Linked Lists and Trees Questions

Dynamic and pointer based data structures including linked lists and tree structures commonly tested in interviews. For linked lists cover node based representation, traversal, insertion at head and tail, deletion, searching, reversing a list, detecting cycles, and tradeoffs versus array based lists. For trees cover basic concepts such as binary trees and binary search trees, tree node representation, insertion and deletion in search trees, recursion patterns, and traversal algorithms including depth first search with in order pre order and post order variants and breadth first search. Also include problem solving patterns such as recursion and iterative stack or queue based approaches, analysis of time and space complexity in plain terms, and common interview tasks such as lowest common ancestor, tree balancing awareness, and converting between representations. Practice includes implementing algorithms, writing traversal routines, and reasoning about correctness and performance.

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As an AI Engineer, explain node based linked lists including singly, doubly and circular variants. Show a node structure in pseudocode, explain traversal, insertion at head and tail, deletion and typical pointer manipulations. Discuss tradeoffs versus array based lists with respect to cache locality, random access, insertion and deletion costs, memory overhead and use cases in ML pipelines such as streaming datasets or representing computation graph chains.

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Implement level_order(root) in Python to perform breadth first traversal of a binary tree and return a list of lists containing node values for each depth level. Use an explicit queue and show sample tree input and output. Explain space complexity in terms of maximum width and tradeoffs when working with very wide trees in ML preprocessing.

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Implement deletion operation for an AVL tree in Python including updating node heights and performing rotations for LL, RR, LR and RL imbalance cases. Provide helper rotate functions, show the sequence after base BST deletion and explain why AVL maintains O(log n) height and deletion cost.

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Define a BinaryTree node class in Python with left and right children. Implement recursive inorder, preorder and postorder traversal functions that return lists of node values. Use an example tree and show expected traversals. Discuss call stack usage, time and space complexity and how traversal patterns differ for N-ary trees.

HardTechnical

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Design and implement a persistent immutable singly linked list in Python where cons(value) returns a new list head that shares structure with existing versions. Explain memory usage, structural sharing, time complexity for cons and append, and use cases for persistent lists in ML experiments and reproducibility.

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