Problem-Solving for Developers - A Beginner's Guide
Summary
TLDRIn this video, the creator discusses the critical skill of problem-solving in software development, using the real-world scenario of merging over 600 pull requests on GitHub. The script outlines seven concepts to tackle coding problems efficiently, emphasizing the importance of understanding the problem, researching, breaking it down, and using tools like the GitHub API. It also highlights the value of pseudocode, test-driven development, and the iterative process of refining code. The video encourages viewers to practice, seek feedback, and appreciate the continuous learning journey in programming.
Takeaways
- 😀 Problem-solving is a critical skill for software developers, often more important than knowing every feature of a programming language.
- 🔍 Identifying and understanding the nature of the problem is the first step in solving it, which can save time and effort in the long run.
- 📚 Researching and refining the problem by learning from others' solutions is encouraged, as it can provide a solid starting point for your own code.
- 👥 Collaboration and discussion with other developers can lead to innovative solutions and help break down larger problems into smaller, more manageable tasks.
- 🔬 Utilizing APIs like GitHub's GraphQL API can help automate tasks, such as merging pull requests, which would otherwise be repetitive and time-consuming.
- 📝 Writing pseudocode is an effective way to outline code logic before diving into actual implementation, focusing on structure rather than syntax.
- 🔄 Test-driven development is a recommended practice that can help ensure the quality and reliability of your code by catching issues early.
- 💡 Implementing a working prototype quickly, even if imperfect, can boost confidence and provide a solid foundation for further refinement.
- 🛠️ Continuously improving code through practices like better naming, adding comments, and optimizing algorithms leads to more maintainable and efficient code.
- 🎼 Problem-solving in programming is like learning a musical instrument; it requires consistent practice and gradual improvement to master.
- 👨🏫 Seeking feedback from more experienced developers can accelerate learning and help you overcome challenges in your coding journey.
Q & A
What problem did the speaker create by offering to mail a sticker to anyone who submitted a pull request?
-The speaker ended up with over 600 pull requests to review and merge, which would have taken a significant amount of time to do manually.
What is the speaker's perspective on the importance of programming in solving problems?
-The speaker views programming as a powerful tool for eliminating manual and repetitive work, which is one of the fundamental problems that software is designed to solve.
What does the speaker consider the most important skill of a software developer?
-The speaker considers problem-solving to be the most important skill of a software developer, as it enables developers to ship code faster and perform better in technical interviews.
Why does the speaker emphasize the importance of understanding the problem before jumping into solutions?
-The speaker emphasizes this because spending time understanding the problem allows for more effective and efficient solutions, and it's a key part of the problem-solving process.
What does the speaker suggest doing before starting to code as a way to break down the problem?
-The speaker suggests researching and refining the problem, discussing the idea with other developers, and using APIs to understand the tools and requirements needed to solve the problem.
What is the purpose of writing pseudocode according to the speaker?
-Writing pseudocode helps to outline the logic of the code without worrying about syntax or implementation details, making it easier to focus on the structure and flow of the solution.
Why is exploring the API before implementing the code valuable according to the speaker?
-Exploring the API beforehand helps to understand the schema and requirements, making the implementation process easier and more efficient.
What is the speaker's approach to writing tests for their code?
-The speaker advocates for test-driven development, writing tests before implementing the code to ensure the validation logic is correct and to prevent regressions in the code.
What does the speaker suggest doing after implementing a working prototype of the code?
-The speaker suggests taking a break, reflecting on the code, and then improving it by enhancing readability, adding comments, removing duplication, and optimizing algorithms.
How does the speaker describe the process of becoming good at problem-solving in programming?
-The speaker describes it as a skill that is developed through practice, repetition, and learning from feedback, similar to learning a musical instrument.
What advice does the speaker give for dealing with a difficult problem in coding?
-The speaker advises taking a break and focusing the mind elsewhere for a short period, as the subconscious can continue working on the problem, often leading to an 'aha' moment.
Outlines
😀 Automating Code Reviews: A Real-World Problem
The speaker introduces a personal challenge of having to manually review and merge over 600 pull requests on GitHub, which sparked the discussion on the importance of problem-solving skills in software development. The video aims to explore seven concepts that can enhance coding problem-solving abilities, emphasizing the shift from learning a programming language to mastering the art of tackling problems efficiently. The example of automating the merging of pull requests using programming is used to illustrate the elimination of manual, repetitive tasks, a fundamental issue software aims to solve.
🔍 Problem Identification and Breakdown
The speaker outlines the first step in problem-solving: identifying and understanding the problem at hand. In this case, the issue is the need to merge a large number of pull requests on GitHub without manual intervention. The speaker explains the process of defining the problem with context, explaining why it's an issue, and summarizing the benefits of solving it. The problem is then broken down into smaller, more manageable sub-problems, such as validating each pull request and researching the GitHub API to ensure it can support the required tasks.
📝 Pseudocoding and API Exploration
The speaker discusses the importance of pseudocoding as a means to outline the logic of the code before diving into syntax and implementation details. This method allows for a focus on naming and readability. The speaker also highlights the value of exploring the GitHub API using tools like Insomnia to understand the schema and ensure it meets the project's requirements. The process includes writing a GraphQL query to retrieve open pull requests and planning a function to validate and merge them, emphasizing the need for clear and concise pseudocode to guide the actual coding process.
👨💻 Implementing Code and Testing
The speaker moves on to the implementation phase, advocating for a quick prototype approach to get a working model as soon as possible, even if it's not perfect initially. The focus is on getting all tests to pass and having a functional base to build upon. The video also touches on the optional but recommended practice of test-driven development, where tests are written before the code to ensure the validation logic is correct. The process of writing tests, implementing code to pass those tests, and then refactoring is described, highlighting the benefits of this approach for catching issues and preventing regressions.
🛠 Refining and Optimizing Code
After implementing a working prototype, the speaker suggests taking a break to allow the subconscious to work on any lingering issues. Upon returning, the speaker recommends reflecting on the code and looking for areas of improvement, such as enhancing readability, adding comments, removing duplication, and proving the time and space complexity of algorithms. The importance of continuous learning and practice in problem-solving is emphasized, along with seeking feedback from more experienced developers to improve one's skills.
🎓 Conclusion and Call to Action
In conclusion, the speaker wraps up the video by reiterating the importance of practice and feedback in mastering problem-solving skills. They encourage viewers to share their thoughts in the comments and to consider becoming a pro member at Fireship.io for more in-depth learning. The speaker thanks the audience for watching and looks forward to the next video, ending with a motivational note on the journey of learning to program and the development of the mind's ability to visualize computer system solutions to problems.
Mindmap
Keywords
💡Problem Solving
💡Pull Request
💡Code Review
💡Programming
💡Software Developer
💡Whiteboarding
💡Context
💡Research
💡API (Application Programming Interface)
💡Pseudocode
💡Test-Driven Development
💡Implementation
💡Practice
Highlights
The speaker created a problem by offering to mail stickers to anyone who submitted a pull request, resulting in over 600 code changes to review and merge.
Programming is introduced as a solution to eliminate manual, repetitive work, a fundamental problem that software aims to solve.
The importance of problem-solving skills over language-specific features is emphasized for software developers.
Highly experienced developers are characterized by their problem-solving abilities rather than just their knowledge of programming languages.
Problem-solving is identified as a critical skill in technical interviews, where the thought process is valued over memorization of syntax.
The speaker suggests that everyone's problem-solving approach is unique and encourages following one's instincts.
The first step in problem-solving is to identify and understand the nature of the problem, as illustrated by the speaker's experience with pull requests.
The importance of context in defining a problem is highlighted, with the example of optimizing the merging of pull requests on GitHub.
Research and refinement of the problem is suggested as the second step, including discussing ideas with other developers and using APIs.
The use of GitHub's GraphQL API is proposed for retrieving and validating pull requests, breaking down the larger problem into smaller subproblems.
Pseudocode is introduced as a method to outline code logic before implementation, focusing on the structure rather than syntax.
The benefits of writing pseudocode for readability and naming clarity are discussed.
Exploring an API before coding is recommended for understanding its capabilities and limitations.
Test-driven development is introduced as a best practice, emphasizing the value of writing tests before implementing code.
The red-green-refactor process is explained as a method to improve code quality through iterative testing and refinement.
The implementation phase is described as getting a working prototype done quickly, even if it's not perfect initially.
The psychological aspect of solving problems is touched upon, suggesting that taking breaks can lead to solutions through subconscious processing.
Improving a working prototype is easier than writing perfect code from the start, with a list of improvement strategies provided.
The importance of continuous learning and practice in problem-solving is emphasized, likening it to developing calluses on a musician's fingers.
Getting feedback from more experienced developers is suggested as a way to improve one's coding skills and problem-solving abilities.
Transcripts
houston we have a problem I created a
bit of a problem last week by offering
to mail a sticker to anybody who
submitted a pull request to this repo
and now I'm stuck with over 600 code
changes to review and merge I could sit
at my computer for a few days and
manually merge each one by clicking a
button but luckily we have this awesome
thing called code that lets us do this
thing called programming to solve
problems like this in today's video
we'll look at the steps involved in what
many consider to be the most important
skill of a software developer problem
solving well look at seven different
concepts that can help you solve coding
problems quickly and reliably when you
become comfortable with these concepts
you'll be able to ship code faster and
be more comfortable in technical
interviews we can use my real-world
problem with pull requests as an example
what we have here is a very specialized
use case but it represents one of the
most fundamental problems that software
solved the elimination of manual
repetitive work many new developers
start their programming journey focused
on learning a language and that's
perfectly fine because obviously you
need to know a language to solve
problems with code but when you get to
know highly experienced developers
you'll realize that their skill set is
more about problem solving than it is
about knowing every single feature of
the language that use that's why most of
the top companies have you do
whiteboarding problems and interviews
they want insight into your thought
process when you approach a software
development problem because that skill
is much more difficult to learn than
memorizing the syntax of a programming
language it takes years of experience
and practice to get good at but once you
have it down you'll be able to
confidently turn your ideas into reality
through the magic of code and you won't
even need YouTube channels like this for
tutorials but in the meantime make sure
to subscribe and hit the notification
bellow so you don't miss the next
sticker giveaway now I want to start
things off by saying that everybody's
brain is different and there's no one
universal right way to solve a problem
I'm going to show you techniques that
work well for me but follow your
instincts and do what works best for you
the first step is to identify and
understand the nature of the problem if
I had an hour to solve a problem I'd
spend 55 minutes thinking about the
problem and five minutes thinking about
solutions in our case we have six
hundred pull requests on github and we
don't want to have to click this stupid
button six hundred times so what we have
here is an internal optimization that
will hopefully save us time and money
but there are many different types of
software problems out there you might
have a bug and existing software where
you have to look through the application
stack trace and figure out the root
cause or you might have a more abstract
problem like the user experience that
tends to be such a big problem
that many teams break things down into
epic stories and themes through the
agile approach when defining a problem I
first like to start with context we have
more than 600 pull requests on github
that must be merged then explain why
that's an issue it would take hours of
mindless code review and button clicking
to get that done and lastly summarize
why we should solve this problem it can
be automated with the github API to save
us time and money so now that we've
decided this problem is worth our time
we can break it down into a bunch of
smaller problems I remember when I first
got into development I'd often asked
myself where do I start I would have a
clear vision of what I wanted to build
but just no idea how to put things in
motion and that brings us to step number
two research and refine the problem and
how do you do that
of course you google it and then click
on the first Stack Overflow result that
comes up just copy and paste that into
your codebase and the problem is solved
in all seriousness you should go out and
research what other people have done to
solve the same problem because you're
likely not the first one and it's
perfectly okay and typically encouraged
to use other people's solutions as a
starting point just make sure you
confidently understand what the code
does before using it now in our case we
have a pretty specialized problem not
many people have to concurrently merge
600 pull requests if possible discuss
the idea with other developers I want to
give a shout out to Christian wheeler on
github who opened an issue that started
the discussion about how we can merge
all these pull requests he provided a
bash script that we can run from the
command line but after doing some more
research we realized that we would need
to validate every single pull request by
ensuring that each person who made a
submission only modified the one file
that they were authorized to modify and
that breaks our larger problem into a
smaller one of how do we validate each
individual pull request
luckily github has a really nice graph
QL API that we can use to retrieve
information from github servers about
our account but before I started writing
any code I did some research first to
make sure the API supported what I
wanted to do we can further refine the
problem into two smaller objectives
retrieve all the pull requests from
github and then merge each one
individually by researching the API
documentation on github I was able to
confirm that it supports these
requirements now at this point we have
our main problem broken down into a few
subproblems and we've done research on
the tools and api's that can support
these requirements in most situations
there will be more than one way to solve
a problem like in this case I could use
the graph QL API or the REST API so make
sure to weigh the pros and cons of
alternative approaches and now we're
ready for step three pseudocode
in this step our goal is to write an
outline for how we will implement our
code you could do this on a white board
a piece of paper or directly in your
editor the idea is that you focus on the
logic of your code without having to
worry about the syntax or implementation
details if you're very comfortable in a
language like in my case JavaScript I
recommend writing your pseudocode in
that language in this case here I start
with a main function and then inside
that function I know I'll need a graph
QL client I'm not sure where I'll get it
so for now I'm just using this as a
placeholder and I know it's going to
need an auth token to authenticate with
the github API from there I'll need to
retrieve all the open pull requests
using a graph QL query and then I'll
write a function to validate each one
before emerging it in the function body
I'll add some comments about the
validations that we want
run inside this function they say there
are only two hard things in programming
cache and validation and naming things
an added benefit of writing pseudocode
is that you can focus on naming things
before your code gets filled up with a
bunch of other syntax so it's a great
way to increase your code readability
then from there we'll set up a for loop
and if the pull request is valid then
we'll go ahead and merge it with a graph
QL mutation and now we have a general
idea of how we'll implement our code now
because we're working with an API it's
also very valuable to explore that API
before you dive into it to do that I'm
using an app called insomnia that allows
me to make requests to the API before I
actually implement the code in
JavaScript graph QL makes this
especially nice because we can see the
entire schema of the API without ever
having to leave this app I have an
entire video dedicated to graph QL if
you want to learn more about it but the
code itself is pretty self describing
our query first makes a reference to the
git repo and then we fetch ten pull
requests that have a state of open and
then we grab the fields that we know
we'll need in our algorithm like the
changed files the author and so on but
the bottom line here is that
understanding the API will make it much
easier to implement the solution when we
get to the code and now we're ready for
the next step which is optional but
highly recommended test-driven
development if you're building a
critical feature that your business
depends on you should test it and yet
another skill of an experienced
developer is understanding what test
will be valuable for that feature and
really the only way to get good at that
is to start writing tests and see where
they add value to your codebase in this
example I think a valuable test would be
one that checks our validation logic to
ensure that the username that requested
a sticker is the same as the username
that made the pull request the basic
process looks like this we start by
writing a test that describes what we're
actually testing then we execute our
code using some mock data and lastly if
we write an expectation expecting the
return value of that code to be a
certain shape in this case it should be
the value of true from here we could
expand on this by adding additional test
cases with more mock data and we can
keep doing this until we're confident
that our code can handle any situation
that we throw at it but one thing you
might have noticed is that we're writing
this test before we've written or
implemented any actual code why would we
do that
it's not always practical but writing
your test before you write your code can
be extremely valuable because it takes
you through the red green refactor
process you start by writing a failing
test that forces you to think about what
you're trying to do then you figure out
how to do that thing by
implementing some code that makes the
test pass and from that point you can
reflect on what you've done and try to
simplify or optimize your code when you
write good specs they'll be able to
catch issues in your code much quicker
than you can manually debug them and
they also help prevent regressions in
your code when you go back to refactor
things later on and now we're ready to
move on to the easy part the
implementation details now personally
when I go to implement code I try to get
it done as quickly as possible or in
other words have all my tests passing
and have a working prototype in the
least amount of time possible even if
the code is not perfect and the reason
for that is psychological solving a big
problem is a collection of small steps
and when you try to perfect every small
step it takes a really long time to get
to the finish line and that can be
really discouraging
there's nothing worse for a developer
than to work on a project for weeks at a
time only to have the project cancelled
for one reason or another personally I
like to rush to implement my initial
code like I'm doing a hackathon when I
get to a full working prototype I now
have confidence that this problem can be
solved and now it's time to relax get a
good night's sleep and then reflect on
the code in fact here's a little pro tip
that I've learned over the years when
you find yourself banging your head
against the wall in a small problem for
hours just take a break and focus your
mind somewhere else for 15 minutes when
you come back you might magically solve
that problem in five minutes that might
sound silly or just too simple but Isaac
Asimov actually explains that it's your
subconscious still solving the problem
while your conscious mind is doing
something else and that's why people
often have aha moments right before they
go to sleep or in the shower now that we
have a full working prototype let's take
some time to reflect on it there are
many things you can look forward to
improve your code so here's a short list
improve readability by naming things
better add comments remove duplication
and prove the time and space complexity
of your algorithms add caching to reduce
cloud computing costs and improve your
air handling and so on and so on the
bottom line is that it's much easier to
improve a working piece of code than it
is to write a perfect piece of code on
the first go around the last thing you
should keep in mind is that problem
solving is a skill you never stop
learning there's an infinite number of
problems to solve each with its own
unique and novel challenges and you
should take practice seriously practice
we're talking about practice man at the
end of the day it doesn't matter which
programming language philosophy or
framework you use to solve the problem
the only thing that does matter is that
you solve a problem in my opinion the
best way to get good at this skill is to
it's just like a musical instrument
you're not going to pick it up and start
making music right away you have to
spend a huge amount of time practicing
and pushing yourself to overcome new
challenges when you learn to play the
guitar your fingers develop calluses
which build up over months of painful
plane when you learn how to program your
mind develops the ability to look at a
problem and visualize how a computer
system can solve that problem to become
really good at anything you have to
practice and repeat practice and repeat
until the technique becomes intuitive
and lastly get feedback from other
developers especially developers that
are more experienced than you it's easy
to feel self-conscious about your code
especially when you really care about it
but the more you do this the faster your
what the folks per minute will decrease
I'm gonna go ahead and wrap things up
there if you have things you want to add
to this video make sure to leave them in
the comments and if you want to build
entire apps with me consider becoming a
pro member at fire ship IO thanks for
watching and I will see you in the next
one
[Music]
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