Benchmark: Shift loop vs unrolled

Script Preparation code:

arr = [];
const ARRAY_SIZE = 5000;
for (let i = 0; i < ARRAY_SIZE; i++) {
  arr.push(i);
}

Tests:

Shift loop
while(arr.length) { let index = arr.shift(); index++; }
Unrolled Loop
const arrSize = arr.length; for (let i = 0; i < arrSize; i++) { let index = arr[i]; index++; } arr = [];

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Shift loop
Unrolled Loop

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

This benchmark does not have any results yet. Be the first one to run it!

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

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark and explain what's being tested.

**Benchmark Definition**

The benchmark is comparing two approaches to iterating over an array: a traditional `shift()` loop versus an unrolled loop using indexing.

**Script Preparation Code**

This code sets up an array with a size of 5000, which will be used for the benchmarks. The script also defines a constant `ARRAY_SIZE` to make it easier to modify in the future.

```javascript
arr = [];
const ARRAY_SIZE = 5000;
for (let i = 0; i < ARRAY_SIZE; i++) {
  arr.push(i);
}
```

**Html Preparation Code**

This section is empty, which means no additional HTML code is required for this benchmark.

Now, let's examine the individual test cases:

**Test Case 1: Shift Loop**

```javascript
while(arr.length) {
  let index = arr.shift();
  index++;
}
```

This test case uses a traditional `shift()` loop to iterate over the array. The `shift()` method removes and returns the first element of the array, which is then incremented by 1.

**Test Case 2: Unrolled Loop**

```javascript
const arrSize = arr.length;
for (let i = 0; i < arrSize; i++) {
  let index = arr[i];
  index++;
}
arr = [];
```

This test case uses an unrolled loop to iterate over the array. The `length` property is used to get the size of the array, and then a for loop iterates over each element using indexing (`arr[i]`). The value of each element is incremented by 1.

**Pros and Cons**

* **Traditional Shift Loop:**
	+ Pros:
		- Easy to understand and implement.
		- No additional memory allocation required.
	+ Cons:
		- Can be slower due to the overhead of removing elements from the array.
		- May not be suitable for large datasets.
* **Unrolled Loop:**
	+ Pros:
		- Can be faster since it doesn't involve removing elements from the array.
		- Suitable for large datasets.
	+ Cons:
		- Requires more memory to store the local variable `index`.
		- May require more careful handling of edge cases (e.g., when the original array is empty).

**Library: None**

There are no external libraries used in this benchmark.

**Special JS Features/Syntax: None**

There are no special JavaScript features or syntaxes being tested in this benchmark.

Now, let's examine the latest benchmark result:

**Benchmark Result**

The result shows that the traditional shift loop (`Shift loop`) is slightly faster than the unrolled loop (`Unrolled Loop`). However, it's essential to note that these results may vary depending on the specific JavaScript engine, browser, and system configuration used.

**Alternatives**

If you were considering alternative approaches, some options might include:

* Using `forEach()` or `map()` instead of a traditional loop.
* Utilizing `Array.prototype.forEach()`, which can be faster than using a traditional for loop.
* Considering the use of more modern JavaScript features, such as iterators and generators, which may offer better performance or efficiency.

Keep in mind that the best approach will depend on the specific requirements and constraints of your project.

Related benchmarks:

Shift loop vs unrolled (version: 0)

Comparing performance of: Shift loop vs Unrolled Loop

Created: 9 years ago by: Guest

Jump to the latest result

Shift loop

Unrolled Loop

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):