I knew the answer involved a hashmap plus a doubly linked list but explaining why out loud while also coding it was harder than I anticipated.
Start by clarifying requirements and constraints, then propose a hash map combined with a doubly linked list to achieve O(1) operations. Walk through the design, implement the core methods, and discuss trade-offs and edge cases.
Pro tip: Mention that you would use a doubly linked list with sentinel nodes to simplify edge cases, and that you would consider thread-safety if the cache is shared across threads.
Ask about capacity limits, thread-safety, and whether keys/values are generic. Confirm that get and put must be O(1) and that eviction is based on least recent use.
Explain that a hash map provides O(1) access to nodes, and a doubly linked list maintains recency order. Together they enable O(1) get, put, and eviction.
Detail how get moves the accessed node to the front (most recently used), and put inserts or updates a node, moving it to the front and evicting the tail if capacity is exceeded.
Write clean code for the LRU cache class, using sentinel head and tail nodes to avoid null checks. Include helper methods for adding and removing nodes.
State that all operations are O(1) time and O(capacity) space. Discuss edge cases like capacity 0 or 1, updating existing keys, and thread-safety if needed.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Clarify the in-place constraint and confirm matrix dimensions, then present the layer-by-layer rotation approach. Explain the four-way swap for each element in a layer, and analyze time and space complexity.
Pro tip: Mention that you can also achieve the rotation by first transposing the matrix and then reversing each row, which is simpler to implement and less error-prone, but still in-place.
Confirm that the matrix is n x n, rotation is 90 degrees clockwise, and no additional matrix can be allocated. Ask if the matrix can be modified in place.
Decide between layer-by-layer four-way swapping or transpose-then-reverse. Both are O(n^2) time and O(1) space; pick the one you can explain most clearly.
For layer-by-layer: iterate over each layer from outermost to innermost, and for each element in the top row of the layer, perform a four-way swap with corresponding elements on the right, bottom, and left sides.
State that time complexity is O(n^2) since each element is visited once, and space complexity is O(1). Mention edge cases like n=0 or n=1.
Walk through a 3x3 or 4x4 matrix to verify the rotation, ensuring indices are correct and no element is overwritten prematurely.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.