As the performance requirements of today's real-time systems are on the rise, system engineers are increasingly forced to optimize and tune the execution time of real-time software. Apart from usual optimizations targeting the average-case performance of a program, the worst-case execution time bound (WCET) delivered by program analysis tools often has to be improved to meet all the deadlines and ensure a safe operation of the entire system. Modern computer architectures pose a significant challenge to this task due to their high complexity. Out-of-order execution, speculation, caches, buffers, and branch predictors highly depend on the execution history and are thus difficult to analyze precisely for WCET analysis tools. Time-predictable computer architectures overcome this problems by specifically designed hardware components that are amenable to static program analysis. A recently proposed alternative for caching executable code, i.e., instructions, is the so-called method cache. Instead of a traditional block-based cache design, the method cache operates on larger code blocks under the control of the compiler. Due to its design, the analysis of the method cache is simplified. At the same time, such a system now highly depends on the compiler and its ability to form suitable code blocks for caching. We propose a simple function splitting technique that derives a suitable partitioning of the basic blocks in a program, targeting the method cache of the time-predictable processor Patmos. Our approach exploits dominance properties to form code regions respecting the method cache's parameters as well as constraints of Patmos' instruction set architecture. Experimental results show that the method cache can be competitive with typical instruction cache configurations given the right splitting.