Preface

// RUNTIME VALIDATORS
export function is<T>(input: unknown | T): input is T; // returns boolean
export function assert<T>(input: unknown | T): T; // throws TypeGuardError
export function validate<T>(input: unknown | T): IValidation<T>; // detailed
export const customValidators: CustomValidatorMap; // customizable

// ENHANCED JSON
export function application<...Args>(): IJsonApplication; // JSON schema
export function assertParse<T>(input: string): T; // type safe parser
export function assertStringify<T>(input: T): string; // safe and faster
    // +) isParse, validateParse 
    // +) stringify, isStringify, validateStringify

// RANDOM DATA GENERATOR
export function random<T>(g?: Partial<IRandomGenerator>): Primitive<T>;

Let's study why typia is much faster than class-validator.

• Github Repository: https://github.com/samchon/typia
• Guide Documents: https://typia.io/docs

I've written some articles introducing my TypeScript runtime validator library typia in here dev.to community. In these previous articles, I had often explained that typia boosts up validation spped through AoT (Ahead of Time) compliation, and it is maximum 20,000x faster than class-validator.

By the way, describing the AoT compilation, I'd just told that typia generates static validation code for target T type, and such static code makes program faster. I never had not explained the reason why such static validation codes are much faster than dynamic validation codes of class-validator.

In today, I'll describe the reason why.

// TYPESCRIPT SOURCE CODE
typia.is<number>(3);
typia.createIs<Date>();

// COMPILED JAVASCRIPT CODE
((input) => "number" === typeof input)(3);
(input) => input instanceof Date;

Measured on Surface Pro 8

Every objects are HashMap

To aid your understanding, I will use many figurative expressions and pseudo codes. However, these figurative expressions and pseudo codes may be somewhat different from actual computer engineering theories. Please read this article considering such aspects.

Have you heard that every objects in dynamic languages are HashMap?

To know how typia optimizes the performance, you've to understand this concept. Why dynamic languages are using HashMap, and how the HashMap makes program slower.

// in dynamic language like JavaScript,
const obj = {};

// you can any properties at any time
obj.a = "A";
obj.wafdfaf = 3;
obj[RandomGenerator.string()] = true;

// removing properties are also same
delete obj.a;
delete obj.wafdfaf;

At first, JavaScript is a dynamic language.

So, it is possible to assign any type of value to a variable. In the object case, it is even possible to add or delete properties at any time.
To support dynamic properties' insertions and deletions, the object must be implemented as a HashMap type.

It's the reason why dynamic languages are using HashMap for objects, and there's no any exception case in the dynamic languages. Python, Ruby, PHP, and so on, all of them are using HashMap for objects.

HashMap class

export class HashMap<Key, T> {
    private hasher_: (key: Key) => number;
    private equal_: (x: Key, y: Key) => number;

    // HashMap stores its key-value pairs into a Linked List
    private data_: List<Entry<Key, T>>;

    // Instead, have bucket array of linked list nodes, for fast key finding
    private buckets_: List.Node<Entry<Key, T>>[][];

    private find(key: Key): List.Node<Entry<Key, T>> {
        const hash: number = this.hasher_(key);
        const index: number = hash % this.buckets_.length;
        const bucket: List.Node<Entry<Key, T>>[] = this.buckets_[index] ?? [];

        return bucket.find(
            (node) => this.equal_(node.value.key, key)
        ) ?? this.data_.end();
    }

    // Therefore, single key access could be faster
    public has(key: Key): boolean {
        this.find(key) !== this.data_.end();
    }

    public get(key: Key): T | undefined {
        const it: List.Node<Entry<Key, T>> = this.find(key);
        return it !== this.data_.end() 
            ? it.value.value 
            : undefined;
    }

    // However, full iteration is slower as well as linked list
    public entries(callback: (value: [Key, T]) => void): void {
        let it: List.Node<Entry<Key, T>> = this.data_.begin();
        while (it !== this.data_.end()) {
            callback([it.value.key, it.value.value]);
            it = it.next();
        }
    }

    public size(): number { return this.data_.size(); }
}

export class List<T> {
    private begin_: List<T>; 
    private end_: List<T>;
    private size_: number;

    public size(): number;
    public begin(): List.Node<T>;
    public end(): List.Node<T>;
}
export namespace List {
    export class Node<T> {
        public next: Node<T> | null;
        public prev: Node<T> | null;
        public value: T;
    }
}

• Actual codes:
  • HashMap: https://github.com/samchon/tstl/blob/master/src/container/HashMap.ts
  • HashBuckets: https://github.com/samchon/tstl/blob/master/src/internal/hash/HashBuckets.ts

By the way, you know how to implement the HashMap? HashMap stores its key-value pairs into a Linked List (doubly-linked-list in C++ STL case). Also, for the fast key finding, it stores nodes of Linked List into an Bucket array.

This is the reason why HashMap makes dynamic languages slower. As you know, static languages are containing object properties into a fixed and sequenced memory space like an Array. Comparing iteration speed of Linked List versus Array, which one is faster? Of course, Array is much faster. This is the one of principle reason why dynamic languages are slower than static languages.

• Dynamic languages store properties into Linked List
• Static languages store properties into Array (sequenced memory space)

If my explanation is not easy to understand, read above pseudo codes. It's not the actual implementation of HashMap and Linked List, but would be helpful to understand the concept.

Hidden Class Optimization

Now, we've learned that dynamic languages are utilizing HashMap for dynamic key composition, but it makes program slower because of its storage Linked List. By the way, v8 engine has a special optimization technique for this problem.

When v8 engine detects an object type that has fixed properties' composition, it makes a hidden class definition for the object type. And, the hidden class definition is not using HashMap, but arrange properties into a fixed and sequenced memory space like static languages.

This is called "Hidden Class Optimization". If you've heard that Google Chrome or NodeJS are much faster than other dynamic or some static languages like Java, it's OK to assume that the hidden class optimization is one of the main reason.

Conclusion

Let's summarize up what we've learned in here article:

1. Dynamic languages are using HashMap to support dynamic properties' insertions and deletions.
2. HashMap stores its key-value pairs into a Linked List container, and it makes rpgoram slower
3. Besides, static languages are storing properties into a fixed and sequenced memory space like an Array, and it makes program faster
4. In the v8 engine case, it has a special optimization technique called "Hidden Class Optimization", to escape from the HashMap and store properties into a fixed and sequenced memory space like static languages

The reason why typia is faster than class-validator is also not much different from the theoretical content summarized above. I've designed typia to generate code that favors the v8 engine, and in actually, code generated by typia benefits from the hidden class optimization.

Besides, class-validator and class-transform are always composing its serialization and validation logics through dynamic properties' accessments, especially represented by Reflect. Therefore, class-validator and class-transform never can get benefit from the hidden class optimization, and always iterating the slow Linked List nodes.

The 20,000x speed gap also came from such difference. Typically, the traversal speed of an array and a linked list differs by about a factor of 10. As class-validator and class-transformer have dual to quadruple nested iterations about dynamic key accessing, the 10x gap be powered to maximum (10⁴ = 10,000)x in theorically.