// Write a function that takes two arrays as input, 
// each array contains a list of A-Z; 
// Your program should return True if the 2nd array is a subset of 1st array, or False if not.

function isSubset(source, subset) {
    let isShared = true;
    // Create an object which will be used for store formatted subset object 
    // in order to reduce the duplicated string for a linear search later
    let sourceObject = {};
    let subsetObject = {};

    for (let i = 0; i < source.length; i++) {
        sourceObject[source[i]] = 1;
    }

    for (let i = 0; i < subset.length; i++) {
        subsetObject[subset[i]] = 1;
    }

    // Linear search for finding subset string
    for (let key in subsetObject) {
        if (!(key in sourceObject)) {
            isShared = false;
        }
    }

    return isShared;
}

console.log(isSubset(['A','B','C','D','E'], ['A','E','D'])); // true
console.log(isSubset(['A','B','C','D','E'], ['A','D','Z'])); // false
console.log(isSubset(['A','D','E'], ['A','A','D','E'])); // true

// Big-O notation explain 
// The minumum amount of loop for this function is (source.length * subset.length) + (source.length + subset.length)
// ex. isSubset(['A','B','C','D','E'], ['A','D','Z']) = (5 * 3) + (5 + 3) = 23 times
// if we increase input size from (3, 3) into (6, 6) the result time cosuming will be n ^ 2
// That is mean for Big-O notation,we got O(n ^ 2) (Because the new sizing is ^2 from the original sizing)