Why Does Mutating Object Prototypes Lead to Performance Degradation in JavaScript?

Why Mutating the Prototype of an Object Is Detrimental to Performance

Background

The JavaScript language provides two methods for manipulating the prototype property of an object: the standard setPrototypeOf function and the non-standard __proto__ property. However, it is strongly discouraged to mutate the prototype of an object using either of these methods.

Performance Implications

According to the MDN documentation, mutating the prototype significantly slows down subsequent execution in modern JavaScript implementations. This is because the process involves changing the object's type, which invalidates previously optimized code and forces the interpreter to deoptimize. This deoptimization process can have a significant impact on performance.

Comparison of Mutating Methods

Both foo.__proto__.bar = bar and Foo.prototype.bar = bar create a bar property on the Object.getPrototypeOf(foo) object. However, setting the __proto__ property itself, as in fred.__proto__ = Object.prototype or Object.setPrototypeOf(fred, Object.prototype), is what triggers the performance degradation.

Underlying Reasons

Changing the prototype chain of an existing object disrupts the internal type optimizations employed by JavaScript engines. The engine must discard previously compiled code and fall back to non-optimized code, leading to a performance penalty.

Expert Opinions

Various experts have expressed concerns about mutable prototypes:

• Brendan Eich: "Writable proto is a giant pain to implement and creates type-confusion hazards."
• Brian Hackett: "Mutable proto makes it harder to reason about script behavior and complicates VM, JIT, and analysis implementation."
• Jeff Walden: "Prototype mutation after creation destabilizes performance and impacts proxies and [[SetInheritance]]."

Alternatives

Instead of mutating the prototype of an existing object, it is recommended to create new objects with a different prototype chain using Object.create(). This approach preserves optimizations and avoids the performance penalty associated with prototype mutation.

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