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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.

HardTechnical
0 practiced
Design a concurrent singly linked list for a high-throughput in-memory queue used by ingestion workers. Discuss lock-based vs lock-free approaches, per-node vs coarse-grained locking, memory reclamation (hazard pointers/epoch), and how you would test for correctness under concurrency.
MediumTechnical
0 practiced
Given a singly linked list where each node has an extra 'random' pointer to any node or None, implement a Python function that returns a deep copy of the list. Aim for O(n) time and O(1) extra space (no hash map). Explain the three-step weaving/unweaving technique.
EasyTechnical
0 practiced
Implement a stack data structure using a singly linked list in Python supporting push, pop, peek, and is_empty operations. Discuss complexity and memory characteristics compared to a list/array-backed stack for frequent push/pop workloads.
MediumTechnical
0 practiced
Explain common recursion patterns on trees useful for data engineers: divide-and-conquer returning aggregated values (postorder), path-accumulation (root-to-leaf), and stateful traversal (preorder). For each pattern give a short example use-case in data processing (e.g., computing subtree aggregates, path-based filters).
EasyTechnical
0 practiced
Write a function in Python to reverse a singly linked list. Provide both an iterative O(n) time O(1) space solution and a recursive solution. For the recursive version, explain the stack usage and the maximum recursion depth for a list of length n. Show the Node class signature you assume.

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