Review data structure & algorithm

 

First: Cracking the coding interview

20/9

Chapter 1: The interview process

- Analytical skills

- Coding skills

- Technical knowledge / Computer Science fundamentals

- Experience

- Culture fit / Communication skills

Chapter 5: Behavioral questions

- Go through each of the projects or components of your resume and ensure that you can talk about them in detail.

Challenge - Mistakes/Failures - Enjoyed - Leadership - Conflicts - What You'd do Differently

Business problem - Analytics - How to implement

Chapter 6: Big O

Technique dynamic programming: memoization, tabulation.

Chapter 7: Technical questions

Listen -> Example -> Brute force -> Optimize (BUD: Bottlenecks, unnecessary work, duplicated work) -> Walk through -> Implement -> Test

Listen: information -> input/output, optimal keyword.

Brute force: space/time complexity and then dive into improvement.

Optimize: 

1. Look for any unused information.

2. Use a fresh example.

3. Make time/space tradeoff.

4. Precompute information: Reorganize the data or compute some values upfront that will help save time in the long run.

5. Use a hash table.

6. Think about the best conceivable runtime.

Data structure brainstorm: a tree

Example: Numbers are randomly generated and stored into an array. How would you keep track of the median?

1. Linked list? Probably not -> not to do well with accessing and sorting numbers.

2. Array? Maybe. Could you somehow keep the elements sorted? That's probably expensive. 

3. Binary tree? 

4. Heap?