related benchmarks:

dsadsadas (version: 0)

Comparing performance of: NOEMl vs los vs loddddd

Created: 6 years ago by: Guest

Jump to the latest result

NOEMl

los

loddddd

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):