Benchmark: Imperative vs declarative vs FP, part 1

HTML Preparation code:


<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.5/lodash.fp.min.js'></script>

Script Preparation code:

var data = Array(1000000).map((_, index) => index);

Tests:

Imperative
var result = []; for (let i in data) result.push(i * 5);
Declarative
data.map(i => i * 5);
FP
_.map( _.multiply(5) )(data);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Imperative
Declarative
FP

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 28 days ago):

LLMs can make mistakes. Check important info.

Let's dive into the explanation of what is being tested in this JavaScript microbenchmark.

The benchmark compares three different approaches to perform an operation on a large array of numbers:

1. **Imperative**: This approach uses a traditional loop to iterate over the array and perform the desired operation (in this case, multiplying each element by 5) using imperative programming style.
2. **Declarative**: This approach uses a functional programming style, where the focus is on specifying what needs to be done with the data (i.e., multiplying each element by 5), rather than how it's done. The `map()` method is used to apply this operation to the array.
3. **FP (Functional Programming)**: This approach uses a library-specific function (`_.multiply(5)` in this case) to perform the desired operation, which is a more concise and declarative way of expressing the same logic as the imperative and declarative approaches.

**Pros and Cons:**

* **Imperative**: Pros - widely understood and implemented, easy to debug. Cons - can be verbose, error-prone, and less scalable.
* **Declarative**: Pros - concise, readable, and easier to maintain. Cons - may require additional setup or library support, and can be slower in some cases due to the overhead of creating intermediate arrays.
* **FP**: Pros - concise and declarative, often faster than imperative approaches (due to caching and optimization). Cons - may require additional setup or library support, and can be less understood by developers without experience with functional programming.

The benchmark's results show that:

* The FP approach is the fastest, followed closely by the Imperative approach. This suggests that the concise and declarative nature of functional programming styles can lead to performance gains.
* The Declarative approach is slower than both the Imperative and FP approaches, but still competitive with a well-optimized implementation.

**Library:**

The benchmark uses Lodash.js, a popular JavaScript utility library that provides various functions for functional programming, including `_.map()` and `_multiply()`. These functions are used to demonstrate the declarative and FP styles of programming.

**Other Considerations:**

* The benchmark only measures the performance difference between these three approaches, without considering other factors such as code readability, maintainability, or scalability.
* The results may not be representative of all scenarios, as they depend on the specific implementation and hardware used to run the benchmarks.
* Alternative approaches, such as using `Array.prototype.map()` or a custom iterative loop, are not included in this benchmark.

**Alternatives:**

Other alternatives for performing this operation include:

* Using `Array.prototype.reduce()` instead of `map()`
* Implementing a custom iterative loop without using any libraries
* Using a parallel processing library to take advantage of multiple CPU cores

Latest run results:

Run details: (Test run date: 4 days ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36

Browser/OS: Chrome 130 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
Imperative	1327.5 Ops/sec
Declarative	477.0 Ops/sec
FP	18.9 Ops/sec

Related benchmarks:

Imperative vs declarative vs FP, part 1 (version: 0)

Comparing performance of: Imperative vs Declarative vs FP

Created: 4 years ago by: Guest

Jump to the latest result

Imperative

Declarative

FP

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 28 days ago):