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Code Review Essentials for Software Teams

Code Review is an essential part of any collaborative software project. Large software systems are usually written by more than one person, and so a highly functioning software team needs a robust process to keep its members, as well as the code base itself moving in the right direction.

Code Review is a powerful tool that:

  1. Helps team members adapt their mental model of the system as it’s changing
  2. Ensures the change correctly solves the problem
  3. Opens discussion for strengths and weaknesses of a design
  4. Catches bugs before they get to production
  5. Keeps the code style and organization consistent

It’s helpful to think of these benefits as a hierarchy of needs.

Code Review: Hiercharchy of Needs

Keeping Team Members Together

The most critical function of a Code Review is to keep every member of the team moving in the right direction. You can’t safetly change a system you don’t understand, and so Code Review keeps the team mentally aligned together. When Bob submits a pull request for the accounting subsystem, Amy keeps her mental model of that system updated as she reviews Bob’s code. Amy gets the chance to ask questions about pieces she doesn’t understand, and Bob gets the benefit of clarifying his design decisions as well as teaching someone else about his work. When Amy has to make a change to the accounting subsystem a month later, her mental model of the system is already up to date and ready for action. She spends less time reading code and trying to piece the system together in her brain, and more time thinking about higher level abstractions and designs. Everyone wins, because everyone stays together.

Executing a Good Pull Request

Before you even write a line of code changing the system, ask yourself the following questions:

  • “Is this the right thing to be working on?” There will always be competing needs from customers, internal team members and other parties. This can be a good way to keep priorities straight in your head before you dive in deep. Other processes like iteration / sprint planning meetings also help keep this on track.
  • “Does the team already agree that the change is the right one?” If not, it’d be better to start a design discussion by email or maybe in person. Your changes are more likely to get accepted when people are in agreement about the design before you change it.
  • “How can I break this change into digestable chunks that are easy to review and understand?” Small changes are easier to think about and understand. Good discussions flow from the team being able to comprehend your change quickly. If your change is massive, teammate’s eyes will glaze over, and you might only get a few style nitpicks from them.
  • “How am I going to test this change to kill bugs and ensure correctness?” You might have a QA department, but it’s still your job as the developer to ship quality working software. Easily testable software is usually more decoupled, is broken into smaller chunks, and easier to reason about. You need to have a testing plan for all your changes.

I’ve found that answering these questions ahead of time has saved me a lot of headache in the long run. The last thing you want to do is spend days coding up a change only to have it rejected based on fundamental design flaws or team disagreement. Or for your change to get held up because no one can verify it for correctness. Again, the goal is to change the system while keeping other team members up to date with your changes. Asking yourself about how you’re going to break your work into bite-sized chunks and test those chunks is helpful on many fronts:

  • It reduces risk
  • It makes changes easier to reason about
  • It pushes you towards a better design

You’d rather make many small, precise cuts with a scalpel than one giant gash with a machete. I prefer scalpel driven developement in most additive cases, and like to save the machete for when it’s time to delete large blocks of dead code.

Sending the Pull Request

Ok, so you’ve gotten buy-in from the team that your changes are good, and you’ve achieved the design you set out to build. What’s the most effective way to actually send your pull request? You’ve been working hard on your changes, and you want other members of your team to pay attention to your pull request and give you fast feedback. How can you do that?

Remember earlier when I said that the most important part of a code review is to keep the team’s collective mental model well aligned? Your other teammates are probably working on something completely different than you, maybe in a completely different part of the system. Their brains are in a completely different context, so you must overcome this by giving them the helpful guidance they need to do the review. This means writing a well-organized description of the changes you made, why you made them and any other relevant information they won’t get from just reading the code alone. Don’t make your teammates do more mental work than they have to.

Let’s look at some good and bad examples of pull request descriptions:

Bad Example:

Title: Fix uninitialized memory bug
Description: 

This is the bug Bob and I talked about earlier. I had
trouble with the compiler but managed to make this work. Let me
know what you guys think.

If you’re the developer of this pull request, stop and put yourself in your code reviewer’s shoes for a second. The title is vague, and raises more questions than answers: Where is the memory bug? How critical is this change? What was the bug that Bob and you talked about earlier? What trouble did you have with the compiler? The description doesn’t provide any helpful context about the problem, nor does it provide any helpful description of your changes. If this pull request is long, the reviewer is going to have to dive into the code and do mental gymnastics in an attempt to gain context before even getting a chance to think about how this change fits in to the coherent design of the system.

Here’s a improved example that helps clarify the changeset:

Title: Fix process crash on startup from uninitialized memory [#54633]
Description:

This bug was causing process crashes on boot due to a memory
initialization error in our statistics Counter class. I talked this
over with Bob, and we both agree the crashes are a rare edge case
that don't warrant a hot-fix release. Here's a summary of the
changes:

  - Moved the underlying int variable into the class initializer
    to prevent ununitialized memory in the Counter.
  - Reworked the Counter interface to simplify caller conditional
    logic and prevent further off-by-one counting problems.
  - Added a unit test that exposes the crash

Testing: I've verified the test suite still passes, and verified
manually that the crash doesn't happen locally.

A few things that have improved in this pull request description: The title is descriptive enough to give the reviewer some short context, and entice them to click on the email and learn more. The reviewer knows it’s a process crash (which is usually a really bad thing) and there’s also a bug report number where the reviewer can read more details about the bug report if they’re interested in understand more about the problem. The new description also outlines where the problem was occuring, and helps give some context about how critical the fix is. There’s a summary that lists the high level structural changes in the pull request, which will give the reviewer a mental picture of the changes before they even look at the code. Code reviewers should not be surprised with what they find. This example also outlines testing that was performed, which will give reviewers confidence that the changes were well thought out, well tested and ready to be merged. Set your reviewers up for success by making it stupid easy for them to click ‘merge’.

Reviewers: Giving Constructive Feedback

The next part of the review process to consider is giving constructive feedback to your peers. If the goal is clarity and alignment, giving quality constructive feedback helps everyone understand the system better and push towards better code.

Avoid saying things like:

  • “This design is broken.” Why is it broken? How can it be made better? Statements like this hurt confidence and can bruise egos.
  • “I don’t like this change.” Why don’t you like it? What would you like instead? It’s okay to not like something, but you should articulate your thoughts and provide helpful clues about how the code can be improved.
  • “Can you rewrite this to be more clear?” What’s wrong with what I have now? How should I rewrite it? What’s unclear? Comments like this are themselves unclear, and don’t give a simple path forward.

Instead, say things like:

  • “How does this code handle negative integers?” This feedback is specific, and causes the developer to think through the outcomes themselves. As a reviewer, you might know that the code in question crashes with negative integers, but it’s better to have the developer intuit this themselves. Questions like this might also be indicative of a testing gap, or a need for further specification of scope.
  • “This section is confusing to me, I don’t understand why class A is talking to class B” If the developer hasn’t provided a helpful description, and the code isn’t neatly structured, this kind of comment helps drive for clarity of design and cleaner code.
  • “It looks like you broke an interface boundary here. How will that affect the user?” You’ve pointed out an issue you noticed, giving them the benefit of the doubt that they meant to do it. Now they can think through the unseen ramifications of breaking the interface boundary and either provide a rationale for their decision, or choose to change it.

In general, framing feedback as questions is a good way to drive for clarity, correctness, and at the same time help the developer improve their designs in the future. This is usually how quality creative writing groups give each other feedback. In a creative writing setting, it’s harmful to say things like, “I don’t like this character.” whereas the same comment can be reframed more clearly: “In chapter one your character was warm and compassionate and now he’s cold and icey. He doesn’t seem like a real person to me.” Now there’s specific feedback that can be clarified to suss out the problem.

Programmers like to solve problems and point out issues, so by nature they like to discover and point out flaws. It’s tempting to see code reviews as a way to prove how smart you are by finding problems in your peer’s code. Don’t do it. Code review is a way to get more eyes on a change and suss out critical problems, but your goal should be to review in a way that encourages your team members to improve their skills while fixing the problems at hand.

Style Points

Brace positions, variable / function names, indentation and spacing issues should be addressed, but they are not the central purpose of good code review (notice that I put them at the top the code review pyramid). If you find that your team is spending 90% of it’s time nitpicking indentation and variable names, you’re probably wasting everyone’s time on something that could be mostly automated. Write up a style guide, enforce indentation and spacing issues on check-in and spend your time focusing on higher value issues. I don’t want to diminish the importance of a consistent style. On the contrary, having a consistent idiomatic style is one of the easiest ways to make your codebase easy to read and comprehend. Still, if you spend all of your code review focused on these simplistic tasks, ask yourself whether you’re avoiding the harder and more important work of keeping your team mentally aligned and thinking about higher level designs.

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Seeing Software Complexity

When you are first learning how to program a computer, your goal is to just make everything work correctly. There are mental hurdles you must climb to write your first program: What programming language should you use? Where do you type everything in? Where do all these semicolons go? Why does it say syntax error when everything looks correct? By the time everything actually compiles and runs, it feels like you’ve accomplished a great feat, and the task is complete. In reality, the first time your code builds and runs is just the beginning of what it means to build well-designed software.

Your first ever programs may get the job done, but their design will probably be a mess. When you build things in the real world, your mind grasps how the different parts of a design fit together much easier than when you’re studying the design of a software project. If I showed you a building made out of Legos, you would have no problem seeing all its individual parts, and understanding how each piece fits together with its neighbors. Building in the real world is both concrete and sensory. We can utilize all of our senses to understand the inner-workings of a design that is before us.

Software is not concrete, and it is not sensory. You can’t touch your code, and when you see your code, you only see symbols that represent some abstract design. The way the pieces of a program fit together must be kept in your head. When reading a book, you first read the words on the page and build a mental image from the words. When you’re reading a program, you must also read the words on the screen, but also reconstruct the mental image of the pieces of the software. You must see all the actors, map out the dependencies, recognize the contact points, and decigher all the interactions of your code. If you’re building a bridge, it’s easy to see if a support-beam is coming into contact with too many other pieces of the bridge. If you’re building software, seeing these connection points is an exercise in your ability to hold the structure clearly in your mind.

The more you program, the more you understand that the simplest way to hold a software design in your head is by making it simple. A program that is simple is easy to understand and easy to work with. Good programmers can look at a piece of code and recognize when it’s complex. Great programmers can look at a piece of code, recognize when it’s complex and then proceed to make it simple.

An airplane pilot I knew once told me that the most dangerous pilots are not the novices, and not the veterans, but the pilots just in between. They are the pilots who no longer have the fearful respect of a novice, nor the wisdom of an expert, but instead have the cockiness of an intermediate. They’ve got enough flying time under their belt that they don’t know how much they don’t know, and are dangerous because they believe themselves to much better than they really are.

A dangerous developer thinks they’re writing good code, perhaps because their variables are well named and their methods are short, but in reality their designs might be a tangled web of gunk. Seeing only superficial qualities like method length is how you miss the hidden complexities of your program. On the surface your code might be easy to read, but impossible to comprehend.

How can we defeat complexity in our programs? Many developers will reach for a design pattern, a codified best practice, or some other precscribed cookie-cutter recipe. Yes, applying a design pattern might help you, but rather than ask yourself which design pattern you should be using, ask yourself instead how easily can you visualize the design of the code in your head. As a starting point, some basic questions I like to ask are:

  1. How many moving pieces (objects, functions, actors) are in this code path?
  2. How much do the moving pieces know about each other?
  3. How much state is there to manipulate?
  4. How many branches are there into and out of my code?
  5. How many dependencies, both internal and external are there?

These questions are merely ways to assess code complexity - they are by no means exhaustive, nor are they always the right questions to ask. Complexity falls out of a system that is not understood, and is wound too tightly on itself. A program that is easily understood is often indicative of a system that is simple. If you cannot understand the design of your software, you have no control over it.

If I could ask one thing of you it would be this: practice seeing complexity. Not just in software, but all around you. Unlike many other things in this world, software changes easily. You have the power to make your software simple: See the complexity, know the complexity, and then destroy it.

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Making An Impact In Software

Do What You Want - Those are the most frightening four words brought to us by the connection revolution. If you want to sing, sing. If you want to lead, lead. If you want to touch, connect, describe, disrupt, give, support, build, question… do it. You will not be picked. But if you want to pick yourself, go for it. The cost is that you own the results. – Seth Godin, The Icarus Deception

It’s hard to break free from the the mental entrenchment of yesterday’s industrial economy: If you work harder, and do what the boss says, your career as a software developer will go exactly where you want it to go. This is not how you win in software. You don’t win by following directions, you don’t win by waiting for someone to tell you what to do, and you certainly don’t win by producing code the same way new cars roll off the factory line.

You win in software when you recognize that what you’re building are tools that create leverage and value that are bigger than yourself. Software scales, and bits are cheap to spread to everyone. We live in an era where a five person team has the potential to help millions of other people simply with the software they write and share with the world.

The scarcity isn’t access to the right tools - we have cloud computing, abundance of open source solutions, and more new programming languages than we know what to do with. The scarcity is the developer who knows how to take what they’re building and shape it in a way that reaches more people, touches more lives, and makes a bigger impact.

Software is changing the world faster than our minds can adapt to the change. Tomorrow’s problems demand solutions that you’ve never written before, and maybe never even thought about before.

Will you make an impact?

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Blake Smith

create. code. learn.