  Stream constraint programming is a recent addition to the family of
constraint programming frameworks, where variable domains are sets of infinite
streams over finite alphabets. Previous works showed promising results for its
applicability to real-world planning and control problems. In this paper,
motivated by the modelling of planning applications, we improve the
expressiveness of the framework by introducing 1) the "until" constraint, a new
construct that is adapted from Linear Temporal Logic and 2) the @ operator on
streams, a syntactic sugar for which we provide a more efficient solving
algorithm over simple desugaring. For both constructs, we propose corresponding
novel solving algorithms and prove their correctness. We present competitive
experimental results on the Missionaries and Cannibals logic puzzle and a
standard path planning application on the grid, by comparing with Apt and
Brand's method for verifying eventuality conditions using a CP approach.
