Bloom Filters

In general, the worse case scenario when searching through a data set is when the datum being searched for doesn’t exist. In this case, the complete data storage needs to be searched before it’s possible to conclude that the datum cannot be found. If only there was a way to eliminate the need to perform unnecessary searches when we know the data won’t be found. Fortunately, there is a data structure that allows you to do just that. This data structure is knows as a “Bloom Filter”.
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Functional programming using bind

Since the introduction of the STL (Standard Template Library) the use of functors has been a prevalent part of writing C++. Most of the STL algorithms require the use of a functor. For example, the std::transform requires a function object that, given an input of the current value of the current position, it will return a new value what will be used to modify the current value.
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Lowest Common Ancestor (BST)

The Binary Search Tree (BST) is a tree like data structure that allows for the quick lookup of data. They work by storing inserted data in a tree like structure that uses the “divide and conquer” approach to locate data. Each node in the tree has, at most, two children. The left hand side (lhs) node will always contain a value that is less than it’s parent. The right hand side (rhs) node will always contain a value that is greater-than or equal to it’s parent.

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Condition Variables

You work in a bar, pouring pints for the locals. One of your regulars comes in; he’s looking pretty grumpy today. “Whiskey” he snaps. You put down a glass and pour. You finish pouring and he necks back the drink. “Again”, he snaps. Again, you pour and as soon as you finish he necks it. This repeats two or three more times before the grumpy man slams down the money for his tab and leaves. Congratulations, you have just taken part in a “Producer/Consumer” exchange.

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