Megamorphic Cache in JavaScript

Caching is a fundamental optimization technique in software development, reducing redundant computations by storing and reusing previously calculated results. A megamorphic cache takes this a step further by dynamically adapting its caching strategy based on the type of the function being cached. This challenge asks you to implement a JavaScript megamorphic cache that can intelligently cache functions with varying argument types and return types.

Problem Description

You are tasked with creating a MegamorphicCache class in JavaScript. This cache should be able to store and retrieve results of functions, but crucially, it should determine the appropriate caching strategy (e.g., stringifying arguments, using a simple equality check) based on the types of arguments passed to the cached function. The cache should handle functions with various argument types (numbers, strings, booleans, objects, arrays, etc.) and return types.

Key Requirements:

• cache(func): Takes a function func as input and adds it to the cache.
• get(func, ...args): Retrieves the result of func called with the provided args. If the result is already cached for those specific arguments, it returns the cached value. Otherwise, it calls func with args, caches the result, and returns it.
• Dynamic Strategy Selection: The cache must automatically determine a suitable strategy for caching based on the types of arguments passed to the function. For simple types (numbers, strings, booleans), a simple equality check might suffice. For objects and arrays, stringification might be necessary. The cache should be robust enough to handle a mix of argument types.
• Cache Key Generation: The cache key should be generated based on the function and its arguments. The key generation should be consistent, meaning the same function and arguments should always produce the same key.

Expected Behavior:

• The cache should correctly store and retrieve results for functions with different argument types.
• The cache should avoid unnecessary recomputation by returning cached results when appropriate.
• The cache should handle edge cases gracefully, such as functions that return undefined or null.
• The cache should not modify the original function.

Edge Cases to Consider:

• Functions with no arguments.
• Functions with arguments of mixed types.
• Functions that return objects or arrays.
• Functions that return undefined or null.
• Functions that throw errors. (The cache should not crash if the function throws an error; it should return the error.)
• Functions with arguments that are themselves functions.

Examples

Example 1:

Input:
const cache = new MegamorphicCache();
const add = (a, b) => a + b;
const result1 = cache.get(add, 2, 3);
const result2 = cache.get(add, 2, 3);

Output:
result1: 5
result2: 5
Explanation: The first call to `cache.get(add, 2, 3)` calculates 2 + 3 = 5, caches the result, and returns 5. The second call returns the cached value 5 without recomputation.

Example 2:

Input:
const cache = new MegamorphicCache();
const greet = (name) => `Hello, ${name}!`;
const result1 = cache.get(greet, "Alice");
const result2 = cache.get(greet, "Bob");

Output:
result1: "Hello, Alice!"
result2: "Hello, Bob!"
Explanation: The first call calculates "Hello, Alice!" and caches it. The second call calculates "Hello, Bob!" and caches it, as the arguments are different.

Example 3:

Input:
const cache = new MegamorphicCache();
const objFunc = (obj) => obj.value;
const obj1 = { value: 10 };
const obj2 = { value: 10 }; // Different object instance, same value
const result1 = cache.get(objFunc, obj1);
const result2 = cache.get(objFunc, obj2);

Output:
result1: 10
result2: 10
Explanation:  The cache should recognize that `obj1` and `obj2` have the same `value` property and return the cached result. Stringification or a deep comparison might be used internally to achieve this.

Constraints

• The MegamorphicCache class should be implemented in JavaScript.
• The cache should have a maximum size of 100 entries. (This is to prevent unbounded memory usage.)
• The time complexity of get should be, on average, O(1).
• The space complexity of the cache should be proportional to the number of cached entries.
• The cache key generation should be deterministic.

Notes

• Consider using JSON.stringify for caching objects and arrays, but be aware of its limitations (e.g., circular references).
• You might want to explore different caching strategies based on the argument types.
• Error handling is important. The cache should not crash if the function throws an error.
• Think about how to handle functions with arguments that are themselves functions. These should be treated as part of the arguments.
• The implementation should be reasonably efficient and avoid unnecessary computations. A simple equality check is sufficient for primitive types. For objects and arrays, consider a deep comparison or stringification.