Benchmark: Functional Vs Imperative 10 elems

Script Preparation code:

window.nums = new Array(10).fill(0).map((x,i) => i)

Tests:

Functional
const y = nums.filter(x => x%2).map(x => x*3).filter(x => x < 100) return y
Imperative
const y = [] for(const x of nums) { if(x%2) { const x3 = x*3; if(x3 < 100) { y.push(x3) } } } return y

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Functional
Imperative

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (X11; CrOS x86_64 14541.0.0) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/126.0.0.0 Safari/537.36

Browser/OS: Chrome 126 on Chrome OS 14541.0.0

View result in a separate tab

Test name	Executions per second
Functional	2092581.2 Ops/sec
Imperative	10626187.0 Ops/sec

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

LLMs can make mistakes. Check important info.

**Benchmark Overview**

MeasureThat.net is a website that allows users to create and run JavaScript microbenchmarks to compare the performance of different programming approaches.

**Benchmark Definition JSON Analysis**

The provided JSON represents the benchmark definition, which includes:

* `Name`: The name of the benchmark, "Functional Vs Imperative 10 elems".
* `Description`: An empty description for this benchmark.
* `Script Preparation Code`: A JavaScript code that initializes an array `nums` with 10 elements, each with a unique index value. This is used to filter and manipulate the data in both test cases.
* `Html Preparation Code`: An empty string indicating no HTML preparation is required.

**Individual Test Cases**

There are two individual test cases:

1. **Functional Test Case**
The code uses the `filter` and `map` methods to process the `nums` array:
```javascript
const y = nums.filter(x => x%2).map(x => x*3).filter(x => x < 100)
return y
```
This approach is considered functional programming, where a function takes an input (the array) and returns a new output without modifying the original.

**Pros of Functional Approach:**

* Easier to write and maintain code, as it's more focused on data transformation.
* Less prone to side effects and mutable state issues.
* Can be more composable and reusable.

**Cons of Functional Approach:**

* May require additional memory allocation for creating new arrays, potentially leading to performance overhead.
* May have slower execution due to the creation of temporary intermediate results.

2. **Imperative Test Case**
The code uses a `for` loop and array push to process the `nums` array:
```javascript
const y = []
for (const x of nums) {
  if(x%2) {
    const x3 = x*3;
    if(x3 < 100) {
      y.push(x3)
    }
  }
}
return y
```
This approach is considered imperative programming, where a function explicitly controls the execution flow and modifies state.

**Pros of Imperative Approach:**

* Can be more efficient in terms of memory allocation, as it avoids creating new arrays.
* May have faster execution due to the direct manipulation of the array.

**Cons of Imperative Approach:**

* Can lead to more complex code and harder-to-debug issues due to explicit state management.
* May result in performance overhead due to repeated array lookups and updates.

**Library and Special JS Feature Mention**

There is no library mentioned in the provided benchmark definition or test cases. No special JavaScript features are used beyond standard language features like `filter`, `map`, `for` loops, and conditional statements.

**Other Alternatives**

Some other programming approaches that could be compared on MeasureThat.net include:

* Declarative programming (e.g., Prolog)
* Object-oriented programming (OOP) with encapsulation and inheritance
* Event-driven programming
* Functional reactive programming (FRP)

Note that each approach has its own trade-offs in terms of code complexity, performance, and maintainability. MeasureThat.net provides a platform for users to experiment and compare different programming styles, allowing them to find the most suitable approach for their specific needs.

Related benchmarks:

Functional Vs Imperative 10 elems (version: 0)

Comparing performance of: Functional vs Imperative

Created: 2 years ago by: Guest

Jump to the latest result

Functional

Imperative

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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