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The key to a solid foundation in data structures and algorithms is not an exhaustive survey of every conceivable data structure and its subforms, with memorization of each's Big-O value and amortized cost.

Learn when and how to use different data structures and their algorithms in your own code. This is harder as a student, as the problem assignments you'll work through just won't impart this knowledge. That's fine.

Realize you won't master data structures until you are working on a real-world problem and discover that a hash is the solution to your performance woes.

Good candidates can arrive at the binary search tree as the right path in a few minutes, and then take 10-15 minutes working through the rest of the problem and the other roadblocks I toss out. But occasionally I get a candidate who 'intuitively understands' trees and can visualize the problem I'm presenting.

GPS's battery draining behavior is most noticeable during the initial acquisition of the satellite's navigation message: the satellite's state, ephemeris, and almanac.

GPS is expensive because it is a very slow communication channel - you need to communicate with three or four satellites for an extended duration at 50 bits per second.

Mobile devices such as Android and the iPhone achieve their battery life largely because they can aggressively and quickly enter into and exit from sleep states. GPS prevents this.

Compounding the cost, most mapping software is processor-intense.

The interesting thing about Android's design is how little we modified the kernel.

Android's user-space is so different from stock Linux, you can easily say that Android is not in any way a Linux system, except for the kernel.

Zero-length arrays are useful only in cases where you have a large structure, which contains a field of dynamic length, and you need to share that structure across program or even computer boundaries.

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