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Table of Contents

Topics of Study

Getting the Job

---------------- Everything below this point is optional ----------------

Optional Extra Topics & Resources

Algorithmic complexity / Big-O / Asymptotic analysis

Data Structures

  • Arrays

    • About Arrays:
    • Implement a vector (mutable array with automatic resizing):
      • Practice coding using arrays and pointers, and pointer math to jump to an index instead of using indexing.
      • New raw data array with allocated memory
        • can allocate int array under the hood, just not use its features
        • start with 16, or if starting number is greater, use power of 2 - 16, 32, 64, 128
      • size() - number of items
      • capacity() - number of items it can hold
      • is_empty()
      • at(index) - returns item at given index, blows up if index out of bounds
      • push(item)
      • insert(index, item) - inserts item at index, shifts that index's value and trailing elements to the right
      • prepend(item) - can use insert above at index 0
      • pop() - remove from end, return value
      • delete(index) - delete item at index, shifting all trailing elements left
      • remove(item) - looks for value and removes index holding it (even if in multiple places)
      • find(item) - looks for value and returns first index with that value, -1 if not found
      • resize(new_capacity) // private function
        • when you reach capacity, resize to double the size
        • when popping an item, if size is 1/4 of capacity, resize to half
    • Time
      • O(1) to add/remove at end (amortized for allocations for more space), index, or update
      • O(n) to insert/remove elsewhere
    • Space
      • contiguous in memory, so proximity helps performance
      • space needed = (array capacity, which is >= n) * size of item, but even if 2n, still O(n)

  • Linked Lists

    • Description:
    • C Code (video) - not the whole video, just portions about Node struct and memory allocation
    • Linked List vs Arrays:
    • why you should avoid linked lists (video)
    • Gotcha: you need pointer to pointer knowledge: (for when you pass a pointer to a function that may change the address where that pointer points) This page is just to get a grasp on ptr to ptr. I don't recommend this list traversal style. Readability and maintainability suffer due to cleverness.
    • Implement (I did with tail pointer & without):
      • size() - returns number of data elements in list
      • empty() - bool returns true if empty
      • value_at(index) - returns the value of the nth item (starting at 0 for first)
      • push_front(value) - adds an item to the front of the list
      • pop_front() - remove front item and return its value
      • push_back(value) - adds an item at the end
      • pop_back() - removes end item and returns its value
      • front() - get value of front item
      • back() - get value of end item
      • insert(index, value) - insert value at index, so current item at that index is pointed to by new item at index
      • erase(index) - removes node at given index
      • value_n_from_end(n) - returns the value of the node at nth position from the end of the list
      • reverse() - reverses the list
      • remove_value(value) - removes the first item in the list with this value
    • Doubly-linked List

  • Stack

    • Stacks (video)
    • Will not implement. Implementing with array is trivial

  • Queue

    • Queue (video)
    • Circular buffer/FIFO
    • Implement using linked-list, with tail pointer:
      • enqueue(value) - adds value at position at tail
      • dequeue() - returns value and removes least recently added element (front)
      • empty()
    • Implement using fixed-sized array:
      • enqueue(value) - adds item at end of available storage
      • dequeue() - returns value and removes least recently added element
      • empty()
      • full()
    • Cost:
      • a bad implementation using linked list where you enqueue at head and dequeue at tail would be O(n) because you'd need the next to last element, causing a full traversal each dequeue
      • enqueue: O(1) (amortized, linked list and array [probing])
      • dequeue: O(1) (linked list and array)
      • empty: O(1) (linked list and array)

  • Hash table

More Knowledge

Trees

Sorting

As a summary, here is a visual representation of 15 sorting algorithms. If you need more detail on this subject, see "Sorting" section in Additional Detail on Some Subjects

Graphs

Graphs can be used to represent many problems in computer science, so this section is long, like trees and sorting were.

Even More Knowledge

Final Review

This section will have shorter videos that you can watch pretty quickly to review most of the important concepts.
It's nice if you want a refresher often.

Update Your Resume

Find a Job

Interview Process & General Interview Prep

Mock Interviews:

Be thinking of for when the interview comes

Think of about 20 interview questions you'll get, along with the lines of the items below. Have at least one answer for each. Have a story, not just data, about something you accomplished.

  • Why do you want this job?

  • What's a tough problem you've solved?

  • Biggest challenges faced?

  • Best/worst designs seen?

  • Ideas for improving an existing product

  • How do you work best, as an individual and as part of a team?

  • Which of your skills or experiences would be assets in the role and why?

  • What did you most enjoy at [job x / project y]?

  • What was the biggest challenge you faced at [job x / project y]?

  • What was the hardest bug you faced at [job x / project y]?

  • What did you learn at [job x / project y]?

  • What would you have done better at [job x / project y]?

  • If you find it hard to come up with good answers of these types of interview questions, here are some ideas:

Have questions for the interviewer

Some of mine (I already may know the answers, but want their opinion or team perspective):

  • How large is your team?
  • What does your dev cycle look like? Do you do waterfall/sprints/agile?
  • Are rushes to deadlines common? Or is there flexibility?
  • How are decisions made in your team?
  • How many meetings do you have per week?
  • Do you feel your work environment helps you concentrate?
  • What are you working on?
  • What do you like about it?
  • What is the work life like?
  • How is the work/life balance?

Once You've Got The Job

Congratulations!

Keep learning.

You're never really done.

*****************************************************************************************************
*****************************************************************************************************

Everything below this point is optional. It is NOT needed for an entry-level interview.
However, by studying these, you'll get greater exposure to more CS concepts, and will be better prepared for
any software engineering job. You'll be a much more well-rounded software engineer.

*****************************************************************************************************
*****************************************************************************************************

Additional Books

These are here so you can dive into a topic you find interesting.
  • The Unix Programming Environment
    • An oldie but a goodie
  • The Linux Command Line: A Complete Introduction
    • A modern option
  • TCP/IP Illustrated Series
  • Head First Design Patterns
    • A gentle introduction to design patterns
  • Design Patterns: Elements of Reusable Object-Oriente​d Software
    • AKA the "Gang Of Four" book, or GOF
    • The canonical design patterns book
  • Algorithm Design Manual (Skiena)
    • As a review and problem recognition
    • The algorithm catalog portion is well beyond the scope of difficulty you'll get in an interview
    • This book has 2 parts:
      • Class textbook on data structures and algorithms
        • Pros:
          • Is a good review as any algorithms textbook would be
          • Nice stories from his experiences solving problems in industry and academia
          • Code examples in C
        • Cons:
          • Can be as dense or impenetrable as CLRS, and in some cases, CLRS may be a better alternative for some subjects
          • Chapters 7, 8, 9 can be painful to try to follow, as some items are not explained well or require more brain than I have
          • Don't get me wrong: I like Skiena, his teaching style, and mannerisms, but I may not be Stony Brook material
      • Algorithm catalog:
        • This is the real reason you buy this book.
        • This book is better as an algorithm reference, and not something you read cover to cover.
    • Can rent it on Kindle
    • Answers:
    • Errata
  • Write Great Code: Volume 1: Understanding the Machine
    • The book was published in 2004, and is somewhat outdated, but it's a terrific resource for understanding a computer in brief
    • The author invented HLA, so take mentions and examples in HLA with a grain of salt. Not widely used, but decent examples of what assembly looks like
    • These chapters are worth the read to give you a nice foundation:
      • Chapter 2 - Numeric Representation
      • Chapter 3 - Binary Arithmetic and Bit Operations
      • Chapter 4 - Floating-Point Representation
      • Chapter 5 - Character Representation
      • Chapter 6 - Memory Organization and Access
      • Chapter 7 - Composite Data Types and Memory Objects
      • Chapter 9 - CPU Architecture
      • Chapter 10 - Instruction Set Architecture
      • Chapter 11 - Memory Architecture and Organization
  • Introduction to Algorithms
    • Important: Reading this book will only have limited value. This book is a great review of algorithms and data structures, but won't teach you how to write good code. You have to be able to code a decent solution efficiently
    • AKA CLR, sometimes CLRS, because Stein was late to the game
  • Computer Architecture, Sixth Edition: A Quantitative Approach
    • For a richer, more up-to-date (2017), but longer treatment

System Design, Scalability, Data Handling

You can expect system design questions if you have 4+ years of experience.

Additional Learning

I added them to help you become a well-rounded software engineer, and to be aware of certain
technologies and algorithms, so you'll have a bigger toolbox.

Additional Detail on Some Subjects

I added these to reinforce some ideas already presented above, but didn't want to include them
above because it's just too much. It's easy to overdo it on a subject.
You want to get hired in this century, right?

Video Series

Sit back and enjoy.

Computer Science Courses

Algorithms implementation

Papers

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