This article presents a top-down approach for analyzing sequential events i
n behavioral data. Analysis of behavioral sequential data often entails ide
ntifying patterns specified by the researchers. Algorithms were developed a
nd applied to analyze a kind of behavioral data, called discrete action pro
tocol data. Discrete action protocols consist of discrete user actions, suc
h as mouse clicks and keypresses. Unfortunately, the process of analyzing t
he huge volume of actions (typically, > 10(5)) is very labor intensive. To
facilitate this process, we developed an action protocol analyzer (ACT-PRO)
that provides two levels of pattern matching. Level one uses formal gramma
rs to identify sequential patterns. Level two matches these patterns to a h
ierarchical structure. ACT-PRO can be used to determine how well data fit t
he patterns specified by an experimenter. Complementarily, it can be used t
o focus an experimenter's attention on data that do not fit the prespecifie
d patterns.