Looked straightforward at first glance and then I started second-guessing myself on the bit manipulation.
First, clarify that the input is a list of integers, each representing a byte (0-255). Then, iterate through the list, using a state machine or bit manipulation to validate the UTF-8 encoding rules: single-byte characters start with 0, multi-byte characters start with a sequence of 1s followed by 0, and continuation bytes start with 10. Keep track of the number of expected continuation bytes and ensure they match.
Pro tip: Mention that you would handle edge cases like empty list, invalid start bytes (e.g., 0xFF), and incomplete sequences. Also, discuss the trade-off between using a state machine and bit manipulation for clarity and performance.
Confirm that the list contains integers in the range 0-255, each representing a byte. Ask if the list can be empty or if there are any constraints on length.
Explain the rules: 1-byte: 0xxxxxxx; 2-byte: 110xxxxx 10xxxxxx; 3-byte: 1110xxxx 10xxxxxx 10xxxxxx; 4-byte: 11110xxx 10xxxxxx 10xxxxxx 10xxxxxx. Continuation bytes always start with 10.
Iterate through the list. For each byte, determine if it's a start byte or continuation byte. If start byte, compute the number of expected continuation bytes and check that the following bytes are valid continuation bytes. Use bit masks to extract relevant bits.
Check for invalid start bytes (e.g., 0xFF, 0xFE), incomplete sequences at the end, and unexpected continuation bytes. Return false immediately upon any violation.
State that the algorithm runs in O(n) time and O(1) space. Walk through a few test cases: valid multi-byte sequences, invalid sequences, empty list.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Clarify that the problem is a shortest path on an unweighted graph where each 0-cell is a node and edges connect to 8 neighbors. Then choose BFS for optimality, or A* with Chebyshev distance heuristic for efficiency, and discuss trade-offs.
Pro tip: Mention that BFS is optimal for unweighted graphs, but A* with Chebyshev distance can be more efficient in practice; also handle edge cases like start/end being 1 or out of bounds.
Confirm matrix dimensions, movement rules (8 directions), and that only 0-cells are traversable. Ask about edge cases: start/end blocked, empty matrix, large size.
Treat each 0-cell as a node with edges to its 8 neighbors. For unweighted shortest path, BFS guarantees optimality; A* with Chebyshev distance can be faster but requires a consistent heuristic.
Use a queue for BFS, a 2D array for distances (or visited set), and iterate through 8 directions. Return distance when reaching bottom-right, or -1 if unreachable.
Time O(R*C) since each cell visited once; space O(R*C) for queue/visited. Mention bidirectional BFS or A* for potential speedup on large grids.
Walk through a small matrix, test blocked start/end, single cell, and unreachable cases. Verify 8-direction movement correctly includes diagonals.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.