Negative Bias Temperature Instability (NBTI) is a major reliability issue in nanoscale VLSI systems. Previous work has shown how the exploitation of conventional optimization techniques can reduce the NBTI-induced aging in cache memories. Other works have proposed approaches that incorporate software directed data allocation strategies to partially recover from NBTI-induced aging in Scratchpad Memories(SPM). In this paper, we extend the existing software approach in order to enhance the memory allocation flexibility and make it more appropriate for real embedded applications. Simulation results demonstrate how our proposed data allocation strategies can help mitigate the NBTI induced aging effects, as well as reduce the leakage energy consumption on scratchpad memories.