Benchmark: Lodash clone deep object array vs string array

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/npm/lodash@1.3.1/lodash.min.js"></script>

Script Preparation code:

var N = 10000;
var stringItems = [ ...Array(N).keys() ].map( i => "foo");
var objectItems = [ ...Array(N).keys() ].map( i => { return { bar: "foo" } });

Tests:

Clone deep strings
_.cloneDeep(stringItems);
Clone deep objects
_.cloneDeep(objectItems);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Clone deep strings
Clone deep objects

Fastest: N/A

Slowest: N/A

Autogenerated LLM Sumamry (model llama3.2:3b, generated 4 days ago):

LLMs can make mistakes. Check important info.

Let's dive into the benchmark and explain what's being tested.

The provided JSON represents a JavaScript microbenchmarking test case on MeasureThat.net. The test compares the performance of two approaches: cloning an array of strings with Lodash's `cloneDeep` function versus cloning an array of objects with the same function.

**What is being compared?**

1. Cloning an array of strings using Lodash's `cloneDeep` function.
2. Cloning an array of objects using Lodash's `cloneDeep` function.

**Options being compared:**

* Cloning an array of strings
* Cloning an array of objects

**Pros and Cons of each approach:**

1. **Cloning an array of strings:**
	* Pros:
		+ Easier to implement, as string concatenation is a basic JavaScript operation.
		+ Less memory-intensive, as strings are more compact than objects.
	* Cons:
		+ May not be representative of real-world scenarios, where data may involve complex structures.
2. **Cloning an array of objects:**
	* Pros:
		+ More representative of real-world scenarios, where data often involves nested objects and arrays.
		+ Allows for testing of object-oriented programming concepts, such as inheritance and polymorphism.
	* Cons:
		+ More memory-intensive, as objects require more memory than strings.
		+ May be slower due to the overhead of creating and manipulating complex objects.

**Lodash library:**

The `cloneDeep` function is a utility function from Lodash that creates a deep copy of an object or array. The purpose of this function is to recursively traverse the input data structure, creating new copies of all nested elements, and return a new, independent copy of the original data structure.

**Special JS feature: None mentioned**

The benchmark does not rely on any special JavaScript features or syntax that would make it less applicable to other programming languages or environments.

**Other alternatives:**

If you wanted to create similar benchmarks for other programming languages or libraries, you could consider the following:

* For string cloning:
	+ Using the `String.prototype.split()` method with an empty array as a separator.
	+ Creating a custom function that concatenates strings using a template engine like Handlebars.
* For object cloning:
	+ Using the `JSON.parse(JSON.stringify(obj))` syntax, which creates a shallow copy of an object.
	+ Implementing a custom recursive function to create a deep copy of an object.

Keep in mind that these alternatives would require modifications to the benchmark code and may not provide the same level of representativeness as the original Lodash-based approach.

Latest run results:

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

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.0.0 Safari/537.36

Browser/OS: Chrome 117 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
Clone deep strings	2161.6 Ops/sec
Clone deep objects	6.2 Ops/sec

Related benchmarks:

Lodash clone deep object array vs string array (version: 0)

Compares performance of deep cloning an array of objects vs an array of strings with Lodash cloneDeep.

Comparing performance of: Clone deep strings vs Clone deep objects

Created: one year ago by: Guest

Jump to the latest result

Clone deep strings

Clone deep objects

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Sumamry (model llama3.2:3b, generated 4 days ago):