  Next-to-leading logarithmic final-state resummed predictions have
traditionally been calculated, manually, separately for each observable. In
this article we derive NLL resummed results for generic observables. We
highlight and discuss the conditions that the observable should satisfy for the
approach to be valid, in particular continuous globalness and recursive
infrared and collinear safety. The resulting resummation formula is expressed
in terms of certain well-defined characteristics of the observable. We have
written a computer program, CAESAR, which, given a subroutine for an arbitrary
observable, determines those characteristics, enabling full automation of a
large class of final-state resummations, in a range of processes.
