technical questions
how to prepare
- try to solve the problem on your own
- write the code on paper
- test your code on paper (general, base, and error cases)
- type your paper as-is into a computer, note what mistakes you made
- do as many mock interviews as possible
core data structures, algorithms, and concepts
data structures
- linked lists
- trees, tries, graphs
- stacks and queues
- heaps
- vectors/arraylists
- hash tables
algorithms
- breadth-first search
- depth-first search
- binary search
- merge sort
- quick sort
concepts
- bit manipulation
- memory (stack vs heap)
- recursion
- dynamic programming
- big O time and space
| power of 2 |
exact value (x) |
approx value |
x bytes into mb, gb, etc |
| 7 |
128 |
|
|
| 8 |
256 |
|
|
| 10 |
1024 |
1 thousand |
1 kb |
| 16 |
65,536 |
|
64 kb |
| 20 |
1,048,576 |
1 million |
1 mb |
| 30 |
1,073,741,824 |
1 billion |
1 gb |
| 32 |
4,294,967,296 |
|
4 gb |
| 40 |
1,099,511,627,776 |
1 trillion |
1 tb |
walking through a problem
- listen carefully
- draw an example
- be specific, use real numbers or strings (applicable to the problem)
- not special case
- state a brute force
- explain time and space complexity
- valuable to discuss (starting point for optimizations)
- optimize
- look for unused information
- use a fresh example
- solve it incorrectly
- make time vs space tradeoff
- precompute information
- use a hash table
- think about best conceivable runtime
- walk through
- take a moment to solidify your understanding of the algorithm
- walk through your algorithm to feel out structure (know what variables are and when they change)
- implement
- write beautiful code
- modularized code
1,2,3,4,5,6 -> initIncrementalMatrix(int size)
- error checks (add
todo and explain what you would like to test)
- use other classes/structs where appropriate
- good variable names
- test
- start with a conceptual test
- weird looking code
- hot spots (recursive code, division, null nodes, etc)
- small test cases
- special cases (test against nulls, single element values, extreme cases, etc)
bud optimization
b - bottlenecks
u - unnecessary work
d - duplicated work