ATGBuilder: Graph Learning for Android Activity Transition Graphs

arXiv·low signal

Cui et al. present ATGBuilder, a feature-assisted graph-learning method with seed supervision for constructing Android Activity Transition Graphs (ATGs) that model GUI navigation. It targets the known gaps of static analysis (missing valid transitions, extracting infeasible ones) and dynamic exploration (incomplete coverage). Relevant to mobile test-generation and GUI-agent navigation tooling.