Reliability evaluation is a high costly process that is mainly carried out through fault injection or by means of analytical techniques. While the analytical techniques are fast but inaccurate, the fault injection is more accurate but extremely time consuming. This paper presents an hybrid approach combining analytical and fault injection techniques in order to evaluate the reliability of a computing system, by considering errors that affect both the data and the instruction cache. Compared to existing techniques, instead of targeting the hardware model of the cache (e.g., VHDL description), we only consider the running application (i.e., the software layer). The proposed approach is based on the Low-Level Virtual Machine (LLVM) framework coupled with a cache emulator. As input, the tool requires the application source code, the cache size and policy, and the target microprocessor instruction set. The main advantage of the proposed approach is the achieved speed up quantified in magnitude orders compared to existing fault injection techniques. For the validation, we compare the simulation results to those obtained with an FPGA-based fault injector. The similarity of the results proves the accuracy of the approach.