Abstract
Given an array A containing arbitrary (positive and negative) numbers, we
consider the problem of supporting range maximum-sum segment queries on A:
i.e., given an arbitrary range [i,j], return the subrange [i' ,j' ] \subseteq
[i,j] such that the sum of the numbers in A[i'..j'] is maximized. Chen and Chao
[Disc. App. Math. 2007] presented a data structure for this problem that
occupies {\Theta}(n) words, can be constructed in {\Theta}(n) time, and
supports queries in {\Theta}(1) time. Our first result is that if only the
indices [i',j'] are desired (rather than the maximum sum achieved in that
subrange), then it is possible to reduce the space to {\Theta}(n) bits,
regardless the numbers stored in A, while retaining the same construction and
query time. We also improve the best known space lower bound for any data
structure that supports range maximum-sum segment queries from n bits to
1.89113n - {\Theta}(lg n) bits, for sufficiently large values of n. Finally, we
provide a new application of this data structure which simplifies a previously
known linear time algorithm for finding k-covers: i.e., given an array A of n
numbers and a number k, find k disjoint subranges [i_1 ,j_1 ],...,[i_k ,j_k ],
such that the total sum of all the numbers in the subranges is maximized.
