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**Title**: Order Notation in Practice\\
**Proposer**: [[2014:Roger Orr]]\\
**Type**: Presentation\\
**Duration**: 90 mins\\
**Description**: \\
Many of us are familiar with the "Big O" order notation for giving an idea of the complexity of algorithms; for example the C++ std::sort function is described as "N logN".
But sometimes this can seem a little unconnected to the task of actually writing code.\\
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I'll use some examples where there are multiple ways (with different complexity measures) of solving the same problem to explore a few questions, such as:\\
 What does complexity notation actually mean?\\
 What does this measure *not* tell us?\\
 How important is this in practice?\\
 What other considerations are also important to consider?\\
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