Pretty simple linear scan, just iterate and accumulate when the element is between S and E.
Start by clarifying the problem constraints (e.g., array size, value ranges, duplicates) and edge cases (empty array, S > E). Then propose a straightforward O(n) single-pass solution that iterates through the array and accumulates elements within [S, E], discussing time and space complexity. If appropriate, mention potential optimizations or alternative approaches like sorting or using a Fenwick tree for multiple queries.
Pro tip: Demonstrate awareness of real-world scenarios by asking whether the function will be called multiple times on the same array; if so, pre-processing (e.g., sorting and prefix sums) could reduce per-query time to O(log n) or O(1). This shows you think beyond the immediate problem.
Ask about input size, value ranges, whether the array can be modified, and if multiple queries are expected. Confirm the inclusive range and handling of edge cases like S > E or empty array.
Propose iterating through each element and summing those within [S, E]. State the time complexity O(n) and space complexity O(1).
If multiple queries are likely, suggest sorting the array and using binary search to find the range, then prefix sums to get the sum in O(log n) per query after O(n log n) preprocessing. Alternatively, mention a segment tree or Fenwick tree for dynamic updates.
Ensure the solution handles empty arrays, S > E (return 0), and large sums (use appropriate data types). Write modular, readable code with meaningful variable names.
Walk through a few test cases, including edge cases, and clearly state the final time and space complexity of the chosen approach.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.