Benchmark: looploop - MeasureThat.net

Tests:

laksdjhflaksdhjfklajshdlfkas
const s = new Set([1, 2, 3, 4, 5]); const b = Array(10000).fill().map((_, i) => i); const res = []; for (let n of b) { if (s.has(n)) { res.push(n); } }
qp92e8u19283u490128u34
const s = new Set([1, 2, 3, 4, 5]); const b = Array(10000).fill().map((_, i) => i); const res = []; for (let n of s) { if (b.includes(n)) { res.push(n); } }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
laksdjhflaksdhjfklajshdlfkas
qp92e8u19283u490128u34

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 break down the benchmark definition and test cases to understand what's being tested.

**Benchmark Definition**

The benchmark definition is essentially a script that defines a scenario for testing performance. In this case, there are two different scripts:

1. The first script creates an empty Set `s` with elements `[1, 2, 3, 4, 5]`, and then uses the `Array(10000).fill().map()` method to create an array of 10,000 unique integers `b`. It then iterates over both `s` and `b` using a for loop, pushing elements that are common between the two data structures into an empty array `res`.
2. The second script is similar, but with a twist: it uses the `Array(10000).fill().map()` method to create the array `b`, just like in the first script. However, instead of iterating over `s` and checking if each element is present in `b` using `includes()`, it iterates directly over the elements of `s`. This means that for every element in `s`, it checks if its corresponding index in `b` (which may not be unique) is present in `b`.

**Comparison**

The two test cases are comparing the performance of these two approaches:

1. Iterating over `s` using `for...of` loop, and checking each element against `b` using `includes()`.
2. Iterating directly over `s`, without checking each element against `b`. This approach is likely to be faster because it avoids the overhead of searching for elements in the array.

**Pros and Cons**

Here are some pros and cons of these approaches:

1. **Iterate over `s` using `for...of` loop, and check each element against `b` using `includes()`**:
	* Pros: This approach is easy to understand and implement.
	* Cons: It may be slower because of the overhead of searching for elements in the array.
2. **Iterate directly over `s`, without checking each element against `b`.**
	* Pros: This approach is likely to be faster, as it avoids the overhead of searching for elements in the array.
	* Cons: It's less intuitive and may require more effort to implement correctly.

**Library**

In both test cases, a Set object (`s`) is created using the `Set` constructor. A Set is a data structure that stores unique values, which makes it useful for this benchmark. The purpose of the Set is to provide a fast way to check if an element is present in the collection, making it a good candidate for optimization.

**Special JS feature or syntax**

There are no special JavaScript features or syntax used in these test cases beyond what's required for the benchmark itself (e.g., `for...of` loop).

**Other alternatives**

Some alternative approaches to this benchmark could be:

1. Using a different data structure, such as an object or a Map, to store the elements.
2. Using a more optimized algorithm, such as using a Bloom filter or a hash table to check for presence.
3. Adding additional constraints or variations, such as checking for duplicates in the array or searching for specific values within the set.

However, these alternatives would likely require significant changes to the benchmark itself and may not provide meaningful insights into the performance characteristics of the original script.

Related benchmarks:

looploop (version: 0)

Comparing performance of: laksdjhflaksdhjfklajshdlfkas vs qp92e8u19283u490128u34

Created: 5 years ago by: Guest

Jump to the latest result

laksdjhflaksdhjfklajshdlfkas

qp92e8u19283u490128u34

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):