This document proposes a trust behavior-based recommender system for software usage. It outlines constructing a model of trust behavior by observing users' normal usage, problem reflection, and correlation behaviors. The system would generate recommendations based on correlating these trust behaviors across users. An evaluation of the system achieved personalized recommendations as a concrete indicator of interest similarity and preferences. Future work includes improving user acceptance and further performance evaluations using real data.