Done precourse 1

[pranjay01]

No description provided.

[super30admin]

Let's evaluate each file one by one.

Exercise_1.py (Array-based Stack Implementation):

• Correctness: The implementation appears to be correct for a stack using a list. The push, pop, peek, size, and show methods are implemented appropriately. However, the pop method could be simplified by using list.pop() which is O(1) instead of manually deleting the last element.
• Time Complexity: The student claims O(1) for all operations. This is correct for push, pop (if using list.pop()), peek, size, and show. However, in the current implementation, the pop method uses del self.arr[-1] which is also O(1) in Python lists. So the time complexities are accurate.
• Space Complexity: O(n) is correct as the stack stores n elements.
• Code Quality: The code is clean and readable. The show method returns the list, which is appropriate. However, the pop method can be written more concisely by using the built-in pop method of lists. Also, the isEmpty method is implemented but not used in pop and peek? Actually, it is used in pop and peek. So that's good.
• Efficiency: The implementation is efficient. However, using del self.arr[-1] is equivalent to list.pop() but the latter is more idiomatic.

Suggestion for Exercise_1.py:

• In the pop method, you can simply write: return self.arr.pop() if not self.isEmpty() else None. This would be more straightforward.

Exercise_2.py (Linked List-based Stack Implementation):

• Correctness: The implementation has several issues.
  • The initialization sets up a dummy head and last node, but the connections are confusing. Typically, for a stack implemented with a linked list, we only need a head pointer (pointing to the top) and we push and pop from the head for O(1) operations.
  • The current push method seems to be adding at the end (tail) which would require O(n) for pop if we don't have a reference to the previous node. However, the student has implemented a doubly linked list? But the Node class is for singly linked list.
  • The pop method is implemented with a while loop that traverses the list to find the node before the last, which is O(n). This is inefficient for a stack.
  • The peek method is correct if we are maintaining a tail pointer, but the overall design is not standard.
• Time Complexity: The student claims O(1) for push, peek, size and O(n) for pop. This is accurate for the current implementation, but typically we want all stack operations to be O(1). The implementation can be improved by making the top of the stack the head of the list.
• Space Complexity: O(n) is correct.
• Code Quality: The code is a bit complex and not standard. The use of dummy nodes (head and last) is confusing. The variable names could be improved (e.g., tmpNode, lastNode). The pop method is overly complicated.
• Efficiency: The current implementation is inefficient for pop (O(n)). This can be improved to O(1) by reversing the direction of the linked list (i.e., push and pop at the head).

Suggestion for Exercise_2.py:

• Redesign the stack to have a single head pointer that points to the top element.
• Push: create a new node, set its next to the current head, and update head to the new node.
• Pop: if head is not None, save the head data, update head to head.next, and return the saved data.
• This way, both push and pop are O(1).

Exercise_3.py (Singly Linked List Implementation):

• Correctness: The implementation is incomplete and has errors.
  • The append method: It tries to use self.last which is not defined. The class does not have a 'last' attribute. Also, the head is initialized as a dummy node? This is not standard for a singly linked list. Typically, we have a head that is None for an empty list.
  • The find method: The loop condition is incorrect. The variable tmpNode is initialized with next pointing to self.head, but then we are updating tmpNode.next in the loop. This might lead to infinite loops or missing the first element. Also, the loop should traverse until current node is not None.
  • The remove method: Similarly, the logic is flawed. The use of prevNode and currNode is confusing. The initializations are incorrect (e.g., currNode = ListNode(None, self.head.next) but self.head.next might be None). Also, the method does not handle the case when the head is to be removed.
• Time Complexity: The student claims O(n) for append, find, remove which is correct for a singly linked list without tail pointer.
• Space Complexity: O(1) for the operations (excluding the storage for the list itself) is correct.
• Code Quality: The code is not well-structured. There are several syntax errors and logical errors. The use of dummy nodes is not consistent. The methods are not implemented correctly.
• Efficiency: The implementation is inefficient due to errors, but the intended operations are O(n) which is standard.

Suggestion for Exercise_3.py:

• For the singly linked list, start with self.head = None.
• Append: traverse to the end and add the new node. Or maintain a tail pointer to make append O(1).
• Find: start from self.head and traverse until you find the key or reach the end.
• Remove: use two pointers (prev and current) to traverse and remove the node.

Overall, the student has shown understanding of the concepts but the implementations for Exercise_2 and Exercise_3 have significant issues. Exercise_1 is mostly correct.

[super30admin]

Let's evaluate each file one by one.

Exercise_1.py (Array-based Stack Implementation):

• Correctness: The implementation appears to be correct for a stack using a list. The push, pop, peek, size, and show methods are implemented appropriately. However, note that the pop method returns the top element when popped, which is correct, but it uses del self.arr[-1] which is equivalent to self.arr.pop() but less efficient because it involves a function call and then a deletion. Also, the show method returns the entire list, which might be acceptable, but the problem might require printing the stack? The problem statement is not clear, so this might be acceptable.
• Time Complexity: The student claims O(1) for all operations. However, in Python, list.append and list.pop (for the last element) are amortized O(1), so push and pop are indeed O(1). The other operations are O(1). So the time complexity analysis is correct.
• Space Complexity: O(n) is correct as the stack stores n elements.
• Code Quality: The code is clean and readable. However, the pop method could be simplified by using list.pop directly. Also, the isEmpty method is defined but not used in the provided example, but it is good practice. The peek method returns None when the stack is empty, which is acceptable, but the problem might require raising an exception? The problem statement is not clear. Similarly, pop returns None when empty, which might be acceptable.
• Efficiency: Using del self.arr[-1] is less efficient than using self.arr.pop() because the latter is a built-in method optimized for this operation. Also, the pop method calls peek which then checks for emptiness again. This is redundant. We can do:
  def pop(self):
  if self.isEmpty():
  return None
  return self.arr.pop()
  This would be more efficient and concise.

Exercise_2.py (Linked List-based Stack Implementation):

• Correctness: The implementation has several issues.
  • The __init__ method initializes head and last to dummy nodes. This is unusual. Typically, we have a head pointer that points to the top of the stack.
  • The push method: It seems to be adding nodes at the end (like a queue) rather than at the head (for a stack). For a stack, we should push and pop from the same end (usually the head) to have O(1) operations. The current push method is adding at the tail, which would require O(n) to pop (because we need to find the previous node). However, the student has implemented a linked list that seems to be maintaining a pointer to the last node, but the pop method is traversing the list to find the node before the last, which is O(n). This is inefficient.
  • The pop method is traversing the list from the head to find the node before the last. This is O(n). For a stack, we should have O(1) pop. The student's time complexity analysis says O(n) for pop, which is correct for their implementation, but it is not optimal for a stack.
  • The peek method returns the last node's data, which is correct for their implementation (since they are using the tail as the top).
  • The isEmpty method is correct.
  • The currSize method is correct, but it is better to name it size for consistency.
• Time Complexity: As per the student's analysis: O(1) for push, peek, size and O(n) for pop. However, for a stack, we can achieve O(1) for all operations by using a singly linked list with insertion and deletion at the head.
• Space Complexity: O(n) is correct.
• Code Quality: The code is a bit convoluted. The use of dummy nodes (with data None) is unnecessary. The pop method is complex and inefficient. The variable names could be improved (e.g., tmpNode is not descriptive). Also, the pop method has a while loop that is hard to follow.
• Efficiency: The implementation is inefficient for pop. We can change the implementation to have the top of the stack at the head of the linked list. Then, push would be adding at the head, and pop would be removing from the head, both O(1). Also, we don't need a last pointer for a stack implemented with a linked list if we use the head as the top.

Exercise_3.py (Singly Linked List Implementation):

• Correctness:
  • The __init__ method initializes self.head as a dummy node (with data None and next None). This might be intended, but then the append method assumes the existence of a last pointer (which is not defined). The code has self.last.next.next which will cause an error because self.last is not defined. This indicates a major flaw.
  • The append method: It tries to use self.last which is not defined. Also, it doesn't handle the case when the list is empty. Typically, we would traverse to the end to append, which is O(n). But here, the code is incomplete.
  • The find method: It uses tmpNode = ListNode(None, self.head), which creates a new node pointing to the dummy head. Then it traverses with tmpNode.next = tmpNode.next.next, which is incorrect because it modifies the list structure. Also, it should be traversing without changing the list. The loop condition is also flawed: it checks tmpNode.next != None but then sets tmpNode.next = tmpNode.next.next, which might break the list. This method will not work correctly.
  • The remove method: Similarly, it uses two nodes prevNode and currNode, but the initialization is incorrect. prevNode is set to a node pointing to self.head, and currNode to a node pointing to self.head.next. Then in the loop, it updates prevNode.next and currNode.next in a way that might break the list. This method is also flawed.
• Time Complexity: The student claims O(n) for append, find, and remove, which is correct for a singly linked list, but the implementation is incorrect.
• Space Complexity: O(n) is correct.
• Code Quality: The code is poorly implemented. There are several errors and misunderstandings. The use of dummy nodes is not consistent, and the methods are not correctly implemented. The code lacks comments and clear logic.
• Efficiency: Even if implemented correctly, the operations are O(n), which is standard for a singly linked list without a tail pointer for append.

Overall, the student's solutions for Exercise_1 and Exercise_2 are partially correct but have efficiency and design issues. Exercise_3 is incorrect and incomplete.

Strengths:

• The student has attempted to analyze time and space complexity.
• For Exercise_1, the array-based stack is mostly correct and efficient.

Areas for Improvement:

• For Exercise_1, use the built-in list.pop method for better efficiency and simplicity.
• For Exercise_2, redesign the stack to have the top at the head of the linked list to achieve O(1) for both push and pop.
• For Exercise_3, the student needs to revisit the implementation of the singly linked list. They should avoid using dummy nodes unless necessary and ensure that the methods are correctly implemented. Specifically, the append method should traverse to the end, and the find and remove methods should traverse without modifying the list structure.

Given that two out of three solutions have major issues (Exercise_2 is inefficient and Exercise_3 is incorrect), the overall submission needs improvement.