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Random numbers -- really, truly random numbers -- play a very important role in security. Everything from key generation, nonces, shuffling, secure protocols, and many forms of challenge-response rely on unpredictable numbers.

If you've got a lot of real-time tasks and tight deadlines, what's the best way to prioritize them? A technique called RMA guides the way.

The scheduling algorithm you choose depends on your goals. Different algorithms yield different results. Let's suppose you're given ten jobs and each will take a day to finish. In ten days, you will have all of them done. But what if one or more has a deadline? If the ninth task given to you has a deadline in three days, then doing the tasks in the order you receive them will cause you to miss that deadline.

Finding and killing latent bugs in embedded software is a difficult business. Heroic efforts and expensive tools are often required to trace backward from an observed crash, hang, or other unplanned run-time behavior to the root cause. In the worst case scenario, the root cause damages the code or data in such a subtle way that the system still appears to work fine or mostly fine-for some time before the malfunction.

Whether you're using only static memory, a simple stack, or dynamic allocation on a heap, you have to proceed cautiously. Embedded programmers can't afford to ignore the risks inherent in memory utilization.

Unexpected power loss and software bugs can undermine the reliability of non-volatile data. Fortunately, there are various ways to make non-volatile data resilient to such corruption.

Product usability problems require the engineer to take off his engineering hat and think more like a user.

Proper timing in user interfaces often has more to do with the user's perception than with the actual passage of time.