I have a sorted list implemented using linked nodes. I want to find a target element, which algorithm can I effectively use?

What is the worst-time complexity of the following function if the input list is of size n?

def mystery(my_list: ArrayList) -> None:
    my_queue = Queue(len(my_list))
    for item in my_list:
        my_queue.append(item)
    while not my_queue.is_empty():
        print(my_queue.serve())

What does the following code do?

def mystery(a_list: List) -> List:
    my_stack = Stack(len(a_list))
    my_list = List(len(a_list))
    
    for item in a_list:
        my_stack.push(item)
    while not my_stack.is_empty():
        my_list.append(my_stack.pop())
    return my_list

I'm implementing a new web browser, and want to keep track of the history of pages I've visited so that I can implement the back button on the web browser. What would be most appropriate ADT for this history?

Which of the following statements are true for a Circular Queue?

A new thrill ride has opened at Monash Clayton and you want to keep track of students wanting to ride it. What would be most appropriate to store the students?

The Queue ADT implements the following order when serving item:

What is the worst-time complexity of the following function if the input list has n elements?

def mystery(my_list: ArrayList) -> None:
    my_queue = Queue(len(my_list))
    
    count = 0
    for i in range (len(my_list)):
        my_queue.append(my_list[i])
        count+=1
        for i in range (count, 0, -1):
            print(count)

You want to create a shopping list of items you need from the supermarket. What would be most appropriate to store your items?