Part of a continuing series on Interviews and Interview Questions.

Today, we’re going to look at types of coding and algorithm questions. As discussed before, these can be divided up into ‘Problem Solving’ and ‘Knowledge’ questions.

As mentioned before, ‘Knowledge’ questions are very close to ‘human glossary’ questions. ‘What is the Big-O order of QuickSort? Average case? Worst case?’.

But there are some questions which straddle the line between knowledge and problem solving, answers that few but an expert in that topic would be able to exactly recall, like ‘what exactly happens between when you type google.com into your browser and the page appears?’, or ‘compare and contrast various sorting algorithms’.

For those questions, you have to be as widely read as possible, they tend to select for those who are more naturally inquisitive for things outside their specific area of expertise.

Now, for coding questions. There seem to be a few different types, which I’ll try to separate out by data structure[1]:

Arrays and Strings – Any data structure where any element is addressable in O(1) time, where elements are allocated together in memory.

Linked Lists, Stacks, and Queues – Data structures in linear form, where elements far away from the origin are O(N) difficult to access.

Trees – Data structures arranged in a tree form, with a clear root and directionality. Often sorted.

Graphs – Data structures with nodes and edges, where the edges can connect the nodes in arbitrary ways. Home to at least the plurality of the known NP-Complete problems. Note that Graph problems are a superset of the above.

Search and Optimization – Problems where you’re trying to find an optimal (or close to optimal) solution in a large multidimensional tensor or vector field. Many in this category are easily mappable to Graph Theory questions, but many are not, such as 3-D Protein Structure Prediction. Most interviews would likely not ask questions in this category, at least not very complex ones.

Machine Learning and Statistics – Somewhat related to Search and Optimization, problems dealing with how one trains a computer to solve a problem. Likely to become more and more important.

Hashes – Data structures where space is traded for speed. Generally assumed to have 0(1) insertion and retrieval

[1]Hat tip: developer.com