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TIP102 Unit 5 Session 2 Standard (Click for link to problem statements)

Problem Highlights

• 💡 Difficulty: Easy
• ⏰ Time to complete: 10-15 mins
• 🛠️ Topics: Linked Lists, Traversal

1: U-nderstand

Understand what the interviewer is asking for by using test cases and questions about the problem.

• Established a set (2-3) of test cases to verify their own solution later.
• Established a set (1-2) of edge cases to verify their solution handles complexities.
• Have fully understood the problem and have no clarifying questions.
• Have you verified any Time/Space Constraints for this problem?

• What happens if n is greater than the length of the linked list?
  • The function should return all the nodes in the linked list.
• What happens if n is 0?
  • The function should return an empty list.

HAPPY CASE
Input: head = Node("Daisy") -> Node("Mario") -> Node("Toad") -> Node("Yoshi"), n = 3
Output: ["Daisy", "Mario", "Toad"]
Explanation: The function returns the values of the first 3 nodes.

EDGE CASE
Input: head = Node("Daisy") -> Node("Mario"), n = 5
Output: ["Daisy", "Mario"]
Explanation: Since `n` is greater than the length of the linked list, the function returns the values of all nodes.

2: M-atch

Match what this problem looks like to known categories of problems, e.g. Linked List or Dynamic Programming, and strategies or patterns in those categories.

For Linked List problems, we want to consider the following approaches:

• Traversal of a linked list
• Limiting the output based on a count

3: P-lan

Plan the solution with appropriate visualizations and pseudocode.

General Idea: Traverse the linked list, collecting the values of the nodes until you reach n nodes or the end of the list.

1) Initialize an empty list `result` to store the values.
2) Initialize a pointer `current` to the head of the linked list and a counter `count` to 0.
3) Traverse the linked list:
    a) Append the value of the current node to the `result` list.
    b) Move the pointer to the next node and increment the counter.
    c) Stop if the counter reaches `n`.
4) Return the `result` list.

⚠️ Common Mistakes

• Not handling cases where n is greater than the length of the linked list.
• Forgetting to return an empty list when n is 0.

4: I-mplement

Implement the code to solve the algorithm.

class Node:
    def __init__(self, value, next=None):
        self.value = value
        self.next = next

# For testing
def print_linked_list(head):
    current = head
    while current:
        print(current.value, end=" -> " if current.next else "\n")
        current = current.next

def top_n_finishers(head, n):
    result = []
    current = head
    count = 0
    
    while current and count < n:
        result.append(current.value)
        current = current.next
        count += 1
    
    return result

5: R-eview

Review the code by running specific example(s) and recording values (watchlist) of your code's variables along the way.

• Verify the output for various values of n to ensure the function behaves correctly.

Example:

head = Node("Daisy", Node("Mario", Node("Toad", Node("Yoshi"))))

# Test with n = 3
print(top_n_finishers(head, 3))  # Expected Output: ["Daisy", "Mario", "Toad"]

# Test with n = 5
print(top_n_finishers(head, 5))  # Expected Output: ["Daisy", "Mario", "Toad", "Yoshi"]

6: E-valuate

Evaluate the performance of your algorithm and state any strong/weak or future potential work.

• Time Complexity: O(N) where N is the smaller of n or the length of the linked list.
• Space Complexity: O(N) for storing the output list of node values.