Looks dead simple until you realize sorting by value doesn't work.
Clarify the problem constraints (e.g., non-negative integers, return type) and then propose a greedy sorting approach with a custom comparator. Explain that by sorting the numbers as strings using a comparator that compares concatenations (a+b vs b+a), we can arrange them to form the largest number. Finally, discuss handling edge cases like all zeros and analyze time/space complexity.
Pro tip: Mention that the comparator must be transitive to ensure correct sorting, and note that in languages like Python, you can use functools.cmp_to_key to implement it. Also, be prepared to discuss why a simple descending lexicographic sort fails (e.g., '9' vs '34').
Ask about input size, number ranges, whether numbers can be negative, and expected output format (string vs integer). Identify edge cases like all zeros or single element.
Explain that to maximize the concatenated number, we should sort the numbers such that for any two numbers a and b, if a+b > b+a (as strings), then a should come before b.
Describe how to implement the comparator, e.g., using a custom sort function or converting to strings and using a key. Mention that the comparator is transitive and thus sorting is valid.
After sorting, concatenate the strings. If the result starts with '0', return '0' (all zeros case). Otherwise, return the concatenated string.
State that time complexity is O(n log n) due to sorting, with O(n) space for the strings. Briefly mention that a naive approach would be to try all permutations (O(n!)) which is infeasible.
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