← Bytedance Interview Insights
I went straight to backtracking which was the right call, but explaining the pruning step cleanly took me longer than it should have.
Use backtracking to build combinations incrementally, ensuring each combination is of size k and numbers are in increasing order to avoid duplicates. Start with an empty list, iterate from a start index to n, add the current number, recurse with the next start index, then backtrack. Analyze time and space complexity based on the number of combinations and recursion depth.
Pro tip: Mention that you can prune the recursion when the remaining numbers are insufficient to reach size k, which optimizes the solution. Also, clarify that combinations are unordered, so you enforce increasing order to avoid duplicates.
Confirm that combinations are unordered and that numbers are distinct. Ensure you understand the input constraints and expected output format.
Explain that backtracking is ideal for generating all combinations because it explores choices systematically and allows pruning.
Design a helper function that takes the current combination, a start index, and the remaining count. At each step, iterate from start to n, add the number, recurse, then remove it.
Optimize by stopping the loop early when the number of remaining elements is less than needed to complete the combination.
State that time complexity is O(C(n, k) * k) due to copying combinations, and space complexity is O(k) for recursion depth, excluding output storage.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.