Field guide to the algorithmic interview

speaker: Wong Yiwen event: Hackers and Painters ** interview process

• prescreening coding test
• 2-3 phone interviews
• 3-5 on-site interviews
• each interview ~1hr long, between 1-8 qns each
• high false positive rate
• international candidates can try once a year ** phone interview
• phone call or skype/google hangout
• live coding, using Google docs or CollabEdit
• scheduling protip: Daylight savings time ** on-site interview
• code on the whiteboard
• lousy markers? bring your own markers ** types of questions asked
• programming languages
• general cs what is idempotence?
• coding/algorithmic
• design how would you create google maps?
• behavioural why would you want to work with us?
• NO lateral thinking/puzzle questions
• NO fermi questions recruiter usually sends an information packet telling you the topics. ** coding/algorithmic questions
• given two strings, return true if they are anagrams
• write a program that prints out the powerset of N elements
• NO implement quicksort
• NO how to balance an avl tree
• NO compute the transitive closure of data dependencies of a given C-type program
• BAD standard problems covered in some CS curriculums ends up as a test of where you went to school
• is your solution optimal? how to optimize? discuss the space and run time complexity
• how to test your solution?
• data does not fit into RAM? ** field tips
• know your data structures: lists/arrays/hashmaps/trees/heap/graphs
• know some basic algorithmic approaches
• studying specific “complicated” algorithms are a waste of time, eg A*, Dijkstra, Bellman-Ford
• more important to know data structures than algorithms
• know the implementation language and complexity of data structures/algorithms in standard library
• pick something interviewer friendly with predictale runtime, eg Java some scripting languages may have strange runtime performance
• know the machine/environment, eg cache vs RA
• make the examples easy to build on, list of 100, 200, 800 instead of list of 1, 2, 8
• discuss characterisics of the problem/solution
• observations about approaches that don’t work ** preparation
• how to approach white boarding problems