Problem
A string is a valid parentheses string (denoted VPS) if it meets one of the following:
- It is an empty string
""
, or a single character not equal to"("
or")"
, - It can be written as
AB
(A
concatenated withB
), whereA
andB
are VPS’s, or - It can be written as
(A)
, whereA
is a VPS.
We can similarly define the nesting depth depth(S)
of any VPS S
as follows:
depth("") = 0
depth(C) = 0
, whereC
is a string with a single character not equal to"("
or")"
.depth(A + B) = max(depth(A), depth(B))
, whereA
andB
are VPS’s.depth("(" + A + ")") = 1 + depth(A)
, whereA
is a VPS.
For example, ""
, "()()"
, and "()(()())"
are VPS’s (with nesting depths 0, 1, and 2), and ")("
and "(()"
are not VPS’s.
Given a VPS represented as string s
, return the nesting depth of s
.
Examples
Example 1:
Input: s = "(1+(2*3)+((8)/4))+1"
Output: 3
Explanation: Digit 8 is inside of 3 nested parentheses in the string.
Example 2:
Input: s = "(1)+((2))+(((3)))"
Output: 3
Solution
Method 1 - Using counters
To determine the nesting depth of a valid parentheses string:
- Initialize a counter
current_depth
to track the current depth as we traverse the string. - Initialize a variable
max_depth
to keep track of the maximum depth encountered. - Iterate through each character in the string:
- Increment
current_depth
when encountering an opening parenthesis(
. - Update
max_depth
ifcurrent_depth
exceeds it. - Decrement
current_depth
when encountering a closing parenthesis)
.
- Increment
- Return the
max_depth
as the nesting depth of the string.
Code
Java
class Solution {
public int maxDepth(String s) {
int currentDepth = 0;
int maxDepth = 0;
for (char c : s.toCharArray()) {
if (c == '(') {
currentDepth++;
if (currentDepth > maxDepth) {
maxDepth = currentDepth;
}
} else if (c == ')') {
currentDepth--;
}
}
return maxDepth;
}
}
Python
class Solution:
def maxDepth(self, s: str) -> int:
current_depth = 0
max_depth = 0
for c in s:
if c == '(':
current_depth += 1
if current_depth > max_depth:
max_depth = current_depth
elif c == ')':
current_depth -= 1
return max_depth
Complexity
- ⏰ Time complexity:
O(n)
, wheren
is the length of the string, since we traverse the string once. - 🧺 Space complexity:
O(1)
, because we use a fixed amount of additional space regardless of the input size.