LeetCode is a popular platform for coding enthusiasts to improve their skills and prepare for technical interviews. One of the most commonly encountered coding problems on LeetCode is the First Bad Version problem, which requires a binary search algorithm to find the first bad version within a given range of versions.
In this article, we will provide a detailed explanation of the problem statement and various approaches to solving it. Additionally, we will analyze the time and space complexity of each solution and discuss their pros and cons. By the end of this article, you will have a thorough understanding of the First Bad Version problem, which will help you approach it with confidence during coding challenges and technical interviews.
Problem Statement:
Consider that you are a product manager and currently leading a team to develop a new product. Unfortunately, the latest version of your product fails the quality check. Since each version is developed based on the previous version, all the versions after a bad version are also bad.
Suppose you have n versions [1, 2, ..., n] and you want to find out the first bad one, which causes all the following ones to be bad.
You are given an API bool isBadVersion(version) that will return whether the version is bad. Implement a function to find the first bad version. You should minimize the number of calls to the API.
For Example:
Given n = 5, and version = 4 is the first bad version.
call isBadVersion(3) -> false
call isBadVersion(5) -> true
call isBadVersion(4) -> true
Then 4 is the first bad version.
Explanation:
What is an API this question talks about?
Well, putting it in simplest terms, an API is something that sends information back and forth between a website or app and a user. In our case, it is just a function that we can call as per our needs.
Now coming to the problem, all we need to do is to find the first version of the product that failed the quality check. Suppose we maintained a checklist of which product passed and which one failed, then our list would be like this -> [ true, true, true, { lots of true }, true, false, false, { lots of falses }, false ]. There exists a point from 1 to n where the product transits from being continuously good to being continuously bad.
Does this pattern remind you of something? Which problem-solving strategy can be applied here?
Algorithm Logic:
The problem can be solved by iterating over all the products from 1 to n and calling the API to check if the respective product is good or bad. But as we are asked to minimize the number of API calls, which in software development is a critical factor of an application's efficiency, we need to think of a better approach.
If the explanation above provoked the idea of binary search in your mind, then yes, you are absolutely right my friend. It is a straightforward implementation of binary search, except that instead of being given an array to use its values, we are given a function to call as per our need. So just as usual, we calculate the mid-value and then call the API, if it returns falls, it means we are in the zone of bad products and need to shift or search space to (mid-1), as mid is already a faulty product. We also assign this mid to our "res" variable which keeps track of the starting index of the bad product. If the API call returns true, it means we are in the range of good products and now we need to shift our left index of search space to mid+1.
C++ Code Solution for First Bad Version Problem:
Here is the code solution for the problem:
// The API isBadVersion is defined for you.
// bool isBadVersion(int version);
class Solution {
public:
int firstBadVersion(int n) {
long long int beg,last,mid;
beg = 1 , last = n;
long int pos = 1;
while(beg<=last){
// ensure you calculate mid values this way ,otherwise ,it would cause overflow
mid = beg + (last-beg)/2;
bool x = isBadVersion(mid);
if(x == true){
pos = mid;
last = mid-1;
}
else
beg = mid+1;
}
// return the first index of faulty product
return pos;
}
};
For any confusion, do comment below and feel free to ask.
Conclusion
By mastering the First Bad Version problem, you can enhance your coding skills and improve your chances in technical interviews. With the approaches discussed in this article, you can approach this problem with confidence and efficiency. So, keep practicing and take on new challenges to excel in your coding journey.
Frequently Asked Questions
1. What is the First Bad Version problem on LeetCode?
The First Bad Version problem is a coding problem on LeetCode that requires finding the first bad version in a given range using a binary search algorithm.
2. Why is the First Bad Version problem important for coding interviews?
The problem tests the ability to design efficient algorithms and optimize API calls. It is commonly encountered in coding interviews and helps candidates stand out.
3. What are some approaches to solving the First Bad Version problem?
Common approaches include recursive and iterative binary search algorithms. Other variations include linear search and checking every version, but they are less efficient.
4. How can one prepare for the First Bad Version problem?
Practice solving similar problems, master binary search algorithms, and familiarise yourself with the LeetCode platform. Reviewing solutions and discussing with peers can also be helpful.
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