Table-Driven Development

Use table-like datastructures to express your code as data and limit error-prone logic.

November 29, 2022 ยท 5 min read

Have you ever written code that looked like this?

enum Foo {
	first = 'first',
	second = 'second',
	third = 'third'

 * Given some string, determines what kind of "Foo" it is.
function classifyFoo(value: string): Foo {
	if (value === 'foo') {
		return Foo.first
	} else if (value === 'bar') {
		return Foo.second
	} else if (value === 'baz') {
		return Foo.third
	} else {
		throw new Error(`Could not deserialize value '${value}' into Foo')


I certainly have. It's a fairly common pattern to have to serialize and deserialize types like this between module boundaries in your code. Maybe the value that you're deserializing into Foo is coming from an API response, or a database. Either way, you have to validate it and transform it into your enum.

Before talking about tables, note that you could write almost identical code using a switch statement:

function classifyFoo(value: string): Foo {
	switch(value) {
		case 'foo':
			return Foo.first
		case 'bar':
			return Foo.second
		case 'baz':
			return Foo.third
			throw new Error(`Could not deserialize value '${value}' into Foo')

This is a little better, because at least Typescript can help you by statically figuring out whether the switch statement is exhaustive. But either way, the code is quite repetitive. But most importantly, code like this is difficult to change, and easy to get wrong.

It's difficult to change because code like this is hard to abstract. If you add a new value to the Foo enum, you have to add a new branch to your function. Also, in my experience, code like this tends to not just stay in once place either -- it tends to infect the rest of your codebase with other, similar if/switch statements, because code like this is difficult to share. It's easy to start slipping side-effects into the branches of your if-statements.

It's also easy to get wrong -- every if, and every switch case statement, represents a branch in the logic of your program. Every branch is an opportunity to get it wrong. For example, it's harder for static analysis tools like Typescript to know if you've mapped every value correctly, or if you're handling every possible case.

Code as data

What's the solution? I'm going to take a page out of functional programming's book and and talk about code as data. In other words, given that most of the code we write can be expressed as a function, mapping some set of inputs to another set of outputs, we can express that mapping declaratively using, well, a Map.

I'll put that a little more concretely. Let's say you're writing an HTTP-based API. Ultimately (since HTTP is a stateless protocol), you might be able to model your entire application as a pure function: (httpRequest) -> [httpResponse, sideEffects] (where sideEffects might be writes to a database, or external API calls). Of course it's never entirely pure, but this captures the essence of it, in a perfect world. You'll also have stateful driver code needed to run that server on an operating system, connect to databases, etc, but the essence of your program is still a pure function.

(Side note: if you're ever written Haskell, you'll know that this is literally how Haskell models all programs. To make anything "happen" in the outside world you use something called the IO monad -- basically just the sideEffects type above that hooks into the runtime.)

So go go back to our example above, what happens if we model the mapping explicitly as a map?

/* prettier-ignore */
const valueToFooMapping = new Map(
	["foo", Foo.first],
	["bar", Foo.second],
	["baz", Foo.third]

Now look how easy it is to "parse" a given value:

const classifyFoo = (value: string) => valueToFooMapping.get(value)
//     ^? (string) => Foo | null

Want to know if a given value is a valid Foo?

const isValidFoo = (value: string) => valueToFooMapping.has(value)
//      ^? (string) => boolean

Note that as our enum grows, the only logic we have to update is the declarative mapping expressed in valueToFooMapping. And that's what "declarative" really means -- "declaring" state statically rather than through logic.

Note that as well, from a performance perspective, (at the cost of the initial map allocation), we've improved the performance of our code from O(n) to O(1), meaning that we will incur no performance cost by growing the size of our enum.

(Side note: I think Map and Set are really under-used types in modern Javascript. They have tons of useful methods on them, and come with performance benefits, that plain Objects don't have. But more on that later.)

Wrapping Up

Naturally, the example above was fairly trivial. In the real world you probably wouldn't even be writing manual serialization/deserialization code -- you'd be using an ORM or a library like zod to model the relationship between strings and an enum.

Once you start thinking of your programs as functional mappings, I think you'll start seeing this pattern everywhere. Many, many switch statements or if-statments could be better modeled as declarative maps, along with logic that operates on those maps.


While the code above is written in Javascript, my thoughts on code structure like this have been moulded by two other languages in particular: