Benchmark: Multiple Filters vs. One Filter With Multiple Conditions

Script Preparation code:

var array = ["a", "b", "1", "2", "cd", "ef", "12", "23"];

Tests:

Multiple Filters
array.filter(element => !Number.isNaN(+element)).filter(element => element.length > 1).filter(element => +element > 20);
One Filter With Multiple Conditions
array.filter(element => !Number.isNaN(+element) && element.length > 1 && +element > 20);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Multiple Filters
One Filter With Multiple Conditions

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 the provided JSON and explain what's being tested, the options being compared, their pros and cons, and other considerations.

**Benchmark Definition**

The benchmark definition is a JavaScript code snippet that defines two different approaches to filtering an array:

1. **Multiple Filters**: This approach uses three separate filter methods to narrow down the array: `filter(element => !Number.isNaN(+element))`, `filter(element => element.length > 1)`, and finally `filter(element => +element > 20)`.
2. **One Filter With Multiple Conditions**: This approach combines multiple conditions into a single filter method using logical AND (`&&`). The condition is `!Number.isNaN(+element) && element.length > 1 && +element > 20`.

**Options Being Compared**

The two approaches being compared are:

* Using separate, chained filter methods (Multiple Filters)
* Combining multiple conditions into a single filter method (One Filter With Multiple Conditions)

**Pros and Cons of Each Approach:**

### Multiple Filters

Pros:

* Easier to read and maintain, as each step is clearly defined
* Can be more efficient if the array is large and most elements don't pass the first filter

Cons:

* Requires more code and may be slower due to the overhead of multiple function calls
* May not take advantage of optimized array filtering algorithms used by modern JavaScript engines

### One Filter With Multiple Conditions

Pros:

* More concise and potentially faster, as it reduces the number of function calls
* Can leverage optimized array filtering algorithms used by modern JavaScript engines

Cons:

* Harder to read and maintain due to the complexity of the single filter method
* May not be as efficient if most elements pass only one condition

**Other Considerations**

* The use of `+element` to convert strings to numbers implies that the benchmark is interested in comparing performance with numeric literals versus string concatenation.
* The presence of `Number.isNaN()` suggests that the benchmark may want to exclude NaN (Not a Number) values from the filtering process.

**Library and Special JS Features**

There are no external libraries mentioned in the benchmark definition. However, it's worth noting that some browsers have built-in support for Array.prototype.includes() and String.prototype.startsWith(), which might affect the performance of certain filter methods.

**Alternative Approaches**

Other possible approaches to filtering an array could include:

* Using `Array.prototype.every()` or `Array.prototype.some()` instead of separate filter methods
* Utilizing modern JavaScript features like arrow functions, destructuring, or template literals to improve code readability and concision
* Exploring alternative filtering algorithms, such as using a binary search approach or leveraging specialized libraries for array filtering

Keep in mind that the choice of approach ultimately depends on the specific requirements and constraints of the project.

Related benchmarks:

Multiple Filters vs. One Filter With Multiple Conditions (version: 0)

Comparing performance of: Multiple Filters vs One Filter With Multiple Conditions

Created: 5 years ago by: Guest

Jump to the latest result

Multiple Filters

One Filter With Multiple Conditions

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):