Is Your Code Too SOLID? (with transcript)

S A R A H
M E I
W D C N Z
2 0 1 5
I S Y O U R C O D E TO O
S O L I D ?
https://www.flickr.com/photos/pie4dan/4567311801
Hello! I gave this talk in July 2015 at WDCNZ in Wellington, New Zealand.

View Slide

DevMynd
S A R A H M E I
C H I E F C O N S U LTA N T
D E V M Y N D
U N I T E D S TAT E S
C H I E F O F BA L D E A G L E S
A N D F R E E D O M

http://world-map1.org/map1520769_0_0.htm
http://www.coolholidaygraphics.com/flagday/glittergraphics/flagdayglitter2.gif
https://www.devmynd.com/images/team/sarah-mei-cutout.png
I’m Sarah Mei. This is my dorky work picture, and I’m the Chief Consultant at DevMynd.

I’m from the United States, speciﬁcally San Francisco. The US, as you know, is the chief of
bald eagles and freedom. I copied that directly from the state department website…

View Slide

DevMynd
I’m a developer, and I work with a lot of Ruby and JavaScript.

View Slide

C O D E BA S E S
I WO R K O N
N O R M A L C O D E BA S E S
https://www.flickr.com/photos/pmarkham/5361277692
I’m usually working with teams managing large codebases that have become unwieldy and
hard to change. This is a common problem, right now, among developers of all persuasions.
In addition to the Ruby and JavaScript folks, I’ve heard it from folks who do .NET, python,
CSS, Java, and PHP.

This isn’t a new problem in the industry. IBM was having this problem in the 70s. It’s
interesting that it’s again at forefront of our collective consciousness right now, though.

View Slide

AT
F I R S T
https://www.flickr.com/photos/jakerust/16661140289/
One theory: code is easier to write than it used to be. There was the explosion of dynamic
languages in the past 10 years, but also new frameworks in compiled languages, and the
addition of usable functional languages. All of this has made it easier than ever to generate
code in volume. You can achieve a large, unwieldy codebase faster than ever before!

Perhaps even when you’re still a small company. You don’t need to be the size of IBM,
anymore, to have their codebase problems.

View Slide

https://www.flickr.com/photos/[email protected]/14184697490
These codebases are messy, but it doesn’t mean the teams failed at planning. Many teams
need, at ﬁrst, the type of very fast iteration that something like Rails brings. Companies that
planned ahead for a large codebase, and put structures in place, couldn’t iterate as quickly.
Some of them don’t exist anymore as a result.

For a business, a messy codebase that works is better than a well-structured one that
doesn’t. So we should all be so lucky as to have these problems.

View Slide

But we need to do something about it! We need to make working in these codebases suck
less, because this type of thing is what the vast majority of developers work on. We need to
make working on this code easy and fun again.

Some people attempt that maneuver this with microservices. That rant is another talk entirely.

View Slide

DevMynd
https://twitter.com/tenderlove/status/573907559871971328
Most companies who do microservices end up like this.

Carving services out of a monolith and carving objects out of a large class are the same skill.
If you haven’t been doing good object design in your main codebase, I guarantee you’re not
going to design a good set of services.

The skill is much easier to practice in a single codebase, where, if you’re wrong, you just
have adjust object boundaries. If you have to adjust service boundaries when you’re wrong,
the learning is much more expensive.

View Slide

DevMynd
https://twitter.com/tenderlove/status/573907559871971328
So before making microservices, I recommend teams get better at object-oriented design.
It’s perhaps not as shiny as microservices, but from a cost perspective, it’s more responsible.

Not coincidentally, we’ve been seeing a resurgence of interest in object-oriented design in
communities that weren’t that interested a few years ago - particularly the dynamic language
communities. There are now lots of books, and blog posts, and conference talks (including
this one) about software design.

View Slide

DevMynd
S A N D I M E T Z
E X P E RT AT
E V E RY T H I N G S E R I O U S LY, G E T I T
A M A Z I N G B O O K
http://www.sandimetz.com/ http://www.poodr.com/
This is the best of the modern takes on object design. Sandi Metz wrote this fantastic book
on understanding objects. I highly recommend you read it, even if you’re not a Ruby
developer.

View Slide

DevMynd
S A N D I M E T Z
E X P E RT AT
E V E RY T H I N G S E R I O U S LY, G E T I T
A M A Z I N G B O O K
http://www.sandimetz.com/ http://www.poodr.com/
Now, I love this book, and all the blog posts, and all the conference talks. But what I do in my
client work doesn’t really look anything like in there. The book uses example code being
written from scratch to show you how to put the right boundaries around your objects.

At ﬁrst, going into large, monolithic, messy codebases, where no one heeded Sandi’s advice,
and moving things around didn’t seem like ‘object-oriented design’ to me.

For a long time I called it ‘refactoring.’ It turns out, though, that those are not separate ideas.

View Slide

D E S I G N
D E C I D I N G
H OW TO
A R R A N G E C O D E
https://www.flickr.com/photos/matley0/3616669592
Before we go any further, I want to deﬁne some terms. Let’s start with software design. I’m
not talking about architecture, or systems, just within a single codebase - software design is
really nothing more (or less) than deciding how code is arranged.

View Slide

D E S I G N
D E C I D I N G
H OW TO
A R R A N G E C O D E
https://www.flickr.com/photos/matley0/3616669592
Many people think that software design is something completely separate from
programming. But in reality, when you’re programming, even if you’re not consciously making
any decisions, you’re still doing design. Every time you put a function in this object and not
that one, you’re doing design. You can try to do it ahead of time, and some people do, but
the vast majority of software design done by developers in our industry is inline.

Just like programming, you’ll be bad at it at ﬁrst, but just like programming, you get better at
software design the more you practice.

View Slide

O B J E C T- O R I E N T E D
D E S I G N
G R O U P I N G R E L AT E D
F U N C T I O N A L I T Y I N O B J E C T S
https://www.flickr.com/photos/mwanasimba/2901201955/
Now let’s be more specific and define object-oriented design. OOD is deciding how code
will be arranged, grouping related functionality in objects.

This does not sound anything like the wikipedia definition of OOD. It’s pretty abstract.
Perhaps it will help us to talk about what object-oriented design is NOT.

View Slide

DevMynd
A L A N G UA G E F E AT U R E
A WAY O F T H I N K I N G
O B J E C T- O R I E N T E D D E S I G N I S

https://www.flickr.com/photos/[email protected]/15635620289/
1. OOD is not a language feature. It’s a way of thinking.
You can write object-oriented code in CSS. You can write it in C, or JavaScript, or Java, or
C#, or Ruby. Languages with explicit syntax support for objects are what you’ll hear people
call “object-oriented languages.” That just means “languages in which it is more convenient
to make objects”, but that’s too long for a wikipedia page title, so…

Object-oriented design is a way of thinking about code arrangement. In some languages it’s
easier to express than others, but it’s possible anywhere.

Buy me a beer and ask me about object design in Haskell some time.

View Slide

DevMynd
A L A N G UA G E F E AT U R E
A WAY O F T H I N K I N G
O B J E C T- O R I E N T E D D E S I G N I S
A D E S T I N AT I O N
A M E A N S TO A N E N D

2. Object-oriented code is not a destination. It’s a means to an end.
You don’t write object-oriented code for its own sake, or because it’s somehow morally or
professionally “better.” No particular way of arranging code is inherently better than any other
way. Object-oriented design is a means that we use, mindfully, to move us toward some
goal.

And for most of us, that goal is ease of change.

View Slide

https://www.flickr.com/photos/redvers/532076662/
We build software for people who don’t really know what they want. They imagine one thing
but they change their mind when they actually see it in action. Or the business shifts focus.
Or a key person is replaced. Or it’s Tuesday - the only constant in software development is
that the end goal shifts as we build it. And it wouldn’t do us any good to wait, because the
act of building is what causes it to shift.

In theory, object-oriented design makes it easier to respond to shifting requirements.

View Slide

https://www.flickr.com/photos/redvers/532076662/
But I can tell you that. And Sandi can tell you that. But I’ll bet you most people in this room
have been on a project where the code was parceled out into objects, and that made it
harder to respond to shifting requirements, harder to change, rather than easier.

To ﬁgure out how that happens, we have to take a step back and consider our goals when
we’re designing software.

View Slide

H I G H
L OW
H I G H
L OW
C O S T O F U N D E R S TA N D I N G
C O S T O F C H A N G E
There are two useful axes to consider when we’re looking at diﬀerent ways to design
software.

On the bottom, we have the cost of understanding the code (low or high). This is how hard
is it to ﬁgure out what’s going on. On the side, we have cost of changing the code (low or
high).

Every choice about how you arrange code - every choice about software design - goes in
one of these quadrants.

View Slide

H I G H
L OW
H I G H
L OW
Let’s start with writing long procedures. Someone does a GET on /calendar to see their
calendar for the month, and a procedure is executed - a list of instructions. It determines the
date range, fetches events within that range from the database, draws the right shaped grid,
places the dates on them and returns that page to the user.

View Slide

H I G H
L OW
H I G H
L OW
Procedures
It’s pretty easy to understand what happens in a procedure. Cost of understanding is low.
Everything that happens is right there in an ordered list.

The tradeoﬀ, in a project with lots of long procedures, is that the cost of change is high. So
procedures belong in the upper left.

The biggest devil there is duplication, which forces you to change multiple places in the code
to make a single logical change. You’ll know you have this problem if you end up touching
every ﬁle in the project to make a change that seems like it should have been simple.

View Slide

H I G H
L OW
H I G H
L OW
Procedures
Some projects, having been burned by the high cost of change with procedures, go
completely in the other direction.

The system is made of innumerable tiny objects that each don’t do much. When you do that
GET on /calendar, a RouteReceiver picks up the call…

View Slide

CalendarParamMgr
GetCalendarIndex
CalendarRouteResolver
CalendarRouteResolverFactory
RouteResolver
RouteReceiver
The RouteReceiver creates a RouteResolver that looks at the URL and ﬁgures out that it
needs a CalendarRouteResolver, which it gets from a CalendarRouteResolverFactory, and
the CalendarRouteResolver looks at what you’re requesting and instantiates a
GetCalendarIndex object, which sends your params to a CalendarParamManager…and so
on.

The sequence of events isn’t written down anywhere in the code. You just have to trace it
through to ﬁgure it out. Little pieces of functionality are spread across many classes.

View Slide

H I G H
L OW
H I G H
L OW
Procedures
Set of Small Objects
A system like this is harder to understand than a procedure. The cost of understanding is
high. A list of instructions will always be easier to understand than a set of objects.

However, once you understand the system, the cost of change is low. Assuming you’ve got
the right abstractions (a notion we’ll deal with in a moment), it’s relatively easy to take, for
example, one params handler out and start using another. So a set of small objects goes
down in the lower right.

View Slide

H I G H
L OW
H I G H
L OW
Procedures
⚠⚡
Now let’s talk about this quadrant here. Danger zone! Code with a high cost of
understanding AND a high cost of change is the worst of both worlds.

There are two types of codebases here, both of which are distressingly common.

View Slide

H I G H
L OW
H I G H
L OW
Procedures
Really big objects

The ﬁrst is a codebase made up of really big objects. Perhaps the framework dictated an
initial set of classes, and all behavior just sort of accreted onto them.

The huge objects always seem to be the ones that are core to the application. They change
with almost every commit, and changes go wrong easily, because all that functionality in one
place means unintentional interference is almost a given.

View Slide

H I G H
L OW
H I G H
L OW
Procedures
Really big objects

The wrong set
of small objects

The other type of codebase is small objects gone wrong, which is what happens when you
try to break down a big class but don’t get the object boundaries quite right.

Then it’s both hard to understand, because it’s objects, and hard to change, because for
one logical change you still have to make changes in lots of diﬀerent places.

The wrong set of small objects is the worst-case scenario. Really big objects are bad, but not
that bad.

View Slide

H I G H
L OW
H I G H
Procedures

L OW
Really big objects

The wrong set
of small objects

So there are two questions here. The ﬁrst: how can we get to the lower left? Can we? Is that
the perfect solution that cannot exist?

The second: how do we move our big lumbering codebases out of the upper right? It doesn’t
really matter what direction we move; anywhere will be an improvement. But usually, when a
codebase is this size, reducing the cost of change is worth increasing the cost of
comprehension. So most people want to move down into sets of small objects.

View Slide

H I G H
L OW
H I G H
Procedures

L OW
Really big objects

The wrong set
of small objects

This is where they start reading about things like SOLID and design patterns, hoping they
can ﬁgure out how to make the move. Let’s talk about patterns brieﬂy before we dive into
SOLID.

View Slide

PAT T E R N S
https://www.flickr.com/photos/dakluza/6665460621
A pattern is an example set of object boundaries that seems to work well in many situations.

I’ll give you an example of a pattern called the Observer.

View Slide

O B S E R V E R
N E W E M A I L
User

Let’s say you have a User class, and when a new user is created, meaning someone has
signed up for your service, it automatically sends them an email to get them to confirm their
account. Normally this is fine. If your user class is small and your object graph is
uncomplicated, then it’s fine to leave this here.

But a lot of times, the user gets to be one of the biggest classes in the system, and it can be
annoying to have it send email every time you make one. You have to find ways to turn it off
when you’re creating a user in your tests, and every test requires you to create a user - so to
make it easier to turn off, you want to separate user creation from email sending.

View Slide

O B S E R V E R
User UserObserver

You create a new class UserObserver, and you move the email functionality over there.
UserObserver gets a creepy set of googly eyes so it can observe the User class.

View Slide

O B S E R V E R
User UserObserver

! E M A I L
N E W
Now when a new user is created, the UserObserver notices, and sends email. That’s cool,
right? You’ve reduced the size of your User class and made it easier to turn oﬀ email
sending. You’ve made the code easier to change. But you’ve also made it harder to
understand.

You used to only have to look one place to see everything that happened when a user was
created. It all happened in the User class. Now you have two places to look. Because it’s in a
separate class, other people may not know it exists, let alone that they have to turn it oﬀ, and
then be unpleasantly surprised when the users they create get emails.

View Slide

H I G H
L OW
H I G H

L OW

E A S I E R TO
C H A N G E
H A R D E R TO
U N D E R S TA N D
If you’re starting out with a codebase in the upper right quadrant and you apply the observer
pattern as we just talked about, you move it down here. (That’s the confounded face emoji, in
case you were wondering.) You’ve made it easier to change but harder to understand.

Applying a pattern improves changeability but worsens understandability.

View Slide

https://www.flickr.com/photos/betsyweber/5902421276
Patterns aren’t free. Many people read about patterns and then start looking for
opportunities to apply them. They assume that making less-structured code into patterns is
always a good idea. They don’t realize that everything has a cost.

And determining whether it’s worth it is the hard part. At what point does lower cost of
change outweigh higher cost of understanding? There’s no single answer. It’ll be different in
different parts of your code, and it will be different at different times in the same part of the
code.

View Slide

https://www.flickr.com/photos/grungetextures/4162992874
So while patterns give us ideas about how to break up code, it gives us no guidance on
when.

Let’s look at the principles and see if they help with that.

View Slide

S O L I D
https://www.flickr.com/photos/chrisjfry/309574260/
SOLID. It sounds so awesome! Who doesn’t want “solid” code? Or to be a “solid”
programmer? There are many object-oriented principles. Academia has been studying object
orientation for decades. However, academics tend not to deal in volumes of code, so most of
the principles are highly academic.

In the 90s, Robert Martin took the ﬁve principles that seemed the most relevant to working
software developers, and assembled this acronym. Let’s talk about what each letter means.

View Slide

N A M E S U M M A RY U T I L I T Y
S
O
L
I
D
We’ll be ﬁlling in this chart as we go. We have three columns:

1. The name of the principle

2. A summary of what it means (not what it says)

3. A measure of how useful it will be in our everyday developer life.

The ﬁrst letter of SOLID is S!

View Slide

S I N G L E R E S P O N S I B I L I T Y
P R I N C I P L E
S O L I D
https://www.flickr.com/photos/shenamt/8582808329/
S is for the single responsibility principle. It says that a class should have one
responsibility, or to put it another way, one reason to change. This was ﬁrst articulated by
Rebecca Wirfs-Brock in the 80s.

It’s a fancy way of saying that smaller things are easier to understand, and harder to mess
up, than larger ones.

View Slide

S S I N G L E
R E S P O N S I B I L I T Y
O N E R E S P O N S I B I L I T Y
P E R C L A S S
M E D
O
L
I
D
As far as utility goes, it’s sort in the middle. The difficulty hinges on the definition of
“responsibility.” If you’ve got a class that finds users, persists users, validates users, allows
access to its related objects, and contains business logic related to users, you could
plausibly say it’s got one responsibility: it manages the user.

View Slide

S S I N G L E
P E R C L A S S
M E D
O
L
I
D
You could equally plausibly say that all of those things are separate responsibilities that all
belong in diﬀerent classes. The principle doesn’t give you guidance because there is no
universal right answer. Sometimes it makes sense to put all that together; other times it
doesn’t. And that shifts over time, even for the same codebase.

The answer to every question in software development is “it depends.”

View Slide

O P E N / C L O S E D
P R I N C I P L E
S O L I D
O is for the open/closed principle. This is usually stated as “a class should be open to
extension but closed to modiﬁcation.” Bertram Meyer came up with this in the 80s.

It’s a fancy way of saying that editing existing code is more diﬃcult and more error-prone
than just adding new code, so: arrange your codebase such that we can add new
functionality just by writing new code.

View Slide

S S I N G L E
P E R C L A S S
M E D
O O P E N / C L O S E D
D O N ’ T E D I T C O D E ;
A D D N E W C O D E
L O W
L
I
D
As far as utility goes…it sounds great, doesn’t it? But it’s hard to conceive of how it could
ever happen in a codebase of signiﬁcant size. It’s not super practical day-to-day.

View Slide

L I S KOV S U B S T I T U T I O N
P R I N C I P L E
S O L I D
https://www.flickr.com/photos/vpickering/14416940341/
L is for the Liskov substitution principle. This is perhaps the most academic of the SOLID
principles. It is a precise, mathematical statement.

Here it is:

View Slide

DevMynd
Let Φ(x) be a property
provable about objects x of
type T. Then Φ(y) should be
true for objects y of type S
where S is a subtype of T.
Let theta(X) be a property provable about objects X of type T. Then theta(Y) should be true for
objects Y of type S where S is a subtype of T.

…ok…

View Slide

L I S KOV S U B S T I T U T I O N
P R I N C I P L E
S O L I D
https://www.flickr.com/photos/vpickering/14416940341/
It’s a fancy way of saying: anywhere you can use an instance of a class Foo, you should be
able to use an instance of class Bar that subclasses Foo. And nothing should go wrong.

The Liskov Substitution Principle was formulated by Barbara Liskov in 1987, when she was
in her late 40s.

View Slide

I T ’ S N E V E R
TO O L AT E TO
https://www.flickr.com/photos/wcouch/8578612563/
It’s never too late to be amazing.

View Slide

S S I N G L E
P E R C L A S S
M E D
A D D N E W C O D E
L O W
L L I S K O V
S U B S T I T U T I O N
I N H E R I TA N C E . I T ’ S A
T H I N G .
L O W
I
D
The Liskov substitution principle basically says “inheritance…it’s a thing.” It seems pretty
obvious to us at this point, but when it was ﬁrst articulated, it was not at all so obvious.

The LSP was such a good idea that, since it was introduced, we have baked it into our
languages. It’s now part of the air we breathe, and we don’t even notice it’s there.

It’s had a huge impact on the way we write software, which, I would guess, is why Martin
chose to include it in SOLID, despite its academic nature. However, while it is fundamental,
it’s not really a great source of practical help day-to-day. Utility is low.

View Slide

I N T E R FA C E
S E G R E G AT I O N
P R I N C I P L E
S O L I D
https://www.flickr.com/photos/[email protected]/8477516123/i
I stands for the interface segregation principle, which says that classes should only have to
depend on the part of an interface they actually need.

It’s a fancy way of saying “don’t let changes to unrelated functionality in a class aﬀect other
things that use it.”

View Slide

W H Y S E G R E G AT E I N T E R FA C E S ?
Musician
AlbumCreator
recordSong
editSong
mixSong
sellMerch
playSetList Gig
Let’s say you have a class Musician that has ﬁve methods on it: recordAlbum, editSong,
mixSong, playSetList, and sellMerch.

It has two classes that consume it: AlbumCreator, and Gig. They use diﬀerent sets of
methods and are not related to each other.

View Slide

Musician
AlbumCreator
recordSong
editSong
mixSong
sellMerch
playSetList Gig
driveVan

Then you add another method - driveVan - that is only used by Gig. You’d expect at this
point that Musician and Gig would have to be recompiled, but it turns out all consumers must
be recompiled. Even AlbumCreator, which didn’t change at all.

With just two consumers - who cares? But what if Musician had hundreds of consumers that
had to be recompiled every time you make any change? You can see how it’s a huge pain. It
makes re-running a test, for one thing, a very long process.

View Slide

StudioActions
AlbumCreator
recordSong
editSong
mixSong
sellMerch
playSetList
Gig
driveVan
VenueActions
Interface segregation says you should break Musician into two diﬀerent classes -
StudioActions and VenueActions. That way, when a new method is added to VenueActions,
AlbumCreator won’t need recompiling.

View Slide

S S I N G L E
P E R C L A S S
M E D
A D D N E W C O D E
L O W
L L I S K O V
T H I N G .
L O W
I I N T E R FA C E
M A K E T H E A P I
S M A L L
H I G H
D
Anyway - it makes more practical sense in compiled languages, so many of us who primarily
use dynamic languages dismiss it as unrelated.

However, it does have a really really useful core idea: if diﬀerent consumers of a class use
non-overlapping sets of methods, that’s a sign that that class has multiple responsibilities
(see S). So I put its utility high, relative to the other principles we’ve looked at here.

View Slide

D E P E N D E N C Y I N V E R S I O N
P R I N C I P L E
S O L I D
https://www.flickr.com/photos/hansmaulwurf/13702053625/
And ﬁnally, D, which stands for the dependency inversion principle. Not dependency
injection, which is one particular implementation of this idea.

Dependency inversion says “depend on abstractions rather than concretions.”

This is a fancy way of saying: if you want to make a new thing, a new instance of a class,
inside another class, think about creating it outside and just passing it in to the constructor,
instead. This has the eﬀect of moving all your choices towards the edges of your system.

View Slide

S S I N G L E
P E R C L A S S
M E D
A D D N E W C O D E
L O W
L L I S K O V
T H I N G .
L O W
I I N T E R FA C E
M A K E T H E A P I
S M A L L
H I G H
D D E P E N D E N C Y
I N V E R S I O N
M O V E C H O I C E S T O
E D G E S O F S Y S T E M
H I G H
There are lots of “dependency injection” frameworks. Angular, .NET, Java. They make it
easier to test classes. Given that most of them have essentially become gigantic global state,
though, it’s sometimes a bit diﬃcult to tie implementations back to the principle. But
dependency inversion does seem to be, theoretically, something a lot of people see. Utility
high.

View Slide

S S I N G L E
P E R C L A S S
M E D
A D D N E W C O D E
L O W
L L I S K O V
T H I N G .
L O W
I I N T E R FA C E
M A K E T H E A P I
S M A L L
H I G H
I N V E R S I O N
H I G H
Now that we’ve ﬁlled it all in, let’s look at this chart for a moment.

SOLID has principles of vastly varying degrees of utility, or concreteness. Utility, or
immediately applicability to code you’re writing today, is one end of a spectrum. The
opposite end is abstraction, which describes a general rule that sounds like a good idea, but
is hard to connect to code you’re looking at in your editor.

View Slide

S S I N G L E
P E R C L A S S
M E D
A D D N E W C O D E
L O W
L L I S K O V
T H I N G .
L O W
I I N T E R FA C E
M A K E T H E A P I
S M A L L
H I G H
I N V E R S I O N
H I G H
O and L are the most abstract, I and D are the most concrete, and S sits in the middle. We’ve
got at least three diﬀerent levels of abstraction here. None of them, even I or D, seems like
it’s actually useful day-to-day for refactoring code. It’s nice to say make the api on an object
small, but … that ship has sailed.

We need things that are more concrete to guide our everyday programming. But it’s not clear
how to ﬁnd them.

View Slide

So the principles are too abstract. The patterns, as we talked about earlier, are more
concrete, but still don’t help us with when. We need something else - our last missing puzzle
piece - to help us actually move our code forward.

Here’s an idea that may be useful.

View Slide

S T R AT E G Y &
TA C T I C S
https://www.flickr.com/photos/teegardin/6150427712/
“Strategy” and “tactics” are military concepts. I didn’t grow up in a military family, so for most
of my life, I thought of these two words as essentially synonymous. But they’re not.

A strategy is a high-level objective that will move us closer to some goal.

A tactic is something you do on the ground to achieve that strategy.

Here’s an example of how these are diﬀerent.

View Slide

\ O /
\ O /
\ O /
G OA L : P R O M O U N TA I N E E R
S T R AT E G Y: C L I M B T H I S M T N
TA C T I C S : T H E R O U T E U P
https://www.flickr.com/photos/frenchy/222016256/
Your goal: be a pro mountaineer. Your strategy: climb this mountain that few people have
climbed before. You’re starting from the bottom (lower left) and need to make it to the
summit (middle top).

There are no trails - you need to ﬁgure out your own path up. The strategy is where you want
to be at the end of the day, and your tactics are how you get there. Tactics includes the
planned route, and contingency plans, and are guided by (and may be changed by) the
strategy as you walk up the mountain.

View Slide

\ O /
\ O /
\ O /
1
2
3
Possible routes include: 1) walking along the treeline and then going up the right-hand ridge.
2) climbing this rockface, sliding along the little shelf there, and then along the left-hand ridge
to the top. 3) just going for it, straight up the face. They all involve diﬀerent tactics - walking
vs. climbing vs. rappelling, etc.

The actual route you take will depend on the weather, your skills, your gear, and many other
things.

View Slide

\ O /
Once you choose a route, it’s still probably not what’s actually going to happen. If you get to
the base of the ridge and discover that an avalanche has made it too perilous to go up that
way, you change tactics, because your strategy of climbing the mountain is no longer in line
with your original tactics. Part of your tactics includes determining when to change tactics.

View Slide

What would happen if all you had was a strategy? All you know is “ok, there’s that mountain,
I need to get to the top of it.” If you set out to achieve this strategy without working out any
of little steps you can take to get there…it’s not likely to work out for you very well. You may
get to the top accidentally, but it’s more likely that you’ll try a few fruitless paths, ﬁnd yourself
in a valley you can’t get out of, and then have to signal to the park rangers to airlift you out.

You need to have tactics in mind, or you probably won’t achieve your strategy.

View Slide

G OA L : C H A N G E A B L E S O F T WA R E
S T R AT E G Y:
TA C T I C S :
O O D E S I G N
S O L I D
https://www.flickr.com/photos/sunfox/5084875405/
Our actual goal is changeable software, rather being a pro mountaineer. Changeable
software is the promise of objects.

One way to think about strategies & tactics for changeable software is that our strategy is
object oriented design. Our tactics would then be things like SOLID & patterns. This is how
object-oriented design is taught, particularly in academia, and it is how most developers look
at it, whether or not they could articulate it.

View Slide

S T R AT E G Y:
TA C T I C S :
O O D E S I G N
S O L I D
There’s a problem, though, with this picture of the world. “Object-oriented design” isn’t
actually a strategy. Remember, a strategy describes what we want our world (in this case our
codebase) to look like at the end of the day.

“Object-oriented design” doesn’t describe that. On the other hand, SOLID is reasonably
good at describing what our codebase should look like when it’s “ﬁnished.” Hmm.

View Slide

S S I N G L E
P E R C L A S S
M E D
A D D N E W C O D E
L O W
L L I S K O V
T H I N G .
L O W
I I N T E R FA C E
M A K E T H E A P I
S M A L L
H I G H
I N V E R S I O N
H I G H
Single responsibility principle, for example, would make a good strategy. It describes a state
of our codebase in which there is one responsibility (at the right granularity!) per class. If we
had that, our codebase would be more changeable.

Open/closed describes this codebase utopia where you never have to edit code to add
features.

In fact all these principles are, at some level, descriptions of when you know your code is
“right.” “If your code were like this, it would be more changeable.”

View Slide

S T R AT E G Y:
TA C T I C S :
S O L I D P R I N C I P L E S
SOLID is a great set of strategies. Our problem is that we’ve been using them like tactics.

For example, you can’t apply single responsibility principle directly to a thousand-line class.
A class like that has a muddy set of abstractions spread across multiple methods each that
are hard to distinguish. When you squint at the class and envision how you’d break it up,
you’ll most likely be wrong. The abstractions are, by deﬁnition, hard to see, because if they
weren’t, you’d have done something about it already.

View Slide

S T R AT E G Y:
TA C T I C S :
Trying to just eyeball a large class and see what the right abstractions are is like trying to
head towards the summit without planning a route ahead of time.

But we do this a lot! I’ve been on many teams where a class got too monstrous, so they’d
take a week oﬀ from doing feature work. They’d spend that week eyeballing the class and
trying to refactor it into the right abstractions. Teams do these a lot. I call this a “stop-the-
world” refactoring.

View Slide

S T R AT E G Y:
TA C T I C S :
What’s wrong with a stop-the-world refactoring? Refactoring is part of being a good software
engineer, right? Taking time to clean up & make code better is important. Right?

View Slide

https://www.flickr.com/photos/jonathancohen/15420956905
Of course it’s important to refactor code. However.

Two interesting things happen when you stop the world to refactor:

1. The product team is unhappy. You’re taking a whole week “oﬀ,” from their perspective,
meaning you’re not working on anything they can see.

2. Because you’re time-limited, you feel pressure at the end of the week to break that class
up somehow, even if you’re not entirely sure yet where the right boundaries are.

#2 is exactly how you end up with one of these.

View Slide

H I G H
L OW
H I G H
L OW
The wrong set
of small objects
❗
❗

View Slide

DevMynd
T H E O N LY WAY TO M A K E A S TO P - T H E - WO R L D
R E FA C TO R I N G WO R K I S TO N OT D O I T .
http://www.imdb.com/title/tt0086567/
The only way to make a stop-the-world refactoring work is to not do it.

It’s like global thermonuclear war. The only winning move is not to play.

When we apply strategies as though they were tactics, we end up with these ham-handed,
mostly unplanned, unpopular changes that, more often than not, leave us in a worse place
than before.

View Slide

When we do one of those stop the world refactorings, we’re doing this. And it’s frustrating.

Ever wonder why good developers who started out in an OO language are turning to
functional programming?

Certainly novelty is part of it, but there’s also a strong undercurrent of fundamental criticism
of OO. They say it just doesn’t work. And that’s because there’s a summit there, and they can
see it, and it seems like they should be able to get to it. But they can’t.

View Slide

What we’re missing is a set of tactics that gets us up there in explicit, small steps. We need
things we can do every day, as we’re doing feature work, to inline the refactoring time and
allow the right objects emerge from the mess over time.

Right now we don’t have very many of tactics. One thing we do have, though, is lots of rules
that tell us what not to do.

View Slide

DevMynd
post.comments.first.author.email
NOPE
For example, we have the Law of Demeter that tells us that `post.comments` is ok, but more
method calls chained on the end of it gets a big ol’ NOPE. When we make long chains of
method calls on diﬀerent objects, we’re introducing coupling we don’t want.

So, ok, don’t do that.

View Slide

DevMynd
We also have code smells, which tell us when something might be wrong with our code.

We have are very few ‘do’s. Most of our rules at this level are ‘don’t’s.

We need ‘do’s. We need a set of tactics. Let’s make one! I’ve made my own acronym. :D

View Slide

S TA B L E
STABLE. This mountain is SOLID, which is cool. But when I’m trying to go up it, what I really
need is stability. I want it to, for example, not be a volcano, not avalanche out from under my
feet, not drop boulders on me, etc. I need it to be solid, sure. But at a more immediate level,
when I’m making my way on the ground, I need stability.

The same is true in my codebase. I want to know that if I make a change in one part of the
code, it won’t cause an avalanche on the other side of the mountain.

View Slide

S TA B L E
So let’s go through these tactics.

I took the six things I wanted to say, and worked pretty hard, actually, to make them into an
acronym. Hey, if it worked for SOLID…

View Slide

S TA B L E
S M E L L Y O U R C O D E
https://www.flickr.com/photos/pedrosimoes7/169983321/
S: smell your code.
Study code smells and the other ‘don’t’s, so that you can start identifying things you could
ﬁx.

Martin Fowler’s Refactoring book is great for this. I’ve worked with teams who would pick
one code smell for a lunch & learn each week, and discuss and look for examples in their
code.

You want to start noticing & naming the problems in the code you look at, even though you
won’t be ﬁxing them all yet.

View Slide

T I N Y P R O B L E M S
F I R S T
S TA B L E
https://www.flickr.com/photos/ian-arlett/13706787684/
T: tiny problems ﬁrst.
In messy code, there will be lots of smells. They’ll overlap and intertwine and interfere with
each other. It will be hard to see what should be made with all this mess.

The best way to get started is to pick a really small problem that you know how to solve in a
very concrete way, and just ﬁx that. For example, rename a variable whose usage has
diverged from its name.

View Slide

S TA B L E
https://www.flickr.com/photos/ian-arlett/13706787684/
T I N Y P R O B L E M S
F I R S T
Pick the smallest problem to ﬁx even though you see enough of the bigger problems to start
guessing their answers. Your goal is to see the large problems better, by clearing away
the small problems obscuring them. The more information you gather about these larger
problems, the more likely your eventual abstractions will be right.

Proper abstractions are worth waiting for. Let them emerge from the code you have by
clearing away the easy cruft.

View Slide

A U G M E N T T E S T S
S TA B L E
https://www.flickr.com/photos/horiavarlan/4273968004/
A: augment your tests.

You will almost certainly have to do this to be able to refactor large classes.

You need integration tests at one level higher than the class you’re working on, and you need
these in place before you start doing any of this. For example, in a server-side MVC
application, if you want to refactor a big controller method, you’ll need view-level integration
tests in place that exercise it. If you want to refactor a big model, you’ll need controller-level
integration tests.

View Slide

https://www.flickr.com/photos/horiavarlan/4273968004/
S TA B L E
A U G M E N T T E S T S
In general: test behavior, not implementation. That’s why you go one level up. You need
tests that describe the behavior you want to keep. This may mean getting rid of some
lower-down unit tests, and/or writing a new set of a tests at a level you haven’t had them
before.

View Slide

S TA B L E
BA C K U P
https://www.flickr.com/photos/mjonasson/19228720295/
B: back up when it’s useful.

When the code has an abstraction in it that is no longer serving you well, sometimes the
most useful thing to do is to ‘rewind’ the code into a more procedural state, put all the
duplication back, and start again. It is much, much easier to move from a procedure to the
right set of objects, than it is to move from the wrong set to the right set.

Don’t get caught by the sunk cost fallacy. Don’t forge ahead with a set of objects that don’t
even ﬁt now, let alone the future.

View Slide

S TA B L E
L E AV E I T
B E T T E R T H A N
Y O U F O U N D I T
https://www.flickr.com/photos/spierisf/6989462184/
L: Leave it better than you found it.
During any one expedition into the code to add a feature or ﬁx a big, you won’t be able to ﬁx
all the problems you see. (Can’t hug every cat! [Hello memes from 2008.]) Sometimes the
only thing you have time to do alongside your stated goal is rename a method so it describes
its behavior better.

View Slide

S TA B L E
L E AV E I T
B E T T E R T H A N
Y O U F O U N D I T
That action seems so small, doesn’t it? Our instinct is to save a bunch of those up and do
them at once. Don’t give into that stop-the-world temptation, though. Fix one thing, the
smallest thing, while you’re working on a story that concerns the code.

I was a girl scout, and one of our rules when we were out camping was that we always left a
camp site in better shape than when we arrived. Over time this made a better experience for
everyone, including ourselves.

View Slide

S TA B L E
L E AV E I T
B E T T E R T H A N
Y O U F O U N D I T
When you change that one method name, you’re removing a little piece of cognitive
dissonance. The next person to come through this code will be able to understand it a little
more easily. Maybe the big abstraction will suddenly be obvious. Or maybe they’ll just ﬁx the
next smallest thing. The key insight is that little things add up over time.

View Slide

E X P E C T
G O O D
R E A S O N S
S TA B L E
https://www.flickr.com/photos/an_untrained_eye/5012331537
E: expect good reasons.
Assume past developers had good reasons to write the code they did. Some code looks so
horrible that we think, “what idiot wrote this? Why would anyone ever do it this way?” And
then you run git blame and ﬁnd out it was you, six months ago. Or it was one of the devs you
really admire.

View Slide

https://www.flickr.com/photos/an_untrained_eye/5012331537
S TA B L E
E X P E C T
G O O D
R E A S O N S
There are forces at work on the code beyond the developer’s experience and technical skill.
Deadlines, relationships with other groups like product, QA, and operations, company
financial situation…all these and more leave their fingerprints on the codebase. Start thinking
about the social pressures that affect your codebase, and many things will make a lot more
sense.

View Slide

S S M E L L Y O U R C O D E
T T I N Y P R O B L E M S F I R S T
A A U G M E N T T E S T S
B B A C K U P
L L E AV E I T B E T T E R
E E X P E C T G O O D R E A S O N S
These are little things you can do to inline-refactor large classes as you’re making progress
on features. You don’t have to stop the world. You can rebuild trust with your product team,
and as a bonus, you’re much more likely to end up with the code you want.

It’s a cycle. Keep ﬁxing the small problems, and the solutions to the large ones will become
obvious.

View Slide

S S M E L L Y O U R C O D E
T T I N Y P R O B L E M S F I R S T
A A U G M E N T T E S T S
B B A C K U P
L L E AV E I T B E T T E R
E E X P E C T G O O D R E A S O N S
You might ask, don’t you still have to stop the world sometimes? After all, once you’ve
cleaned up enough of the small problems so that the solution to the larger problem becomes
obvious, you do have to still actually solve the larger problem.

View Slide

DevMynd
https://twitter.com/kentbeck/status/250733358307500032
Kent Beck has an interesting way of talking about this. “For each desired change, make the
change easy (warning: this may be hard), and then make the easy change.”

When you remove small problems, the big problems become obvious, AND they become
much easier. You amortize the cost spent ﬁxing the big problems and as a result you end up
with higher-quality solution. And when you see it, will look, in retrospect, so completely #@$
%ing obvious.

View Slide

DevMynd
https://twitter.com/kentbeck/status/250733358307500032
Kent’s warning is important to notice, though. “This may be hard.”

The STABLE cycle won’t always prevent you from extracting the wrong objects, or trying a ﬁx
that doesn’t work. You’ll still have go down some paths that lead to dead ends. But in this
process, that’s expected. Back up & try another. That’s why “back up” is one of the essential
steps in this process.

View Slide

But this time, we aren’t wandering aimlessly, like we were back here.

View Slide

\ O /
We’re moving tactically. We’re following steps that we know will get us there. Even if the ﬁnal
shape of the journey doesn’t look like what we thought it would when we started.

View Slide

https://www.flickr.com/photos/bevrichardmartin/5985876061/
https://www.flickr.com/photos/discarnate/27211024/
https://www.flickr.com/photos/lynardie/16191183291/
Work on making your code STABLE, and it will eventually be SOLID. You can get to the top.
You can be the success story. Just make sure you head up with a plan.

View Slide

DevMynd
Sarah Mei
[email protected]
@sarahmei
THANK YOU!
Thank you!

View Slide

Is Your Code Too SOLID? (with transcript)

Is Your Code Too SOLID? (with transcript)

sarahmei

More Decks by sarahmei

Other Decks in Technology

Featured

Transcript