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Many computer programs have graphical user interfaces (GUIs), which need goodlayout to make efficient use of the available screen real estate. Most GUIs donot have a fixed layout, but are resizable and able to adapt themselves.Constraints are a powerful tool for specifying adaptable GUI layouts: they areused to specify a layout in a general form, and a constraint solver is used tofind a satisfying concrete layout, e.g.\ for a specific GUI size. Theconstraint solver has to calculate a new layout every time a GUI is resized orchanged, so it needs to be efficient to ensure a good user experience. Oneapproach for constraint solvers is based on the Gauss-Seidel algorithm andsuccessive over-relaxation (SOR).  Our observation is that a solution after resizing or changing is similar instructure to a previous solution. Thus, our hypothesis is that we can increasethe computational performance of an SOR-based constraint solver if we reuse thesolution of a previous layout to warm-start the solving of a new layout. Inthis paper we report on experiments to test this hypothesis experimentally forthree common use cases: big-step resizing, small-step resizing and constraintchange. In our experiments, we measured the solving time for randomly generatedGUI layout specifications of various sizes. For all three cases we found thatthe performance is improved if an existing solution is used as a startingsolution for a new layout.

Speeding up SOR Solvers for Constraint-based GUIs with a Warm-Start Strategy