Benchmark: for vs foreach vs map 2

Script Preparation code:

var array = Array(100000).fill(1);

Tests:

for
for(let i = 0; i < array.length; i++){ const a = 4 * 99 *array[i]; }
foreach
array.forEach(i => 4 * 99 * i)
map
array.map(i => 4 * 99 * i)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
for
foreach
map

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

I'll break down the provided benchmark definition and test cases to explain what's being tested, compared, and their pros and cons.

**Benchmark Definition**

The provided benchmark measures the performance of three different approaches to iterate over an array: `for`, `foreach`, and `map`. The benchmark uses JavaScript as the programming language.

**Script Preparation Code**

The script preparation code creates a large array with 100,000 elements, filled with the value `1`. This array will be used as input for the iterations.
```javascript
var array = Array(100000).fill(1);
```
**Html Preparation Code**

There is no HTML preparation code provided, which suggests that the benchmark only focuses on JavaScript performance and doesn't consider other factors like rendering or layout.

**Test Cases**

The benchmark consists of three test cases:

1. **`for` loop**:
```javascript
for(let i = 0; i < array.length; i++){\r\n  const a = 4 * 99 *array[i];\r\n}\r\n
```
This is a traditional `for` loop, where the index `i` is incremented manually.

2. **`foreach` loop**:
```javascript
array.forEach(i => 4 * 99 * i)
```
This uses the `forEach` method to iterate over the array. The callback function takes two arguments: the current element (`i`) and its index (not used in this case).

3. **`map` method**:
```javascript
array.map(i => 4 * 99 * i)
```
This uses the `map` method to create a new array with the result of applying the callback function to each element.

**Pros and Cons**

* **`for` loop**: Simple, efficient, and easy to understand. However, it requires manual index management and can be error-prone if not implemented correctly.
* **`foreach` loop**: More concise and flexible than traditional `for` loops. It also avoids the need for manual index management. However, it may have overhead due to method call and iteration overhead.
* **`map` method**: Efficient and concise way to create a new array by applying a transformation function to each element. However, it creates a new array, which can be memory-intensive.

**Library: Lodash**

None of the test cases use any external libraries like Lodash (although I mentioned it in my previous response).

**Special JS Features or Syntax**

There are no special JavaScript features or syntax used in this benchmark. The code is straightforward and easy to understand.

**Alternatives**

Other alternatives for iterating over arrays include:

* **`while` loop**: Another traditional looping construct that requires manual index management.
* **`reduce()` method**: A more functional approach to iteration, which can be useful when working with data transformation pipelines.
* **`flatMap()` method**: Similar to `map()`, but returns an array of transformed elements and flat arrays.

Keep in mind that these alternatives may have different performance characteristics or use cases compared to the original `for`, `foreach`, and `map` loops.

Latest run results:

Run details: (Test run date: 3 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/88.0.4324.192 Safari/537.36

Browser/OS: Chrome 88 on Windows

View result in a separate tab

Test name	Executions per second
for	42.9 Ops/sec
foreach	773.7 Ops/sec
map	520.1 Ops/sec

Related benchmarks:

for vs foreach vs map 2 (version: 0)

Comparing performance of: for vs foreach vs map

Created: 3 years ago by: Guest

Jump to the latest result

for

foreach

map

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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