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Stream processing applications executed on multiprocessor systems usually contain cyclic data dependencies due to the presence of bounded FIFO buffers and feedback loops, as well as cyclic resource dependencies due to the usage of shared processors. In recent works it has been shown that temporal analysis of such applications can be performed by iterative fixed-point algorithms that combine dataflow and response time analysis techniques. However, these algorithms consider resource dependencies based on the assumption that tasks on shared processors are enabled simultaneously, resulting in a significant overestimation of interference between such tasks. This paper extends these approaches by integrating an explicit consideration of precedence constraints with a notion of offsets between tasks on shared processors, leading to a significant improvement of temporal analysis results for cyclic stream …