Coding Interview Patterns and Complexity Refresh

Analyze the time and space complexity of a Java solution, including amortized costs.

Solve an array or string problem using a hash-based lookup strategy.

Solve a fixed-window or variable-window problem using the sliding-window pattern.

Solve a sorted-array problem using opposing or same-direction two pointers.

Use prefix sums to answer repeated range queries or count target subarrays.

Merge overlapping intervals and justify the chosen sort order.

Apply binary search to a monotonic answer space.

Solve and present an unseen coding problem within 40 minutes, stating assumptions, edge cases, complexity, and executable tests.