Benchmark: Two lambdaless filters vs one lambded

Script Preparation code:

var data = Array.from(Array(5000));
                        
var more = (n) => n > 0.3;                         
var less = (n) => n < 0.6;

Tests:

Two filters
var filtered = data.filter(more).filter(less);
Combined filter
var filtered = data.filter(n => more(n) && less(n));

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Two filters
Combined filter

Fastest: N/A

Slowest: N/A

Latest run results:

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

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Let's break down what's being tested in this JavaScript microbenchmark.

**What's being tested?**

The provided benchmark compares the performance of two different approaches to applying filters to an array of numbers:

1. **Two separate filters**: The first approach applies two separate filters, `more` and `less`, to the data array using the `filter()` method twice.
2. **Combined filter**: The second approach combines the two filters into a single condition using the logical AND operator (`&&`) inside an arrow function.

**Options compared**

The benchmark is comparing these two approaches:

1. Two separate filters
2. Combined filter

**Pros and cons of each approach:**

1. **Two separate filters**:
	* Pros:
		+ Easier to understand and maintain, as each filter is a simple one-liner.
		+ Can be optimized independently if needed.
	* Cons:
		+ Requires two function calls (more() and less()), which may incur additional overhead.
2. **Combined filter**:
	* Pros:
		+ Reduces the number of function calls, potentially improving performance.
		+ Simplifies the code into a single expression.
	* Cons:
		+ May be harder to understand and maintain, as it's a more complex condition.
		+ If either filter is not optimized, the combined filter may suffer.

**Library/Functionality:**

The benchmark uses JavaScript's built-in `filter()` method to apply filters to the data array. The `more` and `less` functions are defined in the script preparation code.

**Special JS feature/syntax:**

None mentioned in this benchmark.

**Other alternatives:**

If you wanted to rewrite the benchmark using a different approach, here are some alternatives:

1. **Using `every()` instead of `filter()`**: Instead of filtering out elements, you could use the `every()` method to check if all elements pass the condition.
2. **Using a `Map` or `Array.prototype.reduce()`**: You could store the filters in a map and apply them using `reduce()`, which might be more efficient for large datasets.
3. **Using a library like Lodash**: If you wanted to make the code even simpler, you could use a utility library like Lodash, which provides functions like `filterBy()` that combine multiple conditions.

Keep in mind that these alternatives may not necessarily improve performance or readability in this specific benchmark, but they demonstrate different ways to approach similar problems.

Related benchmarks:

Two lambdaless filters vs one lambded (version: 0)

Comparing performance of: Two filters vs Combined filter

Created: 4 years ago by: Guest

Jump to the latest result

Two filters

Combined filter

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):