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Kadane's Algorithm is not what this problem asks you about.
Your task is to maximize reminder modulo M, not sum itself.
If M=7 then 6 is better than 14, because 6 gives 6 modulo 7, and 14 gives 0 modulo 7 (and 6 is, obviously, more than 0).
Your solution will fail on following test
Here is my solution from a contest.
Well, I know what does the problem ask me about, but I think that we can modify Kadane's Algorithm to solve this problem. Sum solutions can be converted to Mod solutions.
I read the editorial of this problem and I almost got the idea but I prefer to edit my ideas. Please notify me if you can solve this problem by modifying Kadane's.
LL sum = 0 , ans = 0 ; set S ; S.insert(0) ; set :: iterator it ; for(int i=1;i<=n;i++){ sum += A[i] ; sum %= m ; it = S.upper_bound(sum) ; if(it != S.end()) ans = max(ans,sum-(*it)+m) ; else ans = max(ans,sum) ; S.insert(sum) ; }Here is my idea for this solution. Firstly as mentioned by I_love_Tanya_Romanova this problem is not what you have thought earlier. so , suppose you are maintaining curr_sum % m then you have to maximise the sum of the array ending at each index i then take maximum of all. let us consider curr_sum[i] denotes the sum of all elements from 1 to i % m now to maximise this there are two cases only decrease the smallest value less than curr_sum[i] from curr_sum which is obviously 0 else you can subtract the value just greater than curr_sum[i] (consider this value as x). we can see curr_sum[i] — x is negative so we have to add m to it which implies we have to maximise this (curr_sum[i] — x + m) or (m+curr_sump[i] — x) so take the smallest value greater than curr_sum[i] which can be easily find by maintaining a set (denoting by S in my code). hope this is useful in some way or other.