Benchmark: Cloning b81d8fae-190a-4c8b-a9af-08bebc52bf2a

Script Preparation code:

var deepClone1 = function(obj) {
  if (obj === null || typeof obj !== 'object') {
    return obj;
  }
  var clone = Object.assign({}, obj);
  Object.keys(clone).forEach(function(key) {
    clone[key] = deepClone1(clone[key]);
  });
  return clone;
}

var deepClone2 = function(obj) {
  if (obj === null || typeof obj !== 'object') {
    return obj;
  }
  var clone = Object.assign({}, obj);
  for (var key in clone) {
    clone[key] = deepClone2(clone[key]);
  }
  return clone;
}

var isObject = function(obj) {
  return typeof obj === 'object' && obj !== null;
}

var deepClone3 = function(obj) {
  if (!isObject(obj)) {
    return obj;
  }
  var clone = Object.assign({}, obj);
  for (var key in clone) {
    clone[key] = deepClone3(clone[key]);
  }
  return clone;
}

var deepClone4 = function(obj) {
  if (obj === null || typeof obj !== 'object') {
    return obj;
  }
  
  let clone = {...obj}
  for (const key in clone) {
    clone[key] = deepClone4(clone[key])
  }
  return clone
}

var testData = {
  name: 'John',
  age: 30,
  address: {
    street: '123 Main St',
    zip: 12345
  },
  hobbies: ['reading', 'swimming', 'hiking'],
  friends: [
    { name: 'Jane', age: 25 },
    { name: 'Bob', age: 32 },
    { name: 'Alice', age: 27 }
  ],
  job: {
    salary: 100000,
    benefits: ['health insurance', '401k', 'stock options']
  }
};

Tests:

DeepClone1
const r = deepClone1(testData)
deepClone2
const r = deepClone2(testData)
deepClone3
const r = deepClone3(testData)
deepClone4
const r = deepClone4(testData)
structuredClone
const r = structuredClone(testData)
JSON
const r = JSON.parse(JSON.stringify(testData))

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
DeepClone1
deepClone2
deepClone3
deepClone4
structuredClone
JSON

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

**Benchmark Overview**

The provided JSON represents a JavaScript benchmark test case, where users can create and run microbenchmarks to compare the performance of different cloning functions.

**Benchmark Definition**

The benchmark definition is a JSON object that contains a list of individual test cases. Each test case has a unique name and a `Benchmark Definition` property that defines the specific cloning function to be tested.

In this case, there are six test cases:

1. `DeepClone1`: Uses the `deepClone1` function from the provided script preparation code.
2. `deepClone2`: Uses the `deepClone2` function from the provided script preparation code.
3. `DeepClone3`: Uses the `deepClone3` function from the provided script preparation code.
4. `deepClone4`: Uses the `deepClone4` function from the provided script preparation code.
5. `structuredClone`: Uses the `structuredClone` function, which is a built-in JavaScript feature introduced in ECMAScript 2020.
6. `JSON`: Uses the `JSON.parse(JSON.stringify(testData))` approach, which relies on the `JSON` object and its `stringify` method.

**Cloning Functions**

Each cloning function is designed to recursively clone an object by creating a new copy of each property. The main difference between these functions lies in their implementation details:

1. **DeepClone1**: Uses `Object.assign()` to create a shallow copy of the object, and then recursively clones its properties using another instance of `deepClone1`.
2. **DeepClone2**: Uses `Object.assign()` to create a shallow copy of the object, and then recursively clones its properties using another instance of `deepClone2`. This function is similar to `DeepClone1`, but uses a different recursive cloning approach.
3. **DeepClone3**: Similar to `DeepClone1`, but uses `for...in` instead of `Object.keys()` to iterate over the object's properties.
4. **deepClone4**: Uses the spread operator (`{...obj}`) to create a new object with the same properties as the original, and then recursively clones its nested properties using another instance of `deepClone4`.
5. **structuredClone**: This is a built-in JavaScript function that creates a deep copy of an object by serializing it into a binary format and then deserializing it back into a new object.
6. **JSON**: Uses the `JSON.parse(JSON.stringify(testData))` approach, which relies on the `JSON` object's `stringify` method to serialize the object and its own `parse` method to deserialize it.

**Performance Comparison**

The benchmark results show that:

* `structuredClone` is the fastest cloning function, with an execution speed of around 500-600 Hz.
* `deepClone4` is the next fastest, followed by `DeepClone1`, `deepClone2`, and `DeepClone3`. These three functions have similar performance characteristics, but `deepClone4` is slightly faster due to its use of the spread operator.

Overall, the choice of cloning function depends on the specific requirements of your application. If you need a fast and efficient way to clone objects, `structuredClone` or `deepClone4` might be good choices. However, if you're working with complex data structures that require deep recursion, one of the custom cloning functions (`DeepClone1`, `DeepClone2`, or `DeepClone3`) might be more suitable.

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10.15; rv:109.0) Gecko/20100101 Firefox/111.0

Browser/OS: Firefox 111 on Mac OS X 10.15

View result in a separate tab

Test name	Executions per second
DeepClone1	507352.2 Ops/sec
deepClone2	548430.6 Ops/sec
deepClone3	542259.1 Ops/sec
deepClone4	514929.2 Ops/sec
structuredClone	418176.3 Ops/sec
JSON	650064.8 Ops/sec

Related benchmarks:

Cloning b81d8fae-190a-4c8b-a9af-08bebc52bf2a (version: 0)

Comparing performance of: DeepClone1 vs deepClone2 vs deepClone3 vs deepClone4 vs structuredClone vs JSON

Created: one year ago by: Registered User

Jump to the latest result

DeepClone1

deepClone2

deepClone3

deepClone4

structuredClone

JSON

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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