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We consider the problem of computing the diameter of a unicycle graph (i.e., a graph with a unique cycle). We present an O (n) time algorithm for the problem, where n is the number of vertices of the graph. This improves the previous best O (n log ⁡ n) time solution [Oh and Ahn, ISAAC 2016]. Using this algorithm as a subroutine, we solve the problem of adding a shortcut to a tree so that the diameter of the new graph (which is a unicycle graph) is minimized; our algorithm takes O (n 2 log ⁡ n) time and O (n) space. The previous best algorithms solve the problem in O (n 2 log 3 ⁡ n) time and O (n) space [Oh and Ahn, ISAAC 2016], or in O (n 2) time and O (n 2) space [Bilò, ISAAC 2018]. • The paper presents a linear time algorithm for computing the diameter of unicycle graphs. • The paper gives a new algorithm which finds a new edge to add to a tree so that the diameter of the new graph is minimized. • The algorithms rely on certain domination relations among edges of the graphs. [ABSTRACT FROM AUTHOR]

We consider the problem of augmenting an n -vertex tree with one shortcut in order to minimize the diameter of the resulting graph. The tree is embedded in an unknown space and we have access to an oracle that, when queried on a pair of vertices u and v , reports the weight of the shortcut (u , v) in constant time. Previously, the problem was solved in O (n 2 log 3 ⁡ n) time for general weights [Oh and Ahn, ISAAC 2016], in O (n 2 log ⁡ n) time for trees embedded in a metric space [Große et al. , Int. J. FCS], and in O (n log ⁡ n) time for paths embedded in a metric space [Wang, Comput. Geom.]. Very recently an algorithm for general weights requiring O (n 2 log ⁡ n) time and O (n) space has been developed [Wang and Zhao, Theor. Comp. Science]. Finally, a (1 + ε) -approximation algorithm running in O (n + 1 / ε 3) has been designed for paths embedded in R d , for constant values of d [Große et al. , Int. J. FCS]. In this paper we design an asymptotic time-optimal algorithm for trees and general edge-weights that requires O (n 2) time and O (n log ⁡ n) space. Moreover, for trees embedded in a metric space, we design (i) an exact O (n log ⁡ n) -time algorithm and (ii) a (1 + ε) -approximation algorithm that runs in O (n + ε − 1 log ⁡ ε − 1) time. [ABSTRACT FROM AUTHOR]