Human guided evolution of xul user interfaces

Graphical user interface design is a time consuming, expensive, and complex software design process. User interface design is both art and science in that we use both objective and subjective design metrics to evaluate interfaces. An automated process that relies on both subjective and objective metrics to guide the evolution of effective, personalized user interfaces could significantly change current GUI development and maintenance practice. This paper uses an interactive genetic algorithm to evolve XUL user interface layouts by combining objective and subjective metrics. The genetic algorithm encodes expert knowledge from prominent usability guidelines as objective heuristics. Further, the graphical user interface developer (or user!) biases and guides the evolution of the interfaces by subjectively evaluating and selecting the “best ” and “worst ” interfaces from a small set of displayed interface prototypes. We explore how the selection of individuals from the population to be displayed to the user for subjective evaluation affects the convergence of the genetic algorithm and show that our methodology can produce effective interfaces that reflect subjective user-preferred aesthetics