Introduction to Technical Interviews

Jake Shoudy, Fisk University

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What to expect during the interview

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Most technical interviews lasts between 45 mins and 1 hour�

• Most virtual interviews will be on a shared coding document that allows for real-time collaborative remote coding between the candidate and the interviewer, complete with formatting and syntax highlighting. You will also simultaneously either be on a video call or phone call with your interviewer.�
• Interviews usually include 1-3 technical questions each�
• There will usually be time for short introductions and closing questions, however the majority of the time will be spent on technical questions�
• If you need any accommodations during the interview process or have questions about assistive technology in virtual interviews, please let your recruiter know.

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Interview Assessment

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The engineering skills being assessed

• Communication and collaboration
• Data structures and algorithms
• Problem solving and analytical skills
• Code understanding

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What you won’t see

• Brain teasers, puzzles, or trick questions
• Perfect code

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Communication and Collaboration

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Verbalize your thoughts

• Restate the question to confirm understanding
• Think out loud
• Draw pictures to help visualize your solution (graphs)
• Prefer to think in silence? Say so, then summarize

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Listen to your interviewer

• They want you to succeed
• Ask clarifying questions before designing your solution �and writing your code
• Are they providing a hint?

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Languages you could use, but are not limited to:

• C/C++�
• Java�
• Python�
• JavaScript�
• Go

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Don’t worry too much about:

• Small syntax errors�
• Punctuation

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Interviewer considerations

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• How did the candidate analyze the problem?
• Did the candidate miss any special or edge cases?
• Did the candidate approach the problem methodically and logically?
• Does the candidate have a strong foundation in basic computer science concepts?
• Did the candidate produce working code? Did the candidate test the code?
• Is the candidate’s code clean and easy to read and maintain?
• Can the candidate explain their ideas clearly?

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Interview Tips

It is a dialogue,

NOT a monologue

Take

your

time

Explain your thought process

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Virtual Interview Tips

High Energy!

Stable WiFi

Clear and Quiet Background

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Interviewing

Step by step

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Steps for acing the technical interview

1. Clarify the question�
2. Design a solution�
3. Write your code�
4. Test your code

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1. Clarify the question

• Do you understand what the question is asking?
• What are example inputs and outputs? (i.e. test cases)�
• Is there additional information that'd be helpful?
• Can numbers be negative? Repeated?
• Are values sorted? If they're not, can you assume there's a sort function you can call?
• Do I need to handle invalid inputs or can I assume the input is valid?

�Why ask clarifying questions?

• Clarifying questions demonstrate your communication skills.
• Clarifying questions can save you a lot of time and avoid misunderstandings

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2. Design a solution

• Do not start coding immediately.
• Start with the first solution that comes to mind, then iterate.
• Describe your algorithms and performances (what is its Big-O?).
• Make sure you handle edge cases.
• Think about other solutions you have seen or data structures you know and ask “would this be helpful?”
• Think out loud.
• You should be communicating with the interviewer during all of these steps.
• Refine and improve solution collaboratively with your interviewer
• It's ok to talk about ideas that you later realize don't work. It can actually be a good thing if you can explain the issue with certain ideas.

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3. Write your code

• Break your solution into smaller parts using helper functions.

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• If you don’t know the exact API, ask the interviewer.

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• Write the code in the language and style you are most comfortable with (you will be asked to confirm your preferred programming language) �
• It’s important to write full code (not pseudocode)

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4. Test your code

• Don't assume your code works.�
• Walkthrough your code line by line using your test cases from earlier in the process. Run through at least 1 or 2 test cases to check your work.
• You can use your test cases you created in step 1!�
• If you realize there are ways to optimize your solution even more, talk about it!

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Common mistakes to avoid

1. Jumping into code

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2. Not talking about examples

and not thinking of testing

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3. Not writing real code

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4. Not understanding the question

or prematurely optimizing

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Final best practices tips

• Explain- Err on the side of over communicating

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• Clarify- Many questions will be deliberately open-ended

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• Listen- An interview can be collaborative, use your interviewer as a resource and pay attention to any hints they might give you

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• Practice- There are no shortcuts, make sure to practice!

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A chance to

practice

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Sample Interview Question

#1

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Sample Interview Question

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Write a function to detect if a string containing parentheses is balanced.

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1a) Clarifying

Write a function to detect if a string containing parentheses is balanced.

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• What does balanced mean?
• Same number of open parentheses and closing parentheses. Each open/close parentheses must be in a pair
• Does the order of the pairs matter?
• Yes, open parentheses must come before closing parentheses
• Do we want to return a boolean?
• Yes
• Can the string contain non parentheses characters?
• Yes
• What do we do if the string is empty or no parentheses?
• Return True

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1b) Clarifying with Examples

• “” -> True
• “Hello” -> True
• “()” -> True
• “((()))” -> True
• “()()()” -> True
• “((hello)my(f(r)ie()))nd -> True
• “)(“ -> False
• “(()()))()” -> False
• “(“ -> False
• “)” -> False

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2) Design

• Could count the # of open parentheses and the # of closed parentheses then return True if they are equal and False otherwise
• Would this work?
• No! Order of the parentheses matters
• Every time I see a closing parentheses, it should “close out” an opening parentheses.
• Keep track of all characters I have seen thus far. If I see a closing parentheses, remove all recent characters until I find an open parentheses, remove it.
• If no open parentheses is found, return False
• Will this work?
• Seems like it?
• What is the runtime?
• O(n^2)

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3) Write code

def is_string_balanced(string):

characters = []

for char in string:

characters.append(char)

if char == ")":

element = ""

while element != "(":

if "(" not in characters:

return False

element = characters.pop()

return "(" not in characters

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3) Write code: optimize

def is_string_balanced(string):

open_parens = []

for char in string:

if char == "(":

open_parens.append(char)

elif char == ")":

if len(open_parens) == 0:

return False

open_parens.pop()

return len(open_parens) == 0

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3) Write code: solution w/ no extra data structure

def is_string_balanced(string):

open_count = 0

for char in string:

if char == "(":

open_count += 1

elif char == ")":

open_count -= 1

if open_count < 0:

return False

return open_count == 0

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4) Test Code

def is_string_balanced(string):

open_count = 0

for char in string:

if char == "(":

open_count += 1

elif char == ")":

open_count -= 1

if open_count < 0:

return False

return open_count == 0

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Examples

• “” -> True
• “((hello)my(f(r)ie()))nd -> True
• “(()()))()” -> False

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Sample Interview Question

#2

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Sample Interview Question

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Find the index of the maximum value of an array of length N. The first K elements of the array are sorted in increasing value, and the last N-K elements are sorted in decreasing value.

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For example, if we are given this array:

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Our code should return the index of number 37 in the array (hint: what is the index of the first element of an array?)

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1a) Clarifying

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• Are we guaranteed the list only contains integers?
• Yes
• Can there be duplicates? Negative numbers?
• There can be duplicates, but not consecutively (one while increasing and the other while decreasing).
• Yes negative numbers are allowed
• What if the list is empty?
• Let’s assume the list is always non-empty
• Can the list contain only increasing numbers with no decreasing numbers afterwards?
• Yes, this is possible

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1b) Clarifying with Examples

• [1, 2, 3, 2, 1] -> 2
• [5] -> 0
• [1, 10, 20, 30, 100, 150] -> 5
• [-8, -5, -2, -3, -5, -10, -20] -> 2
• [5, 3] -> 0

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2) Design

• Loop over array using the index
• If I find an index where the next value is smaller than the current value then return that index
• If I reach the end, return the index of the last position
• Will this work?
• Seems like it?
• What is the runtime?
• O(n)

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Optimized Solution

Sometimes an optimized solution is not required, possible, or expected, especially for students early on in their college studies

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3) Write code

def find_max_index(nums):

for index in range(len(nums)):

if nums[index] > nums[index + 1]:

return index

return len(nums) - 1

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4) Test code

def find_max_index(nums):

for index in range(len(nums)):

if nums[index] > nums[index + 1]:

return index

return len(nums) - 1

Examples

• [1, 2, 3, 2, 1] -> 2
• [5, 3] -> 0
• [1, 10, 20, 30, 100, 150] -> 5

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Testing and Fixing

• Walk through the example and check the code
• Imagine you have not written the code
• Assume it does NOT work

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4b) Fix code

def find_max_index(nums):

for index in range(len(nums) - 1):

if nums[index] > nums[index + 1]:

return index

return len(nums) - 1

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4c) Test code again

def find_max_index(nums):

for index in range(len(nums)):

if nums[index] > nums[index + 1]:

return index

return len(nums) - 1

Examples

• [1, 2, 3, 2, 1] -> 2
• [5, 3] -> 0
• [1, 10, 20, 30, 100, 150] -> 5

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Optimized Solution

• Sometimes an optimized solution is not required, possible, or expected, especially for students early on in their college studies�
• If we were going to optimize the solution for this question, we could ask the following additional clarifying questions:
• Do we have to look at each element?
• Have we seen any similar problems to this before?
• Can we know if we are in the increasing/decreasing portion?
• Binary search with a look left + right to determine where to go next
• You might not know this yet from your studies, that’s ok!

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Optimized solution

def find_max_idx(sorted_array):

if not sorted_array:

return -1

start = 0

end = len(sorted_array) - 1

while end - start > 1:

middle = (start + end) // 2 # Python 3 floor divide.

if sorted_array[middle] < sorted_array[middle + 1]:

start = middle

elif sorted_array[middle] < sorted_array[middle - 1]:

end = middle

else:

return middle

if sorted_array[start] > sorted_array[end]:

return start

else:

return end

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