When the binary search is used to perform operations on a sorted set, the number of iterations can always be reduced on the basis of the value that is being searched. You can see in the above snapshot of finding the mid element. The analogy of binary search is to use the information that the array is sorted and reduce the time complexity to O(log n).
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Given a string containing digits from 2-9 inclusive, return all possible letter combinations that the number could represent. Return the answer in any order.
A mapping of digits to letters (just like on the telephone buttons) is given below. Note that 1 does not map to any letters.
Example 1:
Input: digits = "23"
Output: ["ad","ae","af","bd","be","bf","cd","ce","cf"]
Example 2:
Input: digits = ""
Output: []
Example 3:
Input: digits = "2"
Output: ["a","b","c"]
Constraints:
0 <= digits.length <= 4
digits[i] is a digit in the range ['2', '9'].
A mapping of digits to letters (just like on the telephone buttons) is given below. Note that 1 does not map to any letters.
Example 1:
Input: digits = "23"
Output: ["ad","ae","af","bd","be","bf","cd","ce","cf"]
Example 2:
Input: digits = ""
Output: []
Example 3:
Input: digits = "2"
Output: ["a","b","c"]
Constraints:
0 <= digits.length <= 4
digits[i] is a digit in the range ['2', '9'].