Benchmark: forEach vs reduce 1000 items

Script Preparation code:

var data = [];

for (let i = 0; i < 1000; i++) {
    data[i] = i;
}

Tests:

forEach reduce
let sum = 0 data.forEach((val) => sum += val)
reduce
sum = data.reduce((sum, item) => sum + item)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
forEach reduce
reduce

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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**Benchmark Definition**

The provided JSON represents a benchmark definition for measuring the performance difference between `forEach` and `reduce` loops when working with an array of 1000 items. The `Script Preparation Code` section initializes an empty array `data` using a traditional `for` loop, while the `Html Preparation Code` section is empty.

**Options Compared**

Two options are compared:

1. **forEach**: Uses the `Array.prototype.forEach()` method to iterate over the array.
2. **reduce**: Uses the `Array.prototype.reduce()` method to accumulate values in an accumulator.

**Pros and Cons of Each Approach**

*   **forEach**
    *   Pros:
        *   More readable and maintainable code
        *   Easier to understand for developers familiar with traditional loops
    *   Cons:
        *   Less efficient than `reduce` due to the overhead of callback function invocation
        *   Can lead to slower performance when dealing with large datasets

*   **reduce**
    *   Pros:
        *   More efficient than `forEach` due to reduced overhead from callback functions
        *   Suitable for use cases where an accumulator is needed
    *   Cons:
        *   Less readable and maintainable code, especially for developers unfamiliar with functional programming concepts
        *   May require additional understanding of the accumulator's purpose

**Library Usage**

None of the benchmark definitions explicitly uses a library. However, if we assume that libraries like Lodash or Ramda might be used in production code, we can infer that `forEach` and `reduce` have different performance characteristics.

**Special JS Features or Syntax**

The provided benchmark does not use any special JavaScript features or syntax. It only focuses on demonstrating the performance difference between two fundamental methods: `forEach` and `reduce`.

**Other Alternatives**

When dealing with large datasets or performance-critical code, developers may also consider alternative approaches:

*   **map() + Array.prototype.forEach()` vs `Array.prototype.reduce()`: This approach uses the `map()` method to create a new array and then iterates over it using `forEach()`. In contrast, `reduce()` directly accumulates values in an accumulator.
*   **filter() + Array.prototype.forEach()` vs `Array.prototype.filter() + reduce()`: Similar to the previous suggestion, this approach uses `filter()` to create a filtered array and then iterates over it using `forEach()`, or uses `filter()` followed by `reduce()` for more complex use cases.

Keep in mind that these alternatives might not be necessary unless you're dealing with extremely performance-critical code or specific edge cases. The original comparison between `forEach` and `reduce` provides a solid foundation for understanding the trade-offs involved.

Related benchmarks:

forEach vs reduce 1000 items (version: 0)

Comparing performance of: forEach reduce vs reduce

Created: 3 years ago by: Registered User

Jump to the latest result

forEach reduce

reduce

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):