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Model the file system as a tree of nodes (directories and files) with a root node, and implement path resolution by splitting the absolute path and traversing from the root. For each operation, validate the path and enforce strict error handling (e.g., no auto-creation of intermediate directories). Then analyze time/space complexity and discuss edge cases like root path, invalid paths, and missing parents.
Pro tip: Explicitly state your assumptions about path format (e.g., no trailing slashes, no '.' or '..') and error types (e.g., throwing exceptions vs. returning error codes) before diving into implementation. This shows clarity and prevents misunderstandings.
Ask clarifying questions about path format, error handling (exceptions vs. return values), and whether operations like ls should list only immediate children or recursively. Confirm that intermediate directories must exist for all operations.
Define a Node class with a name, type (file/directory), and for directories, a map of children; for files, store content as a string or list of strings. Use a root node to represent '/'.
Write a helper to resolve a path to its parent directory and final component, validating each segment. Implement each operation (ls, mkdir, createFile, appendToFile, readFile) using this helper, ensuring strict error handling for missing parents or invalid paths.
Discuss time complexity (O(k) per operation where k is path depth) and space complexity (O(total nodes)). Cover edge cases: root path, empty path, paths with trailing slashes, non-existent parents, and operations on wrong node types.
Walk through example scenarios (e.g., mkdir /a/b, createFile /a/b/c.txt, appendToFile /a/b/c.txt 'hello', readFile /a/b/c.txt) and error cases (e.g., mkdir /x/y without /x). Mention potential optimizations like caching or using a trie.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Easier than part A but they pushed hard on the trade-off discussion.
Start by clarifying requirements (fixed-size, O(1) ops) and then present a circular queue using a fixed-size array with head and tail indices, explaining how modulo arithmetic enables wrap-around. Implement each operation in O(1) and then compare with a doubly linked list, highlighting trade-offs in memory, cache locality, and complexity.
Pro tip: Mention that a circular array avoids per-node allocation overhead and provides better cache performance, which is crucial for high-throughput systems like Snowflake's data cloud. Also, discuss how you would handle edge cases like full/empty conditions without wasting a slot (e.g., using a size counter).
Confirm that the queue has a fixed capacity, all operations must be O(1), and that thread-safety is not required unless specified. Ask about expected usage patterns to justify design choices.
Use a fixed-size array of capacity N, with head and tail indices and a size counter (or a boolean flag) to distinguish full vs. empty. Explain how enqueue and dequeue update indices using modulo arithmetic.
Walk through each operation: enQueue (check full, place at tail, increment tail and size), deQueue (check empty, retrieve from head, increment head, decrement size), Front/Rear (return elements at head/tail), isEmpty/isFull (check size). Emphasize constant time.
Discuss that a doubly linked list also gives O(1) operations but uses extra memory per node (pointers) and has poorer cache locality. A circular array is more memory-efficient and faster in practice due to contiguous memory.
Mention handling of full/empty conditions, potential overflow of indices (use modulo), and possible optimizations like using bitwise AND if capacity is a power of two. Also, note that resizing is not needed for fixed-size.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.