1-bit and 2-bit Characters
Problem Description​
We have two special characters:
- The first character can be represented by one bit
0
. - The second character can be represented by two bits (
10
or11
).
Given a binary array bits
that ends with 0
, return true
if the last character must be a one-bit character.
Examples​
Example 1:
Input: bits = [1,0,0]
Output: true
Explanation: The only way to decode it is two-bit character and one-bit character.
So the last character is one-bit character.
Example 2:
Input: bits = [1,1,1,0]
Output: false
Explanation: The only way to decode it is two-bit character and two-bit character.
So the last character is not one-bit character.
Constraints​
1 <= bits.length <= 1000
bits[i]
is either0
or1
.
Solution for 1-bit and 2-bit Characters​
Approach 1: Increment Pointer​
Intuition and Algorithm​
When reading from the i-th position, if bits[i] == 0
, the next character must have 1 bit; else if bits[i] == 1
, the next character must have 2 bits. We increment our read-pointer i
to the start of the next character appropriately. At the end, if our pointer is at bits.length - 1
, then the last character must have a size of 1 bit.
Code in Different Languages​
- C++
- Java
- Python
class Solution {
public:
bool isOneBitCharacter(vector<int>& bits) {
int i = 0;
while (i < bits.size() - 1) {
i += bits[i] + 1;
}
return i == bits.size() - 1;
}
};
class Solution {
public boolean isOneBitCharacter(int[] bits) {
int i = 0;
while (i < bits.length - 1) {
i += bits[i] + 1;
}
return i == bits.length - 1;
}
}
class Solution(object):
def isOneBitCharacter(self, bits):
i = 0
while i < len(bits) - 1:
i += bits[i] + 1
return i == len(bits) - 1
Complexity Analysis​
Time Complexity: ​
Reason:
N
is the length ofbits
.
Space Complexity: ​
Reason: the space used by
i
.
Approach 2: Greedy​
Intuition and Algorithm​
The second-last 0
must be the end of a character (or, the beginning of the array if it doesn't exist). Looking from that position forward, the array bits
takes the form [1, 1, ..., 1, 0]
where there are zero or more 1
's present in total. It is easy to show that the answer is true
if and only if there is an even number of ones present.
In our algorithm, we will find the second last zero by performing a linear scan from the right. We present two slightly different approaches below.
Code in Different Languages​
- C++
- Java
- Python
class Solution {
public:
bool isOneBitCharacter(vector<int>& bits) {
int i = bits.size() - 2;
while (i >= 0 && bits[i] > 0) {
i--;
}
return (bits.size() - i) % 2 == 0;
}
};
class Solution {
public boolean isOneBitCharacter(int[] bits) {
int i = bits.length - 2;
while (i >= 0 && bits[i] > 0) {
i--;
}
return (bits.length - i) % 2 == 0;
}
}
class Solution(object):
def isOneBitCharacter(self, bits):
parity = bits.pop()
while bits and bits.pop(): parity ^= 1
return parity == 0
Complexity Analysis​
Time Complexity: ​
Reason:
N
is the length ofbits
.
Space Complexity: ​
Reason: the space used by
parity
(ori
).
References​
-
LeetCode Problem: 1-bit and 2-bit Characters
-
Solution Link: 1-bit and 2-bit Characters