The timing requirements of real-time systems can be guaranteed by the well-designed scheduling. The analysis of such scheduling inputs an abstract task model of the system and outputs a diagnostic regarding the practicability of the timing requirements. Task models have evolved from periodic models to more sophisticated graph-based ones, among which the digraph real-time (DRT) task model is the most applicable because of its good expressiveness and analysis efficiency. However, the DRT model can't support the precedence constraints within or between tasks. In this paper, we propose a new task model, called the DRTPC model, that extends the DRT model to support the precedence constraint. Further, based on our model, we present a uniprocessor schedulability analysis algorithm for the static priority scheduling, and introduce an optimization technique to improve the analysis efficiency. Our experiments show that, despite the high computational complexity of the problem, our approach scales very well for large sets of tasks with precedence constraints.