We propose a comprehensive solution to handle memory-overflow problems in multitasking embedded systems thereby improving their reliability and availability. In particular, we propose two complementary techniques to address two significant causes of memory-overflow problems. The first cause is errors in estimating appropriate stack and heap memory requirement. Our first technique, called Shared Supplementary Memory (SSM), exploits the fact that the probability of multiple tasks requiring more than their estimated amount of memory concurrently is low. Using analytical model and simulations, we show that reliability can be considerably improved when SSM is employed. Furthermore, for the same reliability, SSM reduces total memory requirement by as much as 29.31%. The second cause is the presence of coding Mandelbugs, which can cause abnormal memory requirement. To address this, we propose a novel technique, called Opportunistic MicroRejuvenation, which when combined with SSM, provide several advantages: preventing critical-time outage, resource frugality and dependability enhancement. Keywords: stack overflow, heap overflow, embedded systems, software rejuvenation, resource constrained fault-tolerance