Minimizing Code Complexity by Programming Declaratively

Writing good code is something all programmers aspire to, but the definition of what actually makes good code can be a bit tricky to pin down. The idea of good code varies from person to person, from language to language, and also varies between problem domains. Web services, embedded devices and game programming are few software domains that all have very different needs and so also have very different software development styles, methods and best practices.

I truly believe that we are in the stone ages of software development (ok, maybe the bronze age?), and that 100 years from now, people will be doing things radically differently than we do today because they (or we) will have figured out better best practices, and the languages of the day will usher people towards increased success with decreased effort.

This post is on something called declarative programming. The idea is nothing new, as prolog from 1972 is a declarative language, but the idea of declarative programming is something I don’t think is talked about enough in the context of code quality.

By the end of this read, I hope you will agree that programming declaratively by default is a good best practice that pertains to all languages and problem domains. If not, leave a comment and let me know why!

Declarative vs Imperative Programming

Declarative programming is when you write code that says what to do. Imperative programming is when you write code that says how to do it.

Below is some C++ code written imperatively. How long does it take you to figure out what the code is doing?

	int values[4] = { 8, 23, 2, 4 };
	int sum = 0;
	for (int i = 0; i < 4; ++i)
		sum += values[i];
	int temp = values[0];
	for (int i = 0; i < 3; ++i)
		values[i] = values[i + 1];
	values[3] = temp;

Hopefully it didn’t take you very long to understand the code, but you had to read it line by line and reason about what each piece was doing. It may not be difficult, but it wasn’t trivial.

Here is the same code with some comments, which helps it be understandable more quickly, assuming the comments haven’t become out of date (:

	// Declare array
	int values[4] = { 8, 23, 2, 4 };

	// Calculate sum
	int sum = 0;
	for (int i = 0; i < 4; ++i)
		sum += values[i];

	// Rotate array items one slot left.
	int temp = values[0];
	for (int i = 0; i < 3; ++i)
		values[i] = values[i + 1];
	values[3] = temp;

Here is some declarative code that does the same thing:

	int values[4] = { 8, 23, 2, 4 };
	int sum = SumArray(values);
	RotateArrayIndices(values, -1);

The code is a lot quicker and easier to understand. In fact the comments aren’t even needed anymore because the code is basically what the comments were.

Comments are often declarative, saying what to do right next to the imperative code that says how to do it. If your code is also declarative though, there is no need for the declarative comments because they are redundant! In fact, if you decide to start trying to write code more declaratively, one way to do so is if you ever find yourself writing a declarative comment to explain what some code is doing, wrap it in a new function, or see if there is an existing function you ought to be using instead.

As a quick tangent, you can use the newer C++ features to make code more declarative, like the below. You arguably should be doing that when possible, if your code base uses STL, a custom STL implementation, or an in house STL type replacement, but I want to stress that this is a completely separate topic than whether or not we should be using new C++ features. Some folks not used to STL will find the below hard to read compared to the last example, which takes away from the main point. So, if you aren’t a fan of STL due to it’s readability (I agree!), or it’s performance characteristics (I also agree!), don’t worry about it. For people on the other side of the fence, you can take this as a pro STL argument though, as it does make code more declarative, if the readability and perf things aren’t impacting you.

	std::array<int,4> values = { 8, 23, 2, 4 };
	int sum = std::accumulate(values.begin(), values.end(), 0);
	std::rotate(values.begin(), values.begin() + 1, values.end());

We Already Live in a Semi-Declarative World

When reading the tip about using (declarative) comments as a hint for when to break some functionality out into another function, you may be thinking to yourself: “Wait, isn’t that just the rule about keeping functions small, like to a few lines per function?”

Yeah, that is true. There is overlap between that rule and writing declarative code. IMO declarative code is a more general version of that rule. That rule is part of making code declarative, and gives some of the benefits, but isn’t the whole story.

The concept of D.R.Y. “Don’t Repeat Yourself” also ends up causing your code to become more declarative. When you are repeating yourself, it’s often because you are either duplicating code, or because there is boiler plate code that must be added in multiple places to make something work. By applying D.R.Y. and making a single authoritative source of your information or work, you end up taking imperative details out of the code, thus making what remains more declarative. For more information on that check out this post of mine: Macro Lists For The Win


If your particular engineering culture uses TDD (test driven development), you may also say “Hey, this isn’t actually anything special, this is also what you get when you use TDD.”

Yes, that is also true. Test driven development forces you to write code such that each individual unit of work is broken up into it’s own contained, commonly stateless, function or object.

It’s suggested that the biggest value of TDD comes not from the actual testing, but from how TDD forces you to organize your code into small logical units of work, that are isolatable from the rest of the code.

In other words, TDD forces you to make smaller functions that do exactly what they say by their name and nothing else. Sound familiar? Yep, that is declarative programming.

Compilers, Optimizers and Interpreters

The whole goal of compilers, optimizers and interpreters is to make it so you the coder can be more declarative and less imperative.

Compilers make it so you don’t have to write assembly (assembly being just about as imperative as you can get!). You can instead write higher level concepts about what you want done – like loop over an array and sum up the values – instead of having to write the assembly (or machine code!) to load values into memory or registers, do work, and write them back out to memory or registers.

Similarly, the whole goal of optimizers are to take code where you describe what you want to happen, and find a way to do the equivalent functionality in a faster way. In other words, you give the WHAT and it figures out the HOW. That is declarative programming.

Interestingly, switch statements are declarative as well. You tell the compiler what items to test for at run time but leave it up to the compiler to figure out how to test for them. It turns out that switch statements can decide at compile time whether they want to use binary searching, if/else if statements, or other tricks to try and make an efficient lookup for the values you’ve provided.

Surprised to hear that? Give this a read: Something You May Not Know About the Switch Statement in C/C++

Similarly, profile guided optimization (PGO) is a way for the optimizer to know how your code actually behaves at runtime, to get a better idea at what machine code it ought to generate to be more optimal. Again, it’s taking your more declarative high level instructions, and creating imperative low level instructions that actually handle the HOW of doing what your code wants to do in a better way.


If you’ve spent any time using C#, I’ll bet you’ve come to the same conclusion I have: If it takes you more than one line of code to do a single logical unit of work (read a file into a string, sort a list, etc), then you are probably doing it wrong, and there is probably some built in functionality already there to do it for you.

When used “correctly”, C# really tends to be declarative.

C++ Advancements Towards Being Declarative

In the old days of C, there were no constructors or destructors. This meant that you had to code carefully and initialize, deinitialize things at just the right time.

These were imperative details that if you got wrong, would cause bugs and make a bad day for you and the users of your software.

C++ improved on this problem by adding constructors and destructors. You could now put these imperative details off in another section and then not worry about it in the bulk of the code. C++ made C code more declarative by letting you focus more on the WHAT to do, and less on HOW to do it, in every line of code.

In more recent years, we’ve seen C++ get a lot of upgrades, many of which make C++ more declarative. In other words, common things are now getting language and/or STL library support.

For one, there are many operations built in which people used to do by hand that are now built in – such as std::sort or std::qsort. You no longer have to write out a sorting algorithm imperatively, you just use std::sort and move on.

Another really good example of C++ getting more declarative is lambdas. Lambdas look fancy and new, but they are really just a syntactic shortcut to doing something we could do all along. When you make a lambda, the compiler makes a class for you that overloads the parentheses operator, has storage for your captures and captures those captures. A struct that looks like this is called a functor and has existed for a long time before lambdas ever entered C++. The only difference is that if you want to use a functor now, you don’t have to go through a bunch of nitty gritty imperative details for making your functor class. Now, you just defined a lambda and move on.

Domain Specific Languages

Domain specific languages – aka DSLs – exist to let people write code meant for specific purposes. Some examples of DSLs are:

  • HTML – what we use to make static webpages
  • XSLT – a language to transform XML data into other data
  • SQL – a language to query information from databases
  • Regex – a language to search text

Believe it or not, DSL is a synonym of declarative programming languages.

HTML for instance completely cuts out things like loops, memory allocation and image loading, and lets you just specify how a web page should look. HTML is declarative because you deal only with the issues in the problem space, not with the imperative details of how to make it all happen.

It’s similar for the others in the list, and other DSLs not on the list. They all try to remove complexity you don’t care about to try and distill a language that deals only with the things in the problem space.

Our Job As Programmers

As programmers, it’s only one part of our job to make “good code” that is easy to read and easy to maintain, but many non programmers would laugh to hear that we spend so much time thinking about that.

The other part of our job is the end result of what our program does. This is what non programmers focus more heavily on of course, and is ultimately what makes software successful or not – at least in the short term. Software needs to do good stuff well to be successful, but if you don’t make good code, you are going to sink your business in bugs, inflexibility, maintenance costs, etc.

Programmers mainly either write code for use by other programmers (such as libraries and APIs), or they make software for use by other people.

In both cases, the job is really that we are trying to hide away imperative details (implementation complexity) and give our customers a domain specific language to do what they want to do in the easiest and best way possible. It’s very important in both cases that the users of your API or the users of your software don’t have to deal with things outside the problem space. They want to work declaratively, saying only what to do, and have our software handle the imperative details of how to do it. They paid for the software so they didn’t have to deal with those details.

As an example, when you work in an excel spreadsheet and it does an average of a row of columns, it doesn’t make you decide whether it should use SIMD instructions to do the math or scalar instructions. You don’t really care, and it almost certainly doesn’t matter enough to anyone using excel which to do, so excel just does whatever it does internally to give you what you asked for.

It can be a challenge knowing what needs to be hidden away when making an API or software for users, but that comes from understanding what it is that your customers actually need and what they are trying to do, which is already a super important step.

The good news is that you don’t have to perfectly match the customers needs to improve their lives. Any imperative details that you can remove is a win. I’m not talking about taking away abilities that people want and should have, I’m talking about removing “chores”, especially ones that if done wrong can cause problems – like nulling out a pointer after deleting it, or initializing all members of a class when creating an object, or the details of loading an image into memory.

None of this should really be that surprising to anyone, but hopefully thinking of these things in a declarative vs imperative way formalizes and generalizes some ideas.

Why Wouldn’t You Program Declaratively?

Purely declarative programming means that you only describe the things you care about and nothing else. If this is true, why wouldn’t you ALWAYS program declaratively? In fact, why do imperative languages even exist? Why would you ever want to waste time dealing with what you by definition did not care about?

Well, for one, it’s impossible to nail down what it is exactly that people do and do not care about, especially in something like a programming language which is likely to be used for lots of different purposes by lots of different people. It’s been real eye opening seeing the diverse needs of the C++ community in recent years for instance. As a C++ game programmer, surrounded by primarily C++ game programmers, I thought I knew what the language needed, but there are lots of things I never considered because I don’t have a need for, unlike some other C++ programmers out there.

Another big point is that declarative languages by definition are a sort of black box. You tell it what to do but not how. It has to figure out the details of how to do it in a good way. The problem is that the compiler (or similar process) has limited abilities to make these choices, and also has limited information about the problem space.

For instance, a declarative language may let you work with a set and say “put item X into the set” and “does item Y exist in this set?”. You can imagine it could perhaps use a hash table, where each hash bucket was a linked list of values. This way, when you queried if the item Y was in the set, it could hash it, then do comparisons against whatever items were in that bucket.

That implementation is fairly reasonable for many programs.

What if instead, you want to keep a set of unique visitors to a popular website, like say That set is going to use a ton of memory and/or be very slow because it’s going to be HUGE.

In that case, someone is likely to go with a probabilistic algorithm perhaps (maybe a bloom filter), where it’s ok that the answer isn’t exactly right, because the memory usage and computation time drops off significantly going probabilistic, and actually makes the feature possible.

The declarative language is likely not going to be smart enough to figure out that it should use a probabilistic algorithm, and nobody ever told it that it could.

Sure, you could add probabilistic set support to the declarative language, and people could specifically ask for it when they need it (they care about it, so it should be part of the DSL), but we could make this argument about many other things. The point is just that without super smart AI and lots more information (and freedom to make decisions independently of humans), a declarative language is going to be pretty limited in how well it can do in all situations.

Because of this, it’s important for the programmer to be able to profile processing time and other resource usage, and be able to “go imperative” where needed to address any problems that come up.

This is similar to how when writing C++, when we REALLY NEED TO, we can write some inline assembly. The C++ is the more declarative language, that allows you to write more imperative assembly when you need to.

It’s important to note that I’m not saying that declarative programming is inherently slower than imperative programming though. Declarative languages can actually be much faster and more efficient with resources believe it or not. In the example at the beginning of the post where i used std::rotate to replace a loop that moved items in an array, it’s possible that std::rotate uses a memmove to move the bulk of the items, instead of an item by item copy like what I coded. That would be a much better solution, especially for large array sizes.

So, declarative programming isn’t necessarily slower than imperative programming, but, for the times it isn’t doing well enough, we need a way to turn off “auto pilot” mode and give imperative instructions for how to do something better.

In more human terms: If you asked someone to go get the mail, you likely will say “can you get my mail? here’s the key and it’s in box 62.”. You wouldn’t tell the person how to walk to the door, open it, walk out, close it, etc. However, if there were special instructions such as “please check the package locker too”, you would give those details.

Basically, you give only the details that are needed, as simply as possible, but reserve the right to give as fine grained details as needed, when they are needed.

So, i propose this:

  • We as programmers ought to be programming declaratively by default, only resorting to imperative programming when we need to.
  • Our job is to empower our customers to work declaratively by making them good DSLs (aka interfaces), but we should remember that it might be important to let them also go more imperative when needed.

Thanks for reading, and let me know your thoughts!


Here are some interesting links about managing code complexity and writing high quality code:
Youtube: Simplicity Matters (36 minutes)
Functions Should Be Short And Sweet, But Why?
Bitsquid: Managing Coupling
Thoughts on Declarative and Imperative Languages
Declarative vs. Imperative Programming for the Web