This post draws on my personal experiences and challenges over the past term at school, which I entered with hardly any knowledge of DSA (data structures and algorithms) and problem-solving strategies. As a self-taught programmer, I was a lot more familiar and comfortable with general programming, such as object-oriented programming, than with the problem-solving skills required in DSA questions.
This post reflects my journey throughout the term and the resources I turned to in order to quickly improve for my coding interview.
Here're some common questions and answers What's the interview process like at a tech company?
Good question. It's actually pretty different from most other companies.
(What It's Like To Interview For A Coding Job
First time interviewing for a tech job? Not sure what to expect? This article is for you.
Here are the usual steps:
- First, you’ll do a non-technical phone screen.
- Then, you’ll do one or a few technical phone interviews.
- Finally, the last step is an onsite interview.
Some companies also throw in a take-home code test
—sometimes before the technical phone interviews, sometimes after.
Let’s walk through each of these steps.
The non-technical phone screen
This first step is a quick call with a recruiter—usually just 10–20 minutes. It's very casual.
Don’t expect technical questions. The recruiter probably won’t be a programmer.
The main goal is to gather info about your job search. Stuff like:
- Your timeline. Do you need to sign an offer in the next week? Or are you trying to start your new job in three months?
- What’s most important to you in your next job. Great team? Flexible hours? Interesting technical challenges? Room to grow into a more senior role?
- What stuff you’re most interested in working on. Front end? Back end? Machine learning?
Be honest about all this stuff—that’ll make it easier for the recruiter to get you what you want.
One exception to that rule: If the recruiter asks you about your salary expectations on this call, best not to answer.
Just say you’d rather talk about compensation after figuring out if you and the company are a good fit. This’ll put you in a better negotiating position later on.
The technical phone interview(s)
The next step is usually one or more hour-long technical phone interviews.
Your interviewer will call you on the phone or tell you to join them on Skype or Google Hangouts. Make sure you can take the interview in a quiet place with a great internet connection. Consider grabbing a set of headphones with a good microphone or a bluetooth earpiece.
Always test your hardware beforehand!
The interviewer will want to watch you code in real time. Usually that means using a web-based code editor like Coderpad
. Run some practice problems in these tools ahead of time, to get used to them. Some companies will just ask you to share your screen through Google Hangouts or Skype. Turn off notifications
on your computer before you get started—especially if you’re sharing your screen!
Technical phone interviews usually have three parts:
The beginning chitchat
- Beginning chitchat (5–10 minutes)
- Technical challenges (30–50 minutes)
- Your turn to ask questions (5–10 minutes)
is half just to help your relax, and half actually part of the interview. The interviewer might ask some open-ended questions like:
- Tell me about yourself.
- Tell me about something you’ve built that you’re particularly proud of.
- I see this project listed on your resume—tell me more about that.
You should be able to talk at length about the major projects listed on your resume. What went well? What didn’t? How would you do things differently now? Then come the technical challenges
—the real meet
of the interview. You’ll spend most
of the interview on this. You might get one long question, or several shorter ones.
What kind of questions can you expect? It depends.
Startups tend to ask questions aimed towards building or debugging code. (“Write a function that takes two rectangles and figures out if they overlap
.”). They’ll care more about progress than perfection.
Larger companies will want to test your general know-how of data structures and algorithms
(“Write a function that checks if a binary tree
is ‘balanced’ in O(n)O
) ↴ time.”). They’ll care more about how you solve and optimize a problem.
With these types of questions, the most important thing is to be communicating with your interviewer
throughout. You'll want to "think out loud" as you work through the problem. For more info, check out our more detailed step-by-step tips for coding interviews
If the role requires specific languages or frameworks, some companies will ask trivia-like questions (“In Python, what’s the ‘global interpreter lock’?”). After the technical questions, your interviewer will open the floor for you to ask them questions
. Take some time before the interview to comb through the company’s website. Think of a few specific questions about the company or the role. This can really make you stand out.
When you’re done, they should give you a timeframe on when you’ll hear about next steps. If all went well, you’ll either get asked to do another phone interview, or you’ll be invited to their offices for an onsite.
The onsite interview
An onsite interview happens in person, at the company’s office. If you’re not local, it’s common for companies to pay for a flight and hotel room for you.
The onsite usually consists of 2–6 individual, one-on-one technical interviews (usually in a small conference room). Each interview will be about an hour and have the same basic form as a phone screen—technical questions, bookended by some chitchat at the beginning and a chance for you to ask questions at the end.
The major difference between onsite technical interviews and phone interviews though: you’ll be coding on a whiteboard
This is awkward
at first. No autocomplete, no debugging tools, no delete button
…ugh. The good news is, after some practice you get used to it. Before your onsite, practice writing code on a whiteboard (in a pinch, a pencil and paper are fine). Some tips:
- Start in the top-most left corner of the whiteboard. This gives you the most room. You’ll need more space than you think.
- Leave a blank line between each line as you write your code. Makes it much easier to add things in later.
- Take an extra second to decide on your variable names. Don’t rush this part. It might seem like a waste of time, but using more descriptive variable names ultimately saves you time because it makes you less likely to get confused as you write the rest of your code.
If a technical phone interview is a sprint, an onsite is a marathon. The day can get really long. Best to keep it open—don’t make other plans for the afternoon or evening.
When things go well, you’ wrap-up by chatting with the CEO or some other director. This is half an interview, half the company trying to impress you. They may invite you to get drinks with the team after hours.
All told, a long day of onsite interviews could look something like this:
- 10am-12pm: two back-to-back technical interviews, each about an hour.
- 12pm-1pm: one or several engineers will take you to lunch, perhaps in the company’s fancy office cafeteria.
- 1pm-4pm: three back-to-back technical interviews, each about an hour.
- 4pm-5pm: interview with the CEO or some sort of director.
- 5pm-8pm: drinks and dinner with the company
If they let you go after just a couple interviews, it’s usually a sign that they’re going to pass on you. That’s okay—it happens!
There are are a lot of easy things you can do the day before and morning of your interview to put yourself in the best possible mindset. Check out our piece on what to do in the 24 hours before your onsite coding interview
The take-home code test
Code tests aren’t ubiquitous, but they seem to be gaining in popularity. They’re far more common at startups, or places where your ability to deliver right away is more important than your ability to grow.
You’ll receive a description of an app or service, a rough time constraint for writing your code, and a deadline for when to turn it in. The deadline is usually negotiable.
Here's an example problem: Write a basic “To-Do” app. Unit test the core functionality. As a bonus, add a “reminders” feature. Try to spend no more than 8 hours on it, and send in what you have by Friday with a small write-up.
Take a crack at the “bonus” features if they include any. At the very least, write up how you would implement it.
If they’re hiring for people with knowledge of a particular framework, they might tell you what tech to use. Otherwise, it’ll be up to you. Use what you’re most comfortable with. You want this code to show you at your best.
Some places will offer to pay you for your time. It's rare, but some places will even invite you to work with them in their office for a few days, as a "trial.") Do I need to know this "big O" stuff? Big O notation
is the language we use for talking about the efficiency of data structures and algorithms.
Will it come up in your interviews? Well, it depends. There are different types of interviews.
There’s the classic algorithmic coding interview, sometimes called the “Google-style whiteboard interview.” It’s focused on data structures and algorithms (queues
, binary search
That’s what our full course
prepares you for. It's how the big players interview. Google
For startups and smaller shops, it’s a mixed bag. Most will ask at least a few algorithmic questions. But they might also include some role-specific stuff, like Java questions
or SQL questions
for a backend web engineer. They’ll be especially interested in your ability to ship code without much direction. You might end up doing a code test or pair-programming exercise instead of a whiteboarding session.
To make sure you study for the right stuff, you should ask your recruiter what to expect. Send an email with a question like, “Is this interview going to cover data structures and algorithms? Or will it be more focused around coding in X language.” They’ll be happy to tell you.
If you've never learned about data structures and algorithms, or you're feeling a little rusty, check out our Intuitive Guide to Data Structures and Algorithms
. Which programming language should I use?
Companies usually let you choose, in which case you should use your most comfortable language. If you know a bunch of languages, prefer one that lets you express more with fewer characters and fewer lines of code, like Python or Ruby. It keeps your whiteboard cleaner.
Try to stick with the same language for the whole interview, but sometimes you might want to switch languages for a question. E.g., processing a file line by line will be far easier in Python than in C++.
Sometimes, though, your interviewer will do this thing where they have a pet question that’s, for example, C-specific. If you list C on your resume, they’ll ask it.
So keep that in mind! If you’re not confident with a language, make that clear on your resume. Put your less-strong languages under a header like ‘Working Knowledge.’ What should I wear?
A good rule of thumb is to dress a tiny step above what people normally wear to the office. For most west coast tech companies, the standard digs are just jeans and a t-shirt. Ask your recruiter what the office is like if you’re worried about being too casual. Should I send a thank-you note?
Thank-you notes are nice, but they aren’t really expected. Be casual if you send one. No need for a hand-calligraphed note on fancy stationery. Opt for a short email to your recruiter or the hiring manager. Thank them for helping you through the process, and ask them to relay your thanks to your interviewers. 1) Coding Interview Tips
How to get better at technical interviews without practicing Chitchat like a pro.
Before diving into code, most interviewers like to chitchat about your background. They're looking for:
- Metacognition about coding. Do you think about how to code well?
- Ownership/leadership. Do you see your work through to completion? Do you fix things that aren't quite right, even if you don't have to?
- Communication. Would chatting with you about a technical problem be useful or painful?
You should have at least one:
Nerd out about stuff
- example of an interesting technical problem you solved
- example of an interpersonal conflict you overcame
- example of leadership or ownership
- story about what you should have done differently in a past project
- piece of trivia about your favorite language, and something you do and don't like about said language
- question about the company's product/business
- question about the company's engineering strategy (testing, Scrum, etc)
. Show you're proud of what you've done, you're amped about what they're doing, and you have opinions about languages and workflows. Communicate.
Once you get into the coding questions, communication is key. A candidate who needed some help along the way but communicated clearly can be even better than a candidate who breezed through the question. Understand what kind of problem it is
. There are two types of problems:
- Coding. The interviewer wants to see you write clean, efficient code for a problem.
If you start writing code and the interviewer just wanted a quick chitchat answer before moving on to the "real" question, they'll get frustrated. Just ask, "Should we write code for this?" Make it feel like you're on a team
. The interviewer wants to know what it feels like to work through a problem with you, so make the interview feel collaborative. Use "we" instead of "I," as in, "If we did a breadth-first search we'd get an answer in O(n)O
) time." If you get to choose between coding on paper and coding on a whiteboard, always choose the whiteboard. That way you'll be situated next to the interviewer, facing the problem (rather than across from her at a table). Think out loud.
If you're touching on a fact
(e.g., language-specific trivia, a hairy bit of runtime analysis), don't try to appear to know something you don't. Instead, say "I'm not sure, but I'd guess $thing, because...
". The because
can involve ruling out other options by showing they have nonsensical implications, or pulling examples from other languages or other problems. Slow the eff down
. Don't confidently blurt out an answer right away. If it's right you'll still have to explain it, and if it's wrong you'll seem reckless. You don't win anything for speed and you're more likely to annoy your interviewer by cutting her off or appearing to jump to conclusions. Get unstuck.
Sometimes you'll get stuck. Relax. It doesn't mean you've failed. Keep in mind that the interviewer usually cares more about your ability to cleverly poke the problem from a few different angles than your ability to stumble into the correct answer. When hope seems lost, keep poking. Draw pictures.
Don't waste time trying to think in your head—think on the board. Draw a couple different test inputs. Draw how you would get the desired output by hand. Then think about translating your approach into code. Solve a simpler version of the problem.
Not sure how to find the 4th largest item in the set? Think about how to find the 1st largest item and see if you can adapt that approach. Write a naive, inefficient solution and optimize it later.
Use brute force. Do whatever it takes to get some kind
of answer. Think out loud more
. Say what you know. Say what you thought might work and why it won't work. You might realize it actually does work, or a modified version does. Or you might get a hint. Wait for a hint.
Don't stare at your interviewer expectantly, but do take a brief
second to "think"—your interviewer might have already decided to give you a hint and is just waiting to avoid interrupting. Think about the bounds on space and runtime.
If you're not sure if you can optimize your solution, think about it out loud. For example:
Get your thoughts down.
- "I have to at least look at all of the items, so I can't do better than O(n)O(n)."
- "The brute force approach is to test all possibilities, which is O(n^2)O(n2)."
- "The answer will contain n^2n2 items, so I must at least spend that amount of time."
It's easy to trip over yourself. Focus on getting your thoughts down first and worry about the details at the end. Call a helper function and keep moving.
If you can't immediately think of how to implement some part of your algorithm, big or small, just skip over it. Write a call to a reasonably-named helper function, say "this will do X" and keep going. If the helper function is trivial, you might even get away with never implementing it. Don't worry about syntax.
Just breeze through it. Revert to English if you have to. Just say you'll get back to it. Leave yourself plenty of room.
You may need to add code or notes in between lines later. Start at the top of the board and leave a blank line between each line. Save off-by-one checking for the end.
Don't worry about whether your for loop should have "<<" or "<=<=." Write a checkmark to remind yourself to check it at the end. Just get the general algorithm down. Use descriptive variable names.
This will take time, but it will prevent you from losing track of what your code is doing. Use names_to_phone_numbers instead of nums. Imply the type in the name. Functions returning booleans should start with "is_*". Vars that hold a list should end with "s." Choose standards that make sense to you and stick with them. Clean up when you're done. Walk through your solution by hand, out loud, with an example input.
Actually write down
what values the variables hold as the program is running—you don't win any brownie points for doing it in your head. This'll help you find bugs and clear up confusion your interviewer might have about what you're doing. Look for off-by-one errors.
Should your for loop use a "<=<=" instead of a "<<"? Test edge cases.
These might include empty sets, single-item sets, or negative numbers. Bonus: mention unit tests! Don't be boring.
Some interviewers won't care about these cleanup steps. If you're unsure, say something like, "Then I'd usually check the code against some edge cases—should we do that next?" Practice.
In the end, there's no substitute for running practice questions. Actually write code with pen and paper.
Be honest with yourself. It'll probably feel awkward at first. Good. You want to get over that awkwardness now so you're not fumbling when it's time for the real interview.
2) Tricks For Getting Unstuck During a Coding Interview
Getting stuck during a coding interview is rough.
If you weren’t in an interview, you might take a break or ask Google for help. But the clock is ticking, and you don’t have Google.
You just have an empty whiteboard, a smelly marker, and an interviewer who’s looking at you expectantly. And all you can think about is how stuck you are.
You need a lifeline for these moments—like a little box that says “In Case of Emergency, Break Glass.” Inside
that glass box? A list of tricks for getting unstuck. Here’s that list of tricks. When you’re stuck on getting started 1) Write a sample input on the whiteboard and turn it into the correct output "by hand."
Notice the process
you use. Look for patterns, and think about how to implement your process in code.
Trying to reverse a string? Write “hello” on the board. Reverse it “by hand”—draw arrows from each character’s current position to its desired position.
Notice the pattern: it looks like we’re swapping
pairs of characters, starting from the outside and moving in. Now we’re halfway to an algorithm. 2) Solve a simpler version of the problem.
Remove or simplify one of the requirements of the problem. Once you have a solution, see if you can adapt that approach for the original question.
Trying to find the k-largest element in a set? Walk through finding the largest
element, then the second largest
, then the third largest
. Generalizing from there to find the k-largest isn’t so bad. 3) Start with an inefficient solution.
Even if it feels stupidly inefficient
, it’s often helpful to start with something
that’ll return the right answer. From there, you just have to optimize
your solution. Explain to your interviewer that this is only your first idea, and that you suspect there are faster solutions.
Suppose you were given two lists of sorted numbers and asked to find the median of both lists combined. It’s messy, but you could simply:
- Concatenate the arrays together into a new array.
- Sort the new array.
- Return the value at the middle index.
Notice that you could’ve also
arrived at this algorithm by using trick (2): Solve a simpler version of the problem. “How would I find the median of one
sorted list of numbers? Just grab the item at the middle index. Now, can I adapt that approach for getting the median of two
sorted lists?” When you’re stuck on finding optimizations 1) Look for repeat work.
If your current solution goes through the same data multiple times, you’re doing unnecessary repeat work. See if you can save time by looking through the data just once.
Say that inside one of your loops, there’s a brute-force operation to find an element in an array. You’re repeatedly looking through items that you don’t have to. Instead, you could convert the array to a lookup table
to dramatically improve your runtime. 2) Look for hints in the specifics of the problem.
Is the input array sorted? Is the binary tree
balanced? Details like this can carry huge hints about the solution. If it didn’t matter, your interviewer wouldn’t have brought it up. It’s a strong sign that the best solution to the problem exploits it.
Suppose you’re asked to find the first occurrence of a number in a sorted array. The fact that the array is sorted
is a strong hint—take advantage of that fact by using a binary search
Sometimes interviewers leave the question deliberately vague because they want you to ask questions
to unearth these important tidbits of context. So ask some questions at the beginning of the problem. 3) Throw some data structures at the problem.
Can you save time by using the fast lookups of a hash table
? Can you express the relationships between data points as a graph
? Look at the requirements of the problem and ask yourself if there’s a data structure that has those properties. 4) Establish bounds on space and runtime.
Think out loud
about the parameters of the problem. Try to get a sense for how fast your algorithm could possibly
When All Else Fails 1) Make it clear where you are.
- “I have to at least look at all the items, so I can’t do better than O(n)O(n) ↴ time”.
- “The brute force approach is to test all possibilities, which is O(n^2)O(n2) time. So the question is whether or not I can beat that time.”
- “The answer will contain n^2n2 items, so I must at least spend that amount of time.”
State what you know, what you’re trying to do, and highlight the gap between the two. The clearer you are in expressing exactly
where you’re stuck, the easier it is for your interviewer to help you. 2) Pay attention to your interviewer.
If she asks a question about something you just said, there’s probably a hint buried in there. Don’t worry about losing your train of thought—drop what you’re doing and dig into her question. Relax. You’re supposed to get stuck.
Interviewers choose hard problems on purpose. They want to see how you poke at a problem you don’t immediately know how to solve.
Seriously. If you don’t
get stuck and just breeze through the problem, your interviewer’s evaluation might just say “Didn’t get a good read on candidate’s problem-solving process—maybe she’d already seen this interview question before?”
On the other hand, if you do
get stuck, use one of these tricks to get unstuck, and communicate clearly with your interviewer throughout...that’s
how you get an evaluation like, “Great problem-solving skills. Hire.”
Fixing Impostor Syndrome in Coding Interviews “It's a fluke that I got this job interview...” “I studied for weeks, but I’m still not prepared...” “I’m not actually good at this. They’re going to see right through me...”
If any of these thoughts resonate with you, you're not alone. They are so common they have a name: impostor syndrome.
It’s that feeling like you’re on the verge of being exposed for what you really are—an impostor. A fraud. Impostor syndrome is like kryptonite to coding interviews.
It makes you give up and go silent.
You might stop asking clarifying questions because you’re afraid they’ll sound too basic. Or you might neglect to think out loud at the whiteboard, fearing you’ll say something wrong and sound incompetent.
You know you should speak up, but the fear of looking like an impostor makes that really, really
hard. Here’s the good news: you’re not an impostor.
You just feel
like an impostor because of some common cognitive biases about learning and knowledge.
Once you understand these cognitive biases—where they come from and how they work—you can slowly fix them. You can quiet your worries about being an impostor and keep those negative thoughts from affecting your interviews.
Everything you could know
Here’s how impostor syndrome works.
Software engineering is a massive field. There’s a huge universe of things you could
In comparison to the vast world of things you could
know, the stuff you actually
know is just a tiny sliver:
That’s the first problem. It feels like you don’t really know that much, because you only know a tiny sliver of all the stuff there is to know.
The expanding universe
It gets worse: counterintuitively, as you learn more, your sliver of knowledge feels like it's shrinking
That's because you brush up against more and more things you don’t know yet. Whole disciplines
like machine learning, theory of computation, and embedded systems. Things you can't just pick up in an afternoon. Heavy bodies of knowledge that take months
So the universe of things you could
know seems to keep expanding faster and faster—much faster than your tiny sliver of knowledge is growing. It feels like you'll never be able to keep up.
What everyone else knows
Here's another common cognitive bias: we assume that because something is easy for us, it must be easy for everyone else. So when we look at our own skills, we assume they're not unique. But when we look at other
people's skills, we notice the skills they have that we don't have.
The result? We think everyone’s knowledge is a superset of our own:
This makes us feel like everyone else is ahead of us. Like we're always a step behind.
But the truth
is more like this:
There's a whole area of stuff you know
that neither Aysha nor Bruno knows. An area you're probably blind to, because you're so focused on the stuff you don't know.
We’ve all had flashes of realizing this. For me, it was seeing the back end code wizard on my team—the one that always made me feel like an impostor—spend an hour trying to center an image on a webpage.
It's a problem of focus
Focusing on what you don't know causes you to underestimate what you do
know. And that's what causes impostor syndrome.
By looking at the vast (and expanding
) universe of things you could
know, you feel like you hardly know anything.
And by looking at what Aysha and Bruno know that you don't know, you feel like you're a step behind.
And interviews make you really
focus on what you don't know. You focus on what could go wrong. The knowledge gaps your interviewers might find. The questions you might not know how to answer.
Just because Aysha and Bruno know some things you don't know, doesn't mean you don't also know things Aysha and Bruno don't know.
And more importantly, everyone's
body of knowledge is just a teeny-tiny sliver of everything they could learn. We all
have gaps in our knowledge. We all
have interview questions we won't be able to answer.
You're not a step behind. You just have a lot of stuff you don't know yet. Just like everyone else.
The 24 Hours Before Your Interview
Feeling anxious? That’s normal. Your body is telling you you’re about to do something that matters. The twenty-four hours before your onsite are about finding ways to maximize your performance.
Ideally, you wanna be having one of those days
, where elegant code flows effortlessly from your fingertips, and bugs dare not speak your name for fear you'll squash them. You need to get your mind and body in The Zone™
before you interview, and we've got some simple suggestions to help. 5)
Why You're Hitting Dead Ends In Whiteboard Interviews
The coding interview is like a maze
Listening vs. holding your train of thought
Finally! After a while of shooting in the dark and frantically fiddling with sample inputs on the whiteboard, you've came up with an algorithm for solving the coding question your interviewer gave you.
Whew. Such a relief to have a clear path forward. To not be flailing anymore.
Now you're cruising, getting ready to code up your solution.
When suddenly, your interviewer throws you a curve ball.
"What if we thought of the problem this way?"
You feel a tension we've all felt during the coding interview: "Try to listen to what they're saying...but don't lose your train of thought...ugh, I can't do both!"
This is a make-or-break moment in the coding interview. And so many people get it wrong.
Most candidates end up only half understanding what their interviewer is saying. Because they're only half listening. Because they're desperately clinging to their train of thought.
And it's easy to see why. For many of us, completely losing track of what we're doing is one of our biggest
coding interview fears. So we devote half of our mental energy to clinging to our train of thought.
To understand why that's so wrong, we need to understand the difference between what we
see during the coding interview and what our interviewer
The programming interview maze
Working on a coding interview question is like walking through a giant maze.
You don't know anything about the shape of the maze until you start wandering around it. You might know vaguely where the solution is, but you don't know how to get there.
As you wander through the maze, you might find a promising path (an approach, a way to break down the problem). You might follow that path for a bit.
Suddenly, your interviewer suggests a different path:
But from what you can see so far of the maze, your approach has already gotten you halfway there! Losing your place on your current path would mean a huge step backwards. Or so it seems. That's
why people hold onto their train of thought instead of listening to their interviewer. Because from what they can see, it looks like they're getting somewhere!
But here's the thing: your interviewer knows the whole maze
. They've asked this question 100 times.
I'm not exaggerating: if you interview candidates for a year, you can easily end up asking the same question over 100 times.
So if your interviewer is suggesting a certain path, you can bet it leads to an answer.
And your seemingly great path? There's probably a dead end just ahead that you haven't seen yet:
Or it could just be a much longer route to a solution than you think it is. That actually happens pretty often—there's an answer there, but it's more complicated than you think.
Hitting a dead end is okay. Failing to listen is not.
Your interviewer probably won't fault
you for going down the wrong path at first. They've seen really smart engineers do the same thing. They understand it's because you only have a partial view of the maze.
They might have let you go down the wrong path for a bit to see if you could keep your thinking organized without help. But now they want to rush you through the part where you discover the dead end and double back. Not because they don't believe you can manage it yourself. But because they want to make sure you have enough time to finish the question.
But here's something they will
fault you for: failing to listen to them. Nobody wants to work with an engineer who doesn't listen.
So when you find yourself in that crucial coding interview moment, when you're torn between holding your train of thought and considering the idea your interviewer is suggesting...remember this: Listening to your interviewer is the most important thing.
Take what they're saying and run with it. Think of the next steps that follow from what they're saying.
Even if it means completely leaving behind the path you were on. Trust the route your interviewer is pointing you down.
Because they can see the whole maze. 6) How To Get The Most Out Of Your Coding Interview Practice Sessions
When you start practicing for coding interviews, there’s a lot to cover. You’ll naturally wanna brush up on technical questions. But how
you practice those questions will make a big difference in how well you’re prepared.
Here’re a few tips to make sure you get the most out of your practice sessions. Track your weak spots
One of the hardest parts of practicing is knowing what
to practice. Tracking what you struggle with helps answer that question.
So grab a fresh notebook. After each question, look back and ask yourself, “What did I get wrong about this problem at first?” Take the time to write down one or two things you got stuck on, and what helped you figure them out. Compare these notes to our tips for getting unstuck
After each full practice session, read through your entire
running list. Read it at the beginning of each practice session too. This’ll add a nice layer of rigor to your practice, so you’re really internalizing the lessons you’re learning. Use an actual whiteboard
Coding on a whiteboard is awkward at first. You have to write out every single character, and you can’t easily insert or delete blocks of code.
Use your practice sessions to iron out that awkwardness. Run a few problems on a piece of paper or, if you can, a real whiteboard. A few helpful tips for handwriting code:
Set a timer
- Start in the top-left corner. You want all the room you can get.
- Leave blank space between each line of code. This makes it much easier to add things later.
- Slow down. Take an extra second to think of descriptive variable names. You might be tempted to move faster by using short variable names, but that actually ends up costing more time. It’ll make your code harder to debug!
Get a feel for the time pressure of an actual interview. You should be able to finish a problem in 30–45 minutes, including debugging your code at the end.
If you’re just starting out and the timer adds too much stress, put this technique on the shelf. Add it in later as you start to get more comfortable with solving problems. Think out loud
Like writing code on a whiteboard, this is an acquired skill. It feels awkward at first. But your interviewer will expect you to think out loud during the interview, so you gotta power through that awkwardness.
A good trick to get used to talking out loud: Grab a buddy.
Another engineer would be great, but you can also do this with a non-technical friend.
Have your buddy sit in while you talk through a problem. Better yet—try loading up one of our questions on an iPad and giving that to your buddy to use as a script! Set aside a specific time of day to practice.
Give yourself an hour each day to practice. Commit to practicing around the same time, like after you eat dinner. This helps you form a stickier habit of practicing.
Prefer small, daily doses of practice to doing big cram sessions every once in a while. Distributing your practice sessions helps you learn more with less time and effort in the long run
part -2 will be upcoming in another post !
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I'm sure some people will be wondering about the status of the NanoFusion project going forward. Naturally, the outcome of the Nano Build-Off was pretty disappointing for me personally. After initially receiving such a wave of positive feedback here on reddit, it was unfortunate to not even crack the top 20 projects.
In spite of that result, I think the community's desire to see a trustless privacy protocol in the Nano ecosystem is actually quite strong. I believe this Build-Off result is primarily a reflection of the judging criteria, which skewed strongly towards apps that were already somewhat polished, and able to be tested by one person within the space of 10 minutes. This naturally disfavours a project like NanoFusion which is still a proof-of-concept, and requires multiple participants in order to properly use it. All that to say, while I applaud the winning projects for their efforts, and extend my gratitude to Nanillionaire for sponsoring the event, I don't believe that the Build-Off result gives a full picture of the community's true priorities for future development of the Nano ecosystem.
Nevertheless this result points to a stark reality: NanoFusion is not yet ready for consumer use, not by a long shot.
What will it take for NanoFusion to be consumer-ready? Protocol and Reference Implementation Status
There is a small amount of work to be done to finish the reference implementation of the protocol. The binary tree of input mix accounts has been constructed, but the code is not yet written to actually execute the mix, nor to trigger and execute refunds where necessary. That is really the last step that needs to be completed for the reference implementation, and it's not especially complicated. The tricky bit is that there are still a few bugs around communication between the clients that need ironing out. But those are relatively minor bugs, I'm confident they won't require fundamental changes to the protocol or the implementation architecture.
However, once the reference implementation is complete, that is where a whole new set of challenges begins. Wallet Integration
The primary challenge will be to integrate NanoFusion into one or more popular wallets. For a privacy protocol to be most effective, we need as many people as possible using it. In a cryptocurrency like Nano, where transactions and addresses are all publicly visible on a block explorer, privacy is achieved by making it difficult to determine which transactions belong to you. Making it difficult is a matter of having your transactions get "lost in the crowd". The crowd of transactions that might
potentially be yours is called the "anonymity set". We need that anonymity set to be as large as possible, which means we need as many people participating in Fusion events as possible.
The best way to achieve this is to get NanoFusion adopted by popular wallets, and ideally to have it enabled by default. The less decisions that a user needs to make in order to start participating, the better.
This raises one very important question. How do we make it as easy and appealing as possible for the developers of popular wallets to integrate this technology? Workflow Design
In order to make NanoFusion integration appealing
to wallet developers, I believe we need to gear NanoFusion integration around workflows that actually work for end-users of the wallet. This is not as simple as it appears.
The Nano ecosystem is currently geared around the assumption that addresses will tend to be re-used for many sends and receives. This is almost intrinsic to the ORV consensus mechanism. You keep your funds in one account, and the voting weight for that account is assigned to your representative.
In a UTXO-based cryptocurrency, BCH in particular, it is much more normal to use a separate subaddress for every incoming transaction. CashFusion on BCH works by taking all your different receive addresses and mixing the funds from those addresses together (along with the funds of many other people's subaddress sets). But on Nano it's different. Imagine you have an online store accepting Nano funds via BrainBlocks integration. If you receive 100 payments, you might have BrainBlocks forward them all to just one account that you own. But this makes it trivial for a customer to look at the block explorer and see all of your sales volume, which completely undermines your privacy.
In the context of something like BrainBlocks, it's easy to see how our e-commerce store could generate a new address for each transaction, and have BrainBlocks forward funds to that new address. Then we could run NanoFusion later to obscure the linkages between our individual sales. But what about addresses that are shared in public? Lots of people put up single Nano addresses to receive donations, etc. What does NanoFusion do with those? For NanoFusion to be most effective, a given user should NOT have just one input and one output account in the mix. It makes it too easy for their input and output accounts to be linked (at least to a moderate-to-high degree of probability) by the publicly visible amounts in the accounts.
For NanoFusion to be most effective, we need to develop a culture where it is normal for people to use a new address each time they receive some nano. How do we make it appealing for wallet developers to build their wallets this way? I don't really know. The only example of this pattern that I know is Nanonymous (https://github.com/LilleJohs/Nanonymous
). We could potentially implement something like stealth addresses, so that the user really gives out one canonical public address, but a different receive address is actually used for each transaction "under the hood". However, that adds a whole new layer of complexity. It means wallets have to be upgraded to know how to interact with a stealth address. API Design
Even if we could arrange things so that it was more common for individuals to have multiple input accounts to mix, we would still be left with another question. What would wallet developers want the API for NanoFusion to look like? By nature, NanoFusion requires a large number of messages to be sent back and forth between all of the mix participants. For security reasons, those messages cannot be sent all at once. Player A has to wait for Player B to send message 1 before it is safe (cryptographically) for Player A to reveal the content of message 2.
Where To From Here? Technical Reflections
Thinking through all of these practical challenges has given me a new perspective on the whole issue of cryptocurrency privacy protocols. I have a much greater respect for what has been achieved by the Monero project. In Monero, everyone actually uses
the privacy protocol. As described above, that is no small accomplishment. Even though the privacy protocols for Dash, ZCash, BTC and BCH do basically work, their use is not widespread. Even leaving aside the issue of the extra transaction fees incurred (which is not such a problem for Nano), these optional privacy protocols are just not that convenient to use. Because not everyone uses them, the anonymity set is not nearly as large as it could be. And because not everyone uses them, transactions you do before and after a mix/fusion event leak metadata which can be used to undermine the privacy that you gained by using the privacy protocol in the first place.
Inevitably, NanoFusion will also suffer from this problem. Suppose that 20% of the Nano community starts regularly participating in fusions (a very generous estimate, given the low adoption rate of optional privacy features in the other cryptocurrencies mentioned). That still leaves the large majority of transactions probably re-using addresses most of the time. This means that the non-private majority will leak fresh metadata whenever they interact with accounts that were previously obscured through NanoFusion. This is not an easy problem to overcome. It can only be done with a culture shift towards ubiquitous privacy, and that can probably only be achieved by all major wallets agreeing to enable privacy features by default. Not an easy hill to climb. Personal Circumstances
For the sake of transparency, I also want to mention that I will be stepping back from NanoFusion for a while. This is simply a necessity of life. Our first child will be born in a few months. Once that happens, I will obviously have a lot going on and much less time available to work on these kinds of side projects. Between now and then, I need to focus on other projects which have more potential to generate some income for my little family. I'm a dad now(!), and my family comes first.
I'm very glad to have (hopefully) contributed some useful groundwork for the process of bringing privacy to Nano. This project also gave me the chance to learn some new technologies at a much deeper level, I'm grateful that too. Neverthless, for the foreseeable future, I'll be stepping back. I don't make that decision lightly. I put a lot of blood, sweat and tears into bringing NanoFusion this far, so I definitely hope it doesn't just fall by the wayside. I hope others will pick it up and run with it in my absence. Call to Action
Want to make NanoFusion happen? Here's what we really need next:
- Wallet Developers - we need you to speak up. Tell us, what would an ideal NanoFusion API look like? How can we make it as easy as possible for you to integrate NanoFusion into your wallet app? What programming language do you want to use to consume that API? What I would love to see is several wallet developers collaborating together to create a document describing their ideal API. That will make it much easier for potential developers to pick it up and start implementing it.
As always, details of the project are available at http://nanofusion.casa
(including demo videos, technical whitepaper and the link to the GitHub repo).
God bless everyone, thank you to all those who have followed along and offered so much encouragement for this project.
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