How would you approach a medium-level LeetCode problem in an interview? Walk me through how you identify the pattern, choose a data structure, and reason about time and space complexity before coding.
Medium problems are usually combinations of familiar patterns rather than entirely new ideas. Strong candidates map the prompt to common techniques like sliding window, two pointers, BFS/DFS, binary search, or dynamic programming.
# Ask: is this about subarrays, traversal, shortest path, or state transitions?
Input size often determines which solutions are acceptable. If n can be 10^5, an O(n^2) approach is likely too slow, so constraints help narrow the search space before coding.
# n = 10^5 usually suggests O(n) or O(n log n)
Many medium problems are solved by using extra memory to reduce runtime, such as hash maps for O(1) lookup or stacks for monotonic structure. Interviewers want to hear why a tradeoff is worthwhile, not just see the final code.
# Example: use a set to avoid repeated scans
A good interview approach starts with a brute-force baseline, then improves it systematically. This shows problem-solving ability and makes the optimized solution easier to justify.
# Step 1: brute force
# Step 2: identify repeated work
# Step 3: cache or restructure
Before finishing, candidates should test their logic on empty inputs, single-element cases, duplicates, sorted inputs, and boundary values. This catches off-by-one errors and invalid assumptions early.
# Check: empty, one item, duplicates, min/max bounds
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