Greetings, aspiring coders! Today, we're going to delve deep into the complexities of data structures, specifically how to handle queries efficiently using JavaScript. This is a common problem often encountered in numerous data science and algorithmic problems. So let's gear up to unravel the mysteries of managing sorted sets and get our hands dirty with some interactive problem-solving!

Before delving into the task, let's understand how we can achieve sorted set functionality in JavaScript. Although JavaScript does not have a built-in data structure specifically for sorted sets, we can use arrays and objects to simulate this behavior.

To maintain a sorted set in JavaScript:

We can store elements in an array and keep it sorted upon every insertion or deletion. This approach will involve operations like using binary search to find the correct position for insertion or deletion:

• Inserting an element directly at the correct position using binary search takes O(N) in the worst case.
• Removing an element also involves finding their position using binary search, which takes O(N) in the worst case.
• Finding the smallest element greater than or equal to a given value can be achieved through a binary search, making this lookup operation O(log N).

Understanding these operations can help us utilize arrays and objects efficiently for our problem.

We are tasked with designing a JavaScript function named processQueries that can process a series of distinct requests or queries efficiently. The queries comprise a list of two integers — the type of operation and the operand.

There are three types of operations we'll handle:

• Adding an integer to the set (operation type 0)
• Removing an integer from the set (operation type 1). Whenever this operation is invoked, we can guarantee that the integer exists in the set.
• Finding the smallest integer that is greater than or equal to a given value (operation type 2).

The function should return the current size of the set when the operation type is 0 or 1, and the smallest possible integer when the operation type is 2. If such an integer does not exist, the function should return -1.

To understand the step-by-step breakdown of how the function works, let's go through a set of queries in detail.

const queries = [
    [0, 10],  // Add 10 to the set
    [2, 10],  // Find the smallest integer >= 10
    [0, 20],  // Add 20 to the set
    [1, 10],  // Remove 10 from the set
    [2, 10]   // Find the smallest integer >= 10
];

1. First Query: [0, 10]

   • Operation type 0: Add 10 to the set.
   • Current set after adding 10: [10]
   • We then sort the set. Since there is only one element, the set remains [10].
   • Append the current size of the set (1) to results.
   • results now: [1]

2. Second Query: [2, 10]

   • Operation type 2: Find the smallest integer that is greater than or equal to 10.
   • Current set: [10]
   • The smallest integer >= 10 is 10.
   • Append 10 to results.
   • results now: [1, 10]

3. Third Query: [0, 20]

   • Operation type 0: Add 20 to the set.
   • Current set after adding 20: [10, 20]
   • We then sort the set. The sorted set remains [10, 20].
   • Append the current size of the set (2) to results.
   • results now: [1, 10, 2]

4. Fourth Query: [1, 10]

   • Operation type 1: Remove 10 from the set.
   • Current set before removing 10: [10, 20]
   • Remove 10 from the set. The set becomes [20].
   • Append the current size of the set (1) to results.
   • results now: [1, 10, 2, 1]

5. Fifth Query: [2, 10]

   • Operation type 2: Find the smallest integer that is greater than or equal to 10.
   • Current set: [20]
   • The smallest integer >= 10 is 20.
   • Append 20 to results.
   • results now: [1, 10, 2, 1, 20]

The function thus processes each query step-by-step and constructs the results array as [1, 10, 2, 1, 20].