Benchmark: Testing Reduce sum with immutable destructed objects

Script Preparation code:

var myArray = new Array(1000).fill(null)

Tests:

Using destrction
myArray.reduce((accum, entry, index)=> { return { ...accum, sum: accum.sum + index }; }, { sum: 0});
Direct assign
myArray.reduce((accum, entry, index)=> { accum.sum += index; return accum; }, { sum: 0});

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Using destrction
Direct assign

Fastest: N/A

Slowest: N/A

Latest run results:

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

LLMs can make mistakes. Check important info.

Let's break down the provided JSON and explain what's being tested, compared, and considered.

**Benchmark Overview**

The benchmark measures the performance of two approaches to calculate the sum of an array using JavaScript's `reduce` method. The test cases are designed to compare the execution speed of these two methods on a large dataset (1,000 null-filled elements).

**Script Preparation Code**
```javascript
var myArray = new Array(1000).fill(null);
```
This code creates an array of 1,000 elements, all filled with `null`. This array will be used as the input for the `reduce` method.

**Html Preparation Code**
There is no HTML preparation code provided, which suggests that this benchmark focuses solely on JavaScript performance and does not consider rendering or other non-JavaScript aspects.

**Benchmark Definition JSON**

The benchmark definition contains two main parts:

1. **Name**: A descriptive name for the benchmark.
2. **Description**: An empty string, indicating that no description is provided.
3. **Script Preparation Code**: The code snippet that creates the input array (`myArray`).
4. **Html Preparation Code**: Again, an empty string.

**Individual Test Cases**

There are two test cases:

1. **Using Destructure**:
```javascript
myArray.reduce((accum, entry, index)=> {
  return { ...accum, sum: accum.sum + index };
}, { sum: 0 });
```
This code uses destructuring to create a new object (`{ ...accum, sum: accum.sum + index }`) and updates the `sum` property of the accumulator. The key aspect here is the use of the spread operator (`...`) to create a new object.

2. **Direct Assign**:
```javascript
myArray.reduce((accum, entry, index)=> {
  accum.sum += index;
  return accum;
}, { sum: 0 });
```
This code updates the `sum` property directly on the accumulator (`accum.sum += index;`) without creating a new object.

**Pros and Cons of Each Approach**

1. **Using Destructure**:
	* Pros:
		+ Creates a new object, which can be beneficial for readability and maintainability.
		+ May be more efficient due to the creation of a new object, which avoids updating an existing one.
	* Cons:
		+ Requires the use of the spread operator (`...`), which may add overhead.
2. **Direct Assign**:
	* Pros:
		+ Updates an existing object, which can be faster since it doesn't require creating a new object.
	* Cons:
		+ May not be as readable or maintainable due to the direct assignment.

**Library and Special JS Feature**

There is no explicit library mentioned in the benchmark definition. However, the use of destructuring (`{ ...accum, sum: accum.sum + index }`) is an ECMAScript 2018 feature that allows for more concise object creation.

**Other Considerations**

* The benchmark measures the execution speed of both approaches using a large dataset (1,000 elements). This suggests that performance is the primary concern.
* The use of `null` as a filler value in the array may affect the results, as it could potentially impact memory allocation or garbage collection. However, this is unlikely to be the case unless the benchmark is run on very low-memory systems.

**Alternatives**

Some possible alternatives for measuring performance in JavaScript benchmarks include:

* Using other data structures, such as arrays or linked lists, instead of a plain array.
* Incorporating more complex operations, like sorting or filtering, into the benchmark.
* Using different browsers, versions, or devices to compare results across platforms.
* Measuring not only execution speed but also memory usage or garbage collection overhead.

Related benchmarks:

Testing Reduce sum with immutable destructed objects (version: 0)

Comparing performance of: Using destrction vs Direct assign

Created: 3 years ago by: Guest

Jump to the latest result

Using destrction

Direct assign

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):