This a combination of piece of information I found around the internet. If you believe there is a better answer, submit a pull request. Most of this content was put together quickly before an interview for review.

If you use it, please star it so I know it is getting use.

• Big O
• Algorithm Complexity

• Quick Sort
• Merge Sort
• When do you use merge sort, when do you use quick sort

• Hash Tables (How they work, implement one using only arrays)

• Tree Construction Tranversal and manipulation
• Binary Trees
• Nary Trees
• Trie Trees
• Balance Binary Tree
• Red Black Tree
• Splay Tree
• AVL Tree

• Objects and pointers (Graph in memory) pros and cons
• Matrix (Graph in memory) Pros and cons
• Adjacency list (Graph in memory) pros and cons

• Tree Traversal so Breadth first search
• Depth first serch
• Difference between inorder, postorder, preorder
• Computational complexity of each tree traversal, their tradeoffs
• Dijkstra
• A*

• NP-Complete problems like traveling salesman, knapsack problem

• Know about processes, threads, concurrency issues
• Know about locks, mutexes, semaphores and monitors
• Know about deadlock and live lock, how to avoid them
• Know what resources a proccesses needs, a thraed needs, how context switch works, how its initiated by os and hardware
• Know about scheduling
• Know fundamentals of "modern" concurrency constructs

• Recursive problems - know how to use and repurpose common recursive algorithms to solve new problems
• Induction for recursive algorithms

• Basic descrete math questions
• N-choose-k problem