I encountered the following problem for which I couldn't quite find the appropriate solution.
The problem says for a given string having a specific hash value, find the lowest string (which is not the same as the given one) of the
same length and same hash value (if one exists). E.g. For the
following value mapping of alphabets: {a:0, b:1, c:2,...,z:25}
If the given string is: ady with hash value - 27. The
lexicographically smallest one (from all possible ones excluding the
given one) would be: acz
Solution approach I could think of:
I reduced the problem to Coin-Change problem and resorted to finding all possible combinations for the given sum. Out of all the obtained solutions, I sort them up and find the lowest (or the next smallest if the given string is smallest).
The problem however lies with finding all possible solutions (even in a DP approach) which might be inefficient for larger inputs.
My doubt is:
What solution strategy (possibly even Greedy) could give a better time complexity than above?
I cannot guarantee that this will give you a lower complexity, but a couple of things:1 you don't need to check all the space, just the space of lexicographic value less than or equal to the given string. 2: you can formulate it as an integer programming problem:
Assuming your character space is the letters, and each letter is given its number index[0-25] so a corresponds to 0, b to 1 and so forth. let x_i be the number of letters in your string corresponding to index i. You can formulate your problem as:
min sum_i(wi*xi)
st xi*ai = M
xi>=0,
sum_i(xi)=n
sum_i(wi*xi)<= N
xi integer
Where wi= 26^i, ai is equal to hash(letter(i)), n is the number of letters of the original string, N is the hash value of the original string. This is an integer programming problem so you can try plugging it to a solver. The original problem is very similar to subset sum problem with fixed subset size (where the hash values are the elements you are summing over, and the subset size is the length of the string) so you might also want to take a look at that, although as you will see from the answer it is a complicated problem.
Related
A string of length N (can be upto 10^5) is given which consists of only 0 and 1. We have to remove two substrings of length exactly K from the original string to maximize the number of consecutive 1's.
For example suppose the string is 1100110001and K=1.
So we can remove two substrings of length 1. The best possible option here is to remove the 0's at 3rd place and 4th place and get the output as 4 (as the new string will be 11110001)
If I try brute force it'll timeout for sure. I don't know if sliding window will work or not. Can anyone give me any hint on how to proceed? I am not demanding the full answer obviously, just some hints will work for me. Thanks in advance :)
This has a pretty straightforward dynamic programming solution.
For each index i, calculate:
The length of the sequence of 1s that immediately precedes it, if nothing has been removed;
The longest sequence of 1s that could immediately precede it, if exactly one substring is removed before it; and
The longest sequence of 1s that could immediately precede it, if exactly two substrings are removed before it.
For each index, these three values are easily calculated in constant time from the values for earlier indexes, so you can do this in a single pass in O(N) time.
For example, let BEST(i,r) be the best length immediately preceding position i after removing r substrings. If i >= K, then you can remove a substring ending at i and have BEST(i,r) = BEST(i-K,r-1) for r > 0. If string[i-1] = '1' then you could extend the sequence from the previous position and have BEST(i,r) = BEST(i-1,r)+1. Choose the best possibility for each i,r.
The largest value you find in step (3) is the answer.
I am given a string for example aaabb and i have to make it a palindrome with minimum number of shifts,what algorithm should i use to achieve that?
https://www.hackerrank.com/contests/sample-1-1/challenges/cyclic-palindrome
Please no code only algorithm
Idea 1:
You can use polynomial hashing to compute the hash of the shifted string in O(1) using the prefix sums of hashes for the initial string and for its reversed version. After that, you need to check that these two hashes are equal. You can just test all possible shifts and choose the smallest one that fits (the total time complexity is O(N)).
Idea 2:
Let's write the string twice. We need to find a palindrome of at least N characters. You can use Manacher's algorithm to find all such palindromes in linear time and choose the one that corresponds to the smallest shift.
Both solution have a linear time complexity, but the first one is slightly easier to code, while the second one is guaranteed to work for all possible inputs as it doesn't rely on lack of hash collisions.
Interesting thing to notice in palindrome string is there can be at most 1 type of character with odd frequency. i.e., abcccba a(2) b(2) c(3).
So while scanning string, maintain count of characters. If odd_count > 1, print -1
If odd_count = 1, you need to keep this type of character in middle, so shift string minimum times (either left or right shift) and check if it forms palindrome.
If odd_count = 0, you need to shift and check.
Got this question in a recent interview. Basic String compare with a little twist. I have an input String, STR1 = 'ABC'. I should return "Same/Similar" when the string to compare, STR2 has anyone of these values - 'ACB' 'BAC' 'ABC' 'BCA' 'CAB' 'CBA' (That is same characters, same length and same no of occurrences). The only answer struck at that moment was to proceed with 'Merge sort' or 'Quick Sort' since it's complexity is logarithmic. Is there any other better algorithm to achieve the above result?
Sorting both, and comparing the results for equality, is not a bad approach for strings of reasonable lengths.
Another approach is to use a map/dictionary/object (depending on language) from character to number-of-occurrences. You then iterate over the first string, incrementing the counts, and iterate over the second string, decrementing them. You can return false as soon as you get a negative number.
And if your set of possible characters is small enough to be considered constant, you can use an array as the "map", resulting in O(n) worst-case complexity.
Supposing you can use any language, I would opt for a python 'dictionary' solution. You could use 2 dictionaries having as keys each string's characters. Then you can compare the dictionaries and return the respective result. This actually works for strings with characters that appear more than once.
Suppose we have a string A of length n. And we have k <= n.
Now I want to know all distinct strings generated by cyclic shift of any segment of that string of length k, any number of times.
Ex: A = "asdfgh" and k=3.
Then possible permutations are "dasfgh" when segment "asd" is chosen for shifting. Now "dasfgh" can give another permutation "dfasgh" when segment "asf" is chosen.
I want to know if a specific given permutation can be formed or not by such shifts.
Can someone help me by providing some good algorithms or literature or link telling about best approach for solving such questions. I know backtracking can be used but it won't be efficient as n can be as large as 100000.
I am on an interview ride here. One more interview question I had difficulties with.
“A rose is a rose is a rose” Write an
algorithm that prints the number of
times a character/word occurs. E.g.
A – 3 Rose – 3 Is – 2
Also ensure that when you are printing
the results, they are in order of
what was present in the original
sentence. All this in order n.
I did get solution to count number of occurrences of each word in sentence in the order as present in the original sentence. I used Dictionary<string,int> to do it. However I did not understand what is meant by order of n. That is something I need an explanation from you guys.
There are 26 characters, So you can use counting sort to sort them, in your counting sort you can have an index which determines when specific character visited first time to save order of occurrence. [They can be sorted by their count and their occurrence with sort like radix sort].
Edit: by words first thing every one can think about it, is using Hash table and insert words in hash, and in this way count them, and They can be sorted in O(n), because all numbers are within 1..n steel you can sort them by counting sort in O(n), also for their occurrence you can traverse string and change position of same values.
Order of n means you traverse the string only once or some lesser multiple of n ,where n is number of characters in the string.
So your solution to store the String and number of its occurences is O(n) , order of n, as you loop through the complete string only once.
However it uses extra space in form of the list you created.
Order N refers to the Big O computational complexity analysis where you get a good upper bound on algorithms. It is a theory we cover early in a Data Structures class, so we can torment, I mean help the student gain facility with it as we traverse in a balanced way, heaps of different trees of knowledge, all different. In your case they want your algorithm to grow in compute time proportional to the size of the text as it grows.
It's a reference to Big O notation. Basically the interviewer means that you have to complete the task with an O(N) algorithm.
"Order n" is referring to Big O notation. Big O is a way for mathematicians and computer scientists to describe the behavior of a function. When someone specifies searching a string "in order n", that means that the time it takes for the function to execute grows linearly as the length of that string increases. In other words, if you plotted time of execution vs length of input, you would see a straight line.
Saying that your function must be of Order n does not mean that your function must equal O(n), a function with a Big O less than O(n) would also be considered acceptable. In your problems case, this would not be possible (because in order to count a letter, you must "touch" that letter, thus there must be some operation dependent on the input size).
One possible method is to traverse the string linearly. Then create a hash and list. The idea is to use the word as the hash key and increment the value for each occurance. If the value is non-existent in the hash, add the word to the end of the list. After traversing the string, go through the list in order using the hash values as the count.
The order of the algorithm is O(n). The hash lookup and list add operations are O(1) (or very close to it).