LS - General Approach to Solve the problem

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Small Code Challenge Problems
  - 20 - 45 minutes
  - typical solutions: 10-40 LOC
  - used extensively in interviews for a reason
    - mastery on a language
    - logic / reasoning
    - communications
  - not a skill that you "acquire and file away", but needs a lot of practice

Understand the Problem
  - requirements are explicit
    - take notes
    - the odd words problem
  - requirements are not so explicit and need to be modeled
    - examples need to be described in computational words
    - diamond of stars
  - implicit knowledge needs to be captured
    - convert to explicit rules, in computational language
    - what century is that
  - identifying and defining important terms and concepts
    - queen attack
    - same row; same column; esp. same diagnal
  - ask questions to verify your understanding!

Examples / Test Cases
  - Input / Output
  - Test cases serve two purposes:
    - help you understand the problem
    - allow you to verify your solution
  - happy paths
    - combination of requirements; the "obvious" result
  - Edge cases
    - focus on input
    - emptiness (nil/null, "", [], {})
    - boundary conditions
    - repetition / duplication
    - data types
  - Failures / Bad Input
    - raise exceptions / report errors
    - return a special value (nil/null, 0, "", [] etc)
  - ask questions to verify your understanding!

Data Structure
  - input data
  - rules/requirements as data
    - hash / object

  - string, array, hash/object, number
    - string
      - concact, strip, reverse, etc
      - Regular Expression! split, replace, match...
    - array
      - need to walk through it (iteration)
      - index
      - abstractions!!
        - map
        - reduce
        - select/filter
        - all
        - ...
    - hash/object
      - lookup table / dictionary
      - partition data for more efficient access downstream
      - digest
    - number
      - math operations
      - number as string may have advantage over numbers
  - compound data structures
    - array of arrays
    - hash with array/object values, etc

Algorithm
  - Algorithms have to be described in the language of chosen data structure!
    - "then solve it" doesn't count
  - Have to be really fluent with
    - String / Regex
    - Array
      - Ruby: Enumerable
      - JavaScript: Higher Order Functions
    - Hash / Object
      - Creation (default values)
      - Access (default values)
      - Iteration
  - verify your algorithm with your examples / test cases

Abstraction
  - Very important, rely on language built in abstractions: String/Regex, Array, Hash/Object
  - Avoid solving big problems!
    - Always, always, break bigger problems into smaller problems
    - Don't try to walk through a wall
  - lay out the general steps of an algorithm, without having to go to details
    - Try to solve a problem in 1-2 sentences!!!
    - If you can't, raise your abstraction
      - create helper methods/functions
      - push detailed steps to methods/functions

Interview Tips
  - Communicative
  - Getting to a working solution >> no solution
  - De-risking
    - Check your building blocks
      - run code often
      - debug locally
  - Manage your energy