oh sorry.. i saved the complete ans in my draft and posted half ( as i got
interrupted when i ws typing) and so sent incomplete reply,..

here is my complete solution. hope it works.. let me know..if it fails
somewhere.. though i have tried it... on some test cases



Given Input Array A

form the prefix sum array P of A.

i.e P[i] = A[1] + A[2] + ... + A[i]

Now create another array Q of pairs (Value, Index)

such that

Q[i].Value = P[i].
Q[i].Index = i

Now sort that array Q, considering only Q[i].Value for comparison.

We get a new sorted array Q' such that Q'[i].Value  <= Q'[i+1].Value

Now walk the array Q' and find the minimum positive value of Q'[i+1].Value -
Q'[i].Value, considering only those i for which Q'[i+1].Index > Q'[i].Index



Time complexity o( nlogn)



On Thu, Feb 3, 2011 at 6:58 PM, sankalp srivastava <
[email protected]> wrote:

> @above guy with cheers and all and snehal
>
> the best way to prove wrong is by a test case , so ,
>
> -1 -2 3 4
>
> Ricky's solution will give the answer as 4 , while the answer is 7
>
> @snehal .
> [quote]if indices starting at 1
> bothers you then take
>
> P[i]= A[0]  + A[1] + .... + A[i]
> its one and the same thing.. [\Quote]
> I'm really not that stupid to bother about an off-by-one error :-)
> Your algo rephrased :-
>  P[i] = A[1] + A[2] + … + A[i]
> so ,
> P[1]=-1
> P[2]=-3
> P[3]=0
> P[4]=4
>
> Q[i].Value = P[i].
> Q[i].Index = i
>
> So ,
>
> Q[1]=-1 , 1
> Q[2]=-3 , 2
> Q[3]=0 , 3
> Q[4]=4 , 4
>
> Now , as u said , let's sort it
>
> new Q={{4 , 4} ,{0 , 3} ,{-1 , 1} ,{-3 , 3}}
> You din mention anything after this  , so I dunnoe what you plan up
> from  here . How are we going to get the answer {3 , 4 } from here ?
>
> Now ,
>
>
> On Feb 2, 10:06 pm, Ricky <[email protected]> wrote:
> > Hi you can try the following code snippet:
> >         int array[] = {11, -12, 15, -3, 8, -9, 1, 8, 10, -2};
> >         int length = 10;
> >
> >         int max = 0;
> >         int current = 0;
> >
> >         for (int i = 0; i < length; i++)
> >         {
> >                 current += array[i];
> >                 max = max > current ? max : current;
> >         }
> >         std::cout<<"Max is : "<<max;
> >
> > Cheers!!!!!!!!!!
> >
> > On Feb 2, 9:04 pm, snehal jain <[email protected]> wrote:
> >
> >
> >
> > > @ above
> > > didnt get you? why is the solution wrong? and if indices starting at 1
> > > bothers you then take
> >
> > > P[i]= A[0]  + A[1] + .... + A[i]
> > > its one and the same thing..
> >
> > > On Wed, Feb 2, 2011 at 6:02 PM, sankalp srivastava <
> >
> > > [email protected]> wrote:
> >
> > > > This solution is wrong , never has it been said that the indices will
> > > > occur from 1.....i (if that is the case , you don't need to sort ,
> > > > just return the maximum /minimum sum obtained as a result)
> >
> > > > The indices were b/w i..j such that 1<=i<=j<=n
> >
> > > > O(n) solution does not exist .The state space tree will have n! leaf
> > > > nodes(because there is some ordering on the input data , otherwise it
> > > > would have 2^n leaf nodes) .Traversing the tree will take O(log n!)
> > > > steps , or O(n log n)
> > > > In fact a slight modification to this , the subset sum problem id NP-
> > > > complete .
> > > > But with the Q[i] array , you can get the answer with simple
> recursion
> > > > ( or bfs or state space search or dp ) .
> >
> > > > On Feb 2, 1:33 pm, snehal jain <[email protected]> wrote:
> > > > > @ above
> > > > > its nt any homework question.. i found it a good question... aftr
> > > > spending a
> > > > > lot of time i came up with following solution
> >
> > > > > Given Input Array A
> >
> > > > > form the prefix sum array P of A.
> >
> > > > > i.e P[i] = A[1] + A[2] + … + A[i]
> >
> > > > > Now create another array Q of pairs (Value, Index)
> >
> > > > > such that
> >
> > > > > Q[i].Value = P[i].
> > > > > Q[i].Index = i
> >
> > > > > Now sort that array Q, considering only Q[i].Value for comparison.
> >
> > > > > We get a new sorted array Q’ such that Q’[i].Value Q’[i].Index
> >
> > > > > Time complexity o( nlogn)
> >
> > > > > and my O(n) which i posted earlier is giving incorrect result in
> some
> > > > > case..so ignore that..
> >
> > > > > so does there exist O(n) solution for it also.. i had tried a lot
> but
> > > > could
> > > > > not figure out. but i think it should exist as there is for the
> other
> > > > > variation..
> >
> > > > > On Tue, Feb 1, 2011 at 8:24 PM, sankalp srivastava <
> >
> > > > > [email protected]> wrote:
> >
> > > > > > You should not post homework problems .
> > > > > > 1)For divide and conquer :-
> > > > > >       Read about interval trees  , binary indexed trees ,
> segments
> > > > > > trees .
> > > > > >       Solve this using interval tree (By the time you solve a few
> > > > > > basic problems of interval tree , you would be able to figure out
> a
> > > > > > solution)
> >
> > > > > > the function to calculate the parent will be
> > > > > > 1) first check if the two are +ve
> > > > > > 2) if yes , join both of them and also iterate on the sides left
> by
> > > > > > both , to see if you can include them also (You only need to see
> the
> > > > > > positive elements , no negative elements )
> >
> > > > > > T(n)=2T(n/2)+O(n)
> >
> > > > > > I gan explain in detail , please correct me if im wrong
> >
> > > > > > Logic :- Basically in the subproblem , we would have founded the
> > > > > > maximum subarray in that well , subarray (short of words ) .So ,
> if we
> > > > > > want to ,we can only increase the solution in the next subarray
> (the
> > > > > > second subproblem )
> > > > > > So , there will be three cases
> >
> > > > > > Either the subarray , the most minimum sum in one of the
> subproblems
> > > > > > will be the answer
> > > > > > The answer will be from between the gap of the indices between
> the
> > > > > > solutions of the two subproblems
> > > > > > The answer will be any combination of the two
> >
> > > > > > All these three can be checked in O(n) itself .
> >
> > > > > > 2)Using DP(I don't know how many dp (pure dp i mean) algorithms
> are in
> > > > > > O(nlog n) .Never heard of any with the pure dp approach and an n
> log n
> > > > > > solution )
> >
> > > > > > DP(classical for maximum positive sum array ) can be done by
> going
> > > > > > through two loops
> >
> > > > > > dp[i]= minimum positive sum for an array with index (last index
> =i )
> > > > > > p[i]= start index corresponding to this dp[i]
> >
> > > > > > dp[i]= minimum sum condition ( for each i<j )
> > > > > > update p[i] accordingly .Then return  the minimum amongst dp[i]
> and
> > > > > > corresponding p[i] .
> >
> > > > > > This is a complete search , so I don't think it will get wrong .
> >
> > > > > > And i don't think it could be solved in O(n log n) (at least with
> > > > > > dp) .Because the search space tree would be of height O(log n)
> (with
> > > > > > no overlapping problems ) and dp lives upon overlapping
> subproblems .
> > > > > > Or may be , if someone could provide with a O( n log n) solution
> >
> > > > > > Regards ,
> > > > > > Sankalp Srivastava
> >
> > > > > > "I live the way I type , fast and full of errors "
> >
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