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Deep cloning objects is a common scenario in JavaScript where you need to create a complete, independent copy of an object, including all nested structures. This ensures that modifications to the cloned object do not affect the original one. Use cases can range from complex state management in applications to ensuring data immutability in functional programming paradigms.

In JavaScript, objects are stored by reference. This means that directly assigning an object to another variable let b = a only copies the reference, not the data itself. As a result, changes made to the new variable b will also reflect in the original object a. Here's an example:

Even using methods like Object.assign() or the spread operator { ...obj } will only perform a shallow copy, meaning nested objects are still referenced rather than deeply cloned. This could lead to unintended side-effects in scenarios such as:

• Updating complex state in modern front-end frameworks like React.
• Creating immutable data objects where any mutation to one copy should not affect others.
• Cloning deeply nested configuration objects in an application.

For such cases, a deep clone is necessary to ensure that all levels of the object hierarchy are fully duplicated.

Below, we explore two popular approaches to creating a deep clone in JavaScript. Each has its own trade-offs based on complexity and performance.

Using structuredClone()

Since ECMAScript 2021, JavaScript introduced the structuredClone() function to perform a deep copy of objects, including their nested properties.

structuredClone() creates a deep copy of any object that can be serialised, and it handles more data types than traditional JSON-based methods (e.g., Date, Map, Set).

• Efficient: structuredClone() is natively optimised.

• Extended Support: It supports complex data types like Date, Map, Set, and more.

• Browser Support: Ensure that you’re targeting modern environments, as structuredClone() is not supported in older browsers.

• Circular References: It supports circular references, but you should be mindful of complex recursive structures to avoid performance issues.

Using JSON Serialisation

This method serialises the object to a JSON string and then parses it back into a new object. It is simple but comes with limitations.

• Simple and Readable: Minimal syntax makes it accessible for beginners.

• Widely Supported: No dependency on environment-specific features.

• Data Loss: Non-serialisable types (e.g., Function, undefined, Date) will be omitted or converted.

• Circular References: This method fails if the object contains circular references, throwing an error.

• Performance: Can be slower for large objects due to the overhead of serialisation and parsing.

Further Considerations

• Performance:
  For performance-critical applications, structuredClone() is generally faster and more robust than JSON-based approaches. However, for simple use cases on small objects, JSON serialisation might still suffice.

• Edge Cases:
  For objects containing functions, classes, or prototypes, consider using libraries like Lodash’s cloneDeep, which provides more comprehensive support.

• Security Implications:
  Always validate and sanitise objects if they come from external or untrusted sources, especially before cloning, as malicious code could exploit the cloning process.

• structuredClone() Documentation (MDN)
• Lodash cloneDeep
• JSON.stringify() Documentation (MDN)

By understanding and utilising the best deep cloning approach for your use case, you can optimise your code’s performance and data integrity while avoiding subtle bugs caused by shared references.