Build Software from Front-to-Back | Hacker News Reader

Build Software from Front-to-Back

happyvalley.dev

204 pointsstepbeek104 comments

I'm going to disagree with both approaches, and suggest (for lack of a better term) "middle-out".

Always define the API first. Figure out the information necessary, and make sure it meets both front-end constraints (e.g. no information is missing, does it need to be one call or multiple calls, etc.) and back-end constraints (can this be efficient to retrieve from the database, does one server have all the info, etc).

Once you've verified that the API design works for the needs of both ends, then you lock that down and let front-end and back-end teams work independently.

And even if you're coding on your own, it forces you to think about the information architecture first, which is a good habit to get into so you don't paint yourself into a corner in either direction.

Front-first risks building an interface which requires data is which is too complex to retrieve. Back-first risks building the wrong endpoints. API-first requires you to design for both before you start building.

Silicon Valley lives on! iirc there were actual companies started with "middle out compression"

IMO backend constraints are usually less stringent than the frontend part. Mocking the front first avoids a lot of designing round trips I think.

For instance if on the frontend you need to display an infinite list of items, how you get your data can be heavily influenced by your interface. If you plan on having a super fast scroll with the user flying through the items, you might want to do it differently than for a page by page site.

If you design API first you must make this choices upfront, and you paint yourself in a corner if you change opinions when the resulting UX is in your hands and you’re playing with it.

Front (prototype) -> middle -> out

That is usually the best approach. It can still bite you in the ass, though.

Sometimes that approach leads a project into a cemented API and new requirements that arise after real world application can be even harder to implement as a result.

So I guess I’m not arguing, but agreeing while adding that the approach needs a couple qualifiers.

In most cases API comes last, after the data and UI. This is just the state of things unless you intentionally building an api service from scratch. Data stays forever and in many times serves more than one application, UI changes all the time and might connect to more than one data source. API is the decoupling between those two and in most cases dictated by both, not the other way round.

No, the data is always coupled to how it is intended to be processed and useless otherwise. Integration is always a giant headache on projects that don't capture intent clearly with a good API.

The change I'd make here is around "locking down" the API design.

One of the biggest benefit of starting with the API is that both the backend and frontend devs can start playing with that contract, and discovering the nitty-gritty ways where it's less ideal than you'd hoped when you designed it pre-code.

So you get to pressure test it, and iterate on it, from both sides, instead of just from one of them.

> Always define the API first

Impossible. What will the API serve? A list of horses? Wouldn't work if the user needs a mortgage calculator. There is no choice but to define the front-end first. The question is whether it's defined nebulously or with thought - it's rare for thoughtlessness to be the optimal strategy.

For backend engineers who have trouble understanding that the front end is what all the work is in service of, tell them that the frontend us the Tests for their Test Driven Design.

I say this as a backend engineer. The backend genius shines when we figure out how to serve the frontend efficiently (low compute cost) and adapt to rapidly changing frontend requirements without delaying releases.

Ugh, last time I worked on a project that did this the API ended up designed by "an architect" to provide data that the back end didn't have and the front end didn't want. It was an unmitigated disaster.

Outside in drives a much more effective requirements discussion as you work your way down the stack. If the front end asks for data that's "too complex to retrieve" then that's usually obvious from the mock up and it is cheaper to change it at that point before code lower down the stack has been written.

It leads to much cleaner API design and better negotiations about what should go where since the written code of the layer above effectively drives the requirements for the layer below.

I'm not disagreeing with the architect part -- that's what I meant by "Once you've verified that the API design works for the needs of both ends".

An architect working in a vacuum is only going to result in unmitigated disaster in my experience. :)

But I disagree where you say that it's usually obvious from a mock-up that the backend is going to be too complex. In my experience that never occurs to people at all. All too often I've seen designers spend months mocking up fantasy functionality while the backend team is drawing up tables, shards and microservices, only for it to eventually collide in total incompatibility, when the front-end developers say "but the back end doesn't let us do three-quarters of this!" and the back-end developers say "but obviously you can't get the data that way, what ever made you think you could?"

Forcing the API conversation/specification to happen at the start, rather than in the middle, forces extreme clarity for both sides, so that necessary critical compromises are hashed out at the beginning, instead of discovering a horrible incompatible collision midway through.

> designers spend months mocking up fantasy functionality while the backend team is drawing up tables, shards and microservices, only for it to eventually collide in total incompatibility

that's because this methodology is called waterfall, and it has proven to not work, time and time again.

The project should not start with full requirements - it should start with a single requirement/feature (even if that feature by itself doesn't fullfil the purpose of the software). What is the topmost important feature? Do that part first, and have it working end to end. It should take as little time, and done as fast as possible. It should allow the design team to create as simplified a design as possible, and allow the backend to use as simplified a backend as possible. It should allow testing to be done well (good coverage, good unit testing etc).

Then once this is done, the client will judge it, and say what can be improved. Do that one improvement, only, before going back to the client and repeat.

This has been what most successful projects done.

Obviously this is a complex topic but this applies equally well to agile as well as waterfall.

If you're planning your sprint, the point is to figure out the API call first together, before work starts on either front end or back end.

Real-world projects exist on a wide continuum between "maximum agile" and "maximum waterfall", and usually fall somewhere in between. You can't build AWS or Google Search purely out of 2-week sprints with no further advance planning or specification. :P

>Once you've verified that the API design works for the needs of both ends.

Which was easy to do in retrospect or half way through the task, but doing that verification step up front didn't work.

>Figure out the information necessary, and make sure it meets both front-end constraints

Seems to be a glaring contradiction. How would you know if it met front-end constraints if you haven't defined the front-end yet?

My experience is that front-end is king. It defines what the app must do. The API and back-end are the how. Obviously, you need the what before the how.

If you run into a constraint, then you figure out how to work around it, or what can be sacrificed while still having the front-end deliver the what.

Yup! And reference Ivar Jacobson's OOSE: Use Case Driven Approach for just how long of a history this successful approach has had.

Always interesting to read how others work.

I'm a backend dev who does quite a bit of frontend though I deeply dislike the current state of frontend (bring back Webforms)

For me it all starts with the database, always. Code, ux, network is all ephemeral. The schema, the invariants and the data are forever. (this is also why I think microservices are often the wrong approach, you're solving a code problem at the expense of the data)

I've been thinking about the concept of code as pipes for data and the (incorrect) emphasis we place on code. This is why something like MongoDB never clicked for me, code is worthless without the data it operates on and ensuring the quality of that data takes priority over anything.

Of course you need to know roughly what the data will be used for and approaching it database first can result in some nasty surprises if the requirements change, but the rest of the code will rot and be replaced far sooner than the database. Given the churn on frontend the schema in the database will probably see 5 front end frameworks come and go.

Edit: having written this I realised this is also why I don't like or understand letting your ORM handle database migrations. The code is built on top of a dependable database, letting it inform the design of the database is completely the wrong way round, in my opinion.

You would (should?) have a well defined schema with MongoDB. I know some people see this as one of the values of it, but personally it's not why I use it.

If I understand it correctly this was a newer feature, from what I remember when it was first released it was schemaless?

A schema is just a definition and a set of constraints; in a "schemaless" database, you implement the schema in your application.

I agree on the schema being the source of canonical truth. I also agree on ORMs - we use jdbi mainly. But I find it hard to reason about everything up front. There are generally too many unknown unknowns that emerge when the feature is more fully fledged out.

That's also my way.

First design the data. This will tell you how this part of the solution integrates with what everybody else is doing, and will make very obvious some problems that otherwise you may only discover after the system is mature into usage.

Then design the UX and users processes. Programmers get to design only half of those, but both have to be set at the same time.

Then you can do everything else.

And yes, letting an ORM dictate migrations guides people into a completely wrong sequence.

I absolutely agree. This is what makes technologies like graphql so compelling to me. Your data layer shouldn’t mimic the structure the presentation layer, and the presentation layer shouldn’t be tightly coupled to the data layer. And more importantly, data will typically be used by a multitude of apps, all with different purposes. There’s nothing worse than starting a new project that relies on data that was structured to facilitate an old obsolete interface.

the linux command UI (for actions/services) and spreadsheet UI (for data) are the best interfaces that have lasted for over 40 years.

Anything else is ephermal.

History is littered with millions of enterprise software that can't beat the simplicity of a spreadsheet or the flexibility and efficiency of a unix command line

> For me it all starts with the database, always.

I agree, though I generally reduce this question to, "what is the shape of my data?".

I was just thinking something like this as well. The best term for it is 'schema' but that moniker seems so, ill-fitting. For lack of a better term the 'schema' isn't really designed, it's discovered.

Thats how I know I'm on the right path. I start to organize the data and new things that appear fit naturally into what I've already discovered.

This is the epitome of organic design because you are simply the conduit between the truth and a schema definition. If you force yourself to not be clever and just interpret what you've found, your database model will be solid.

What goes in the database? The whole universe? What do you leave out? What do you denormalize and index? These questions are answered by the frontend.

You store the entire universe or whatever reporting requirement demand. You define the database structure based on the requirements of your business logic.

The frontend requirements can help define what api's are required but if you treat your database as dumping tables you limit what your data can do.

You add can add and remove indexes at any point. If you made a bad decision or no decision you would add those when more information is available.

There's no silver bullet I guess but I think the trap that one could fall into here is to think of "the" frontend. There's a bunch of additional consumers of the data model even for a single web-app. Auditing, security, reporting (prior to moving to a separate reporting database), internal tools, possible future mobile or desktop applications, etc. I have found the safest approach is to enforce invariants in the database rather than assume the application code will do the right thing. But as you highlight the schema can be refined by the needs of the front-end, especially where indexing is concerned.

100% agree, though a good ORM handling migrations can be nice as it documents how the schema has changed. Just be sure there is no schema logic that exists only in the ORM and not at the database layer itself.

> Of course you need to know roughly what the data will be used for ...

Can you talk about how you figure this part out? As you imply, this seems like it is your actual first step, not designing the database.

Sure, I guess by first step I was referring to the first thing when I sit down to start coding.

There's all the stuff that comes before actually doing that, generally, though not always, the feature is driven by some front-end requirement and may have accompanying product specification and possibly even UX designs. But I try to take those and think about what the domain concept being addressed is, rather than the shape of the data the front-end requires. Almost always the front-end and requirements will change through iteration so I find that purely mapping the FE concepts directly to the data-structure is less robust than taking a step back and thinking about the actual data without consideration for the proposed front-end design. Though the front-end can still inform aspects of the database at this stage it should only provide minor optimizations to the schema through indexes or normalization choices.

I suppose in part it's taking a domain-driven design approach and making the first step encoding the domain in the database. It has been my experience that many headaches in applications I encounter could have been avoided if the constraints had been enforced against the data at the persistence level rather than assuming the application level code will handle it correctly.

That makes sense. Thanks for the response. It seems like some people in this comment section are coming from your perspective, where the feature has been somewhat defined already, while others are talking about the entire process from the initial idea or problem to working software.

I definitely agree that when possible it is very useful to enforce important constraints in the database.

Linus Torvalds said "Bad programmers worry about the code. Good programmers worry about data structures and their relationships.".

Here's a really interesting discussion about this quote and the idea behind the above: https://softwareengineering.stackexchange.com/questions/1631...

As a backend dev myself, I totally agree with it, but I think when we're developing full blown apps we should have the end user in mind and focus on their experience using our app more than on adopting data-driven UI design.

I generally do like the data-first approach when I have a good idea of what we're building. One place I’ve found it useful to start when you don't have the views planned ahead of time is to mock up the main data management views with handwritten sample JSON data needed to render the functionality desired. Then make the DB schema to provide that data.

If you want to get fancy, you can use Mirage JS [1] to emulate network requests with mock data.

[1] https://miragejs.com/

I tend to agree, and usually go straight for the schema when I start on a project, because the data structure is the model of the real world problem.

With regard to migrations though, I tend to disagree. Code is very easy to manage in version control, so the migration files are merely the data structure represented in code. I love migrations and they've vastly changed the way I work.

You’re both right.

The data model is the thing that stays more invariant in an app, and you can start with that:

https://github.com/Qbix/architecture/wiki/Internet-2.0

But a centralized database is not the future. Client-first web apps are:

https://qbix.com/blog/2020/01/02/the-case-for-building-clien...

So your data will be stored client-side and synced, with Dat or MaidSAFE or IPFS etc.

I would disagree, having been on both sides of this half a dozen times each.

When you write front-to-back, you don't get an immediate sense of what the deeper relationships and nuances of your data models are going to look like. You're designing for what you immediately think you want to see.

This approach can work well, until you run into things that end up being a lot more difficult to implement behind-the-scenes than the data you just expect to appear on the page in front of you.

Personal experience/preference, but the thing that has (almost) never led me wrong was doing a walkthrough of the domain of the application, and then thinking about what the client-side pages and functionality are going to look like (page-by-page, user stories), and then implementing the backend. Finally, wire up the backend to the frontend mockups/design.

For more complex systems, there are things that need to be ironed out in their entirety and have their modeling/relationships, and functionality proven on the API side of things before you decide to start writing UI elements for them.

On the flipside, having worked on projects where there have been major, multi-month setbacks, it was nearly always because the models/domain weren't well thought out and it needed major components to be re-worked (either UI or backend) before we could proceed.

> doing a walkthrough of the domain

Any advice on how to do this without a domain expert to hand?

Somehow the domain has to get into the head of the person doing the modeling. If you're already a domain expert, then it's already there. If you have one next to you, this can happen through conversation. If you don't have an expert with you, you have to load it into your head yourself.

Books, videos, and watching people work are all good. You could also learn to do the thing yourself, if that's possible.

This, pretty much. If you don't have one person with a clear understanding of the backing domain/model of the problem, you're going to be in for a lot of hurt. The person doesn't have to be technical, as long as they understand the business area then you just sit with them and ask them to describe things, while you translate that in your head/on paper to data models.

Almost nothing else about an application matters besides your data models. The UI and other niceties are just a (very replaceable) skin around CRUD-And-CRUD-Accessories on data models. If you screw those up, you have a nice looking, useless theme. Which is pretty ironic given how much disproportionate value non-technical businesspeople place on the UI of things because they can see it/interact with it.

(Not that the UI isn't massively important, but you can still interact with an API minus a frontend. The opposite scenario gives you nice-looking pictures.)

You can also be in a lot of hurt even if you have that person. I've seen a domain expert brought onto teams three times, and they were never of any real help. Those products have either struggled or died btw, so I think it says more about the team than the experts.

If you don't have a domain expert, you should stop everything until you either get one or become one.

> Personal experience/preference, but the thing that has (almost) never led me wrong was doing a walkthrough of the domain of the application, and then thinking about what the client-side pages and functionality are going to look like (page-by-page, user stories), and then implementing the backend. Finally, wire up the backend to the frontend mockups/design.

I'm not totally clear on what you disagree with. it seems like you're suggesting roughly what the article is saying -- figure out the front-end and then implement the backend.

what is the diff between what this article is saying and what you're saying?

Not actually sinking any time into designing and developing a UI before you've walked through it all on a whiteboard, from the perspective of what sort of models and infrastructure are needed to support the featuresets.

Here's an example: Recurring events.

Sounds simple, right? Well, that's what I thought too, until I spent two months learning about what the "rrule" and "rruleset" RFC specs are, and how nightmarishly complex it is to implement a mixture of single and recurring events with granular CRUD and associated records.

You need to allow updating or deleting all recurring events from a master record, or just a single instance of the recurring event, and to be able to attach DB records to specific virtually-generated dates of the recurrence pattern (this one was hell, since databases don't allow foreign-keys on views). Even had to submit a PR for a Postgres library for parsing rrule's to add the proper support that we needed.

In retrospect what should have happened was try to alter the business requirements so that the functionality was slightly different, but you'd never have known that if you go front-to-back.

Having TL'ed both Frontend and Backend at Google, I don't think it's front first or back first. It's "contract first", and here is why:

- Assuming PRD and UX are ready. The Frontend team take a look and come up with the Frontend data model they want. The focus is on making sure it's easiest for them to maintain and develop the client side.

- The Backend team take a look and come up with the Storage data model that is flexible enough for short term future. The Backend should anticipate the growth of the product and try not to be put in a situation where they have to redesign the database/infrastructure.

- Then both teams meet to negotiate the "Contract", which is the API layer. In some case, the API is more similar to the Frontend data model. In some case, the API is more similar to the Storage data model. In other case, there is a translation layer between Storage <-> API <-> Frontend (not as desirable, but not the end of the world). There are standard on how API should be designed (https://aip.dev/).

- When the contract is established, both teams can run more independently to each other, release at different times, and only needs to sync when there is a need for the contract to change. The API is designed to be easily extended, but not changed or deleted. The Backend team doesn't care if the Frontend data model exists. The Frontend team doesn't care what kind of Storage the Backend uses. It's an abstraction.

The complexity of the project can't be entirely eliminated. A good TL makes explainable trade offs on which parts of the system bear the complexity. It's their job to think not only about the architecture, but also how the development can be sustained in the future. This is especially true when the product is developed by a medium-large team. The focus is no longer on having the leanest/optimal code base. The focus is on making sure many parts of the system can move more independently, in parallel, and that it's scale-able to the growing business needs. It's a classic case of Amdahl's Law applicable to real life.

Of course, this is not always applicable to small projects that is never intended to have more than a couple engineers. Even then, when I work on solo full stack projects, I still unconsciously do this contract first approach.

Favorited. Also, I thought "aip.dev" might be a typo but that's also a helpful resource. Thanks for sharing! :)

> Then both teams meet to negotiate the "Contract"

What you describe is pretty much front-end first with the tweak that when the teams negotiate, the burden of proof lies on the back-end. The back-end should contort as much as possible to satisfy the needs of the front-end, allowing it to remain as clean and nimble as possible. Only when it matters should the back-end be able to materially affect the shape of the api. In most cases "mattering" means balancing the needs of this front-end with another that also consumes the back-end.

I always write "front-to-back". I write the code that uses a module, abstraction, api, etc. Then I write that layer until the code works. This goes on layer to layer.

To make it not become a tour-de-force, I start with a golden path, then various aspects (validation, additional operations on data besides rendering, etc). If the data doesn't exist yet, it's mocked. Then later, it's implemented (or made 'live') according to the mocked "schema".

It's not exactly TDD (I rarely write a test except for integration tests or the occasional "let's make sure it's not off-by-one"). It's not top down either, exactly. Perhaps you could call it "needs driven development" or "user driven development". You need it from the start and you use it as soon as possible. From then on, it's just improvements.

If you work back-to-front, you won't have anything working until late in the game. You're constantly imagining all the non-consequential "what-ifs".

But in a way, front-to-back is like TDD except you're not testing via unit tests. You're testing by using. And you will be using it so much that it will be tested thoroughly. You iterate continuously while the top layer / front end keeps working.

Sure, there can be an overarching design. There can be an architecture. There should be. But after that, it's about slowly molding the system towards that design. If you have understood the design, you know when you're veering off course. For sure, it's not like building a bridge.

Pretty good representation of my work flow. I generally save the details (permissions, validations, test coverage) for the end of the process, once the architecture is more solid.

Some projects I spent more thinking on, but especially where specs and design are more vague, I approach it from front to back

I love user-driven design as phrasing. Although I neglected to mention it, I quite often write basic cypress [1] tests early on to get a TDD-like experience.

> For sure, it's not like building a bridge.

It's super interesting how many processes are inherited from traditional engineering.

[1] https://www.cypress.io/

Hm. Maybe. In my experience, tests is just more code, more bugs, more maintenance. If you need to write many tests, you're writing your code wrong. "Just my opinion, man" ;)

You can get something similar with back-to-front. You don't have to spend your time imagining.

With front-to-back, you mock out data. With back-to-front, you mock out interfaces. This is how I write Django projects. I write models, which I can start using right away. Sure it's in the REPL, tests, or admin pages. But I'm using real functionality with real data from the very beginning. Then the custom views and templates get added on top.

+1 :)

"For example, I previously tended to use a bottom-up approach to development. However, SICP showed me the benefits of what it calls "wishful thinking" with a more top-down approach."

https://news.ycombinator.com/item?id=13920125

As a "full-stack" developer who started out on the backend and took on front-end work later in my career, I used to build back-to-front. You generally end up with a cleaner, more scalable, and stable solution. That nobody wants. I've learned this lesson the hard way.

Start with the UX and work your way backwards. I don't like it from an engineering perspective, but it's the only way to go to build products.

Users just do not care what kind of horrible kludge is running behind the slick UI.

Agreed. Unless it is a pet project for no one but yourself, the biggest challenge is figuring out what the problem is and arriving at a solution that works for the user.

Since neither the user nor the programmer knows the right answer, we have to work iterations in. Each iteration is followed by feedback. Given how often we end up being completely wrong, it is best to get to the first feedback as quickly as possible.

Agreed. I found that getting as close as possible to the user minimizes the amount of useless/superfluous code.

Front-end is pretty much as close to the user as you can get.

> it's the only way to go to build products.

This! Back-to-front is a good way to build a scalable, performant, cleanly designed software. Front-to-back is the only viable way to build a usable product.

> Users just do not care what kind of horrible kludge is running behind the slick UI.

For 99.9(9)% of users, the UI is the product. Even those who do know what "back end" means, do not care.

Not trying to be mean, but you really don't make any sort of case for doing this here. You just note you did it because you've become more comfortable with the front end. It also seems like you're designing and implementing an entire system by yourself in which case you can do whatever you want. When dealing with a team, and an API layer that has to be used by more than just your client, I don't see any compelling case presented here to start designing API's specifically for UX use cases.

The techniques are not mutually exclusive, it depends on the context. When you don't have a clear idea of the requirements starting "front to back" helps to understand and gather them while building something that validates them. For your example "back to front" sounds like a better fit.

There is actually a "Design outside-in, develop inside-out" theory that I found illustrated once in an HN comment. It rang so many bells for me that I tried to write it out[1] so that I could understand it better.

[1] https://smalldata.tech/blog/2019/01/16/design-outside-in-dev...

In my experience, the only reliable way to design an API is to cycle through "hats" like gradient descent until the API stops changing. There are no shortcuts! And there are more hats to consider than just frontend and backend. There's security, testability, teachability, performance, upgradability, there are likely many uses for the API, and more. This is why API design is hard.

Just go with an approach that it's your talent stack.

For instance, if your product has a lot of UX nuances, and you aren't artistically inclined, it can make sense to build out the interface first, work out the UX, and then proceed to the backend from there. However, someone with the ability to build wireframes should probably do that first, work on the API, and come back to the frontend.

I'm good at backend stuff, but have a hard time keeping interest in a project I'd I spend all my time in the backend. The frontend keeps me interested because it's visual and helps me see what my goal is.

The other reason to design front end first is that the client mostly cares about that.

Plenty of projects I have worked on will sacrifice anything to have a frontend match a drawing. A friend currently works on a project where finding the purchase button requires you to scroll two inches in a widget where they hid the scroll bar to see the purchase button on a standard 15 inch laptop (as the mockup was built on a wide monitor).

On my current project, if there is so much as a semi-colon out of place, communications will see it. Forget a background process? Nobody notices that.

I'm a back-end dev who's transitioned to being more full stack in the last couple of years. I've written a little bit here on a workflow that I kind of fell into that I've corrected recently and figured it might be useful for other people in the same boat.

Here's my post about this... from 13 years ago :)

http://codingthriller.blogspot.com/2007/12/client-first-deve...

When I worked on full-stack projects, I'd always start by understanding what the frontend needed to display but not necessarily how, which translated well into a database schema and some type definitions.

I would then mock these out so I could start prototyping the rest of the frontend. This usually involved setting up UI components, pages, and linking them up with actions. The goal of the prototype was to demonstrate a few end-to-end (albeit mocked) flows to the user. With the flows and data types in place, it was trivial to design a set of API endpoints and build out the backend.

I agree with this article. There are many developers who think of the database schema first especially in ORM heavy frameworks like rails. Also because of this a lot of people confuse data modeling with the database schema.

I think going in either direction is gonna have flaws. Sometimes frontend informs the backend (rich user flow -> data dependencies) and sometimes backend informs the frontend (often suggesting more composable and maintainable designs)

I've worked on projects that were very front-to-back and without having a constant eye towards the backend, the UI requirements would have ended up dictating a non-composable, non-extensible backend. But I guess applying taste and knowledge to these problems is kind of the point of being "full stack"

The risks of building the frontend first take several forms. There is the eternal problem of the strategy people not understanding that the code can look like it works but not actually work.

And the risk of using mock data to populate a UI (to build it without any backend) is that we don't have good tools for tracking all of the places that we are still using mock data. This can lead to blind spots that make estimating delivery schedules very difficult. Because you may discover late in the process that some corner cases are still using fake data. And, it's a miserable way to work, trying to push through to a milestone when you have no idea how much further you have to go.

There's something to be said for treating it as an iterative process in layers. At first you have no specification, then you have a bad specification, and then increasingly good ones. The final implementation itself comes from having a good spec, and when you have that it should not matter which you start with.

The trouble comes in keeping a clear idea of what an iteration is supposed to test or accomplish beyond "makes it better" - and an end-to-end iteration is expensive. That is where the idea of putting the data model or UI "first" develops, since it lets you build from the technical details towards the concept, as a way of constraining and filtering your thinking.

Something I want to try but have not gotten around to willfully doing, is to treat the initial design stages as an exercise circuit of focusing on each layer for a limited period of time each day, rotating from one to the next.

I'm pretty sure that you could get some great results if a work week were spent doing a four hour cycle, with one hour each thinking and researching data, interfaces, UI, and premise/market.

Not only does this approach help you determine what the backend actually needs to do/acquire, it has the added bonus of getting product teams to iron out critical business logic (which masquerades itself as the frontend) while you transition to backend work.

This is a huge timesaver, because if product decides to change the frontend, you haven't committed huge resources to the backend. Building software front-to-back helps people agree on what needs to get built.

isn't everyone building front to back?

You firstly establish a purpose of your solution. Thinking the job to be done, the users, the features..

Then you do a design. Likely you have a design team, that does research and creates wireframes or high fidelity mock ups.

Then you establish requirements for the various layers in your stack.

So what I described is a fairly typical process. It is front to back.

I can't imagine someone building a product, starting with a myopic focus on the database, followed by rest contracts, etc...

There are plenty of reasonable ways to build web applications. If the process you described works for you, that's great, but others do find different strategies effective too.

For example, your process puts great emphasis on the visual design. To me, that aspect is almost entirely orthogonal to the software design. That's not to say it isn't important to getting a good end result, but once you know what interactions and information architecture you need, how you draw things on a screen doesn't affect anything else much.

I suspect a lot of teams would start with the external models like interactions and information architecture, then move to internal models like database schemas or REST APIs, and then implement the former in terms of the latter.

good point, if you are building software for other systems to consume, the UX portion is not applicable, nearly as much

I think the issue here is that there's a sole developer working on the whole app with the difficult choice of choosing where to start. I think that creating a design that covers most test cases of the app would then let you start from either section of the app. I am surprised OP doesn't mention anything around GraphQL (why or why not it could help).

> creating a design that covers most test cases of the app

I consider this be a very hard thing to accomplish. There are generally too many unknown unknowns. I almost always need exploratory work to figure things out.

I think a highly effective strategy is an outward-in somewhat recursive iteration from high-level details towards a polished, robust solution. Of course, the first step must be some sort of sketch, however minimal or vague, of the user-facing functionality -- "user" can mean a number of things here, depending on the application -- or else you have no idea what you are doing.

Something like:

1. High-level, low fidelity sketch of the user stories and the UI

2. High-level, low fidelity sketch of a possible database schema

3. Refinement of UI and user stories

4. Mid-level sketch of possible API

5. Refinement of DB schema and backend models

6. First pass implementation the UI

7. First pass implementation of the backend (db + models + API)

... A few more iterations, bug testing, and voila! Of course, minor variations of this could also work well. For example, 6 and 7 could probably be easily switched.

Build software through "meeting in the middle". Define the front (user interface), define the back (data structures), and then progress towards the middle.

After all an interface is, by definition, where two things meet and interact. There are too many unknowns otherwise.

I have a mindset to develop the back-end first and then go for the front-end, and I usually do in that fashion. Theoretically it reasons as right. However, I always find that when developing the front end, I inevitably have to add functionality to the back-end.

Recently I started learning ASP.NET Core Razor Pages and found it quite refreshing that the line between front-end and back-end is very much blurred and somehow, the cognitive load is much lesser, than compared to, say, and Angular + API stack.

I felt the same for some of the projects I developed using Django, though, Razor Pages is even more merged when it comes to front-end and back-end.

It's what I call customer experience design. You can build this in terms of user stories, UI mocks, OpenAPI spec etc depending on your customer. This makes the expectations from the API interface very clear. Of course, it may also mean that I'd have to deviate from pure REST but that's easy when you see the customer value. Then the tradeoff between fast, easy and cheap is restricted to components that don't impact the end user and can be changed later. The last thing I'd want is to change my customer's workflow because my entity relationships change.

How foreign the problem space is for me, and how focused much of the audience on HN seems to be on web/database software.

I'm involved with the two biggest types of software in general computing: control systems and large complex commercial transactional systems.

The former don't feature a UI or a database. While the latter have the primary issue of modeling a complex problem domain.

That complex model is by necessity produced without regard to any particular human or system interface, or data persistence. Are such concepts so alien to audiences here?

That’s where https://miragejs.com/ helps. I’ve built few fully functional prototype apps with full UI/UX without a single line of backend code and with front-end acceptance tests.

If you’re prototyping greenfield product, it’ll morph many times as you build it. Once you’re happy where it is, and you’ve stabilized on data structure (not database schemas), then just start replacing mocks withr your API calls. Acceptance tests will tell you if you’ve done it right.

I would be careful: if you're designing a REST API to be consumed by other developers and applications there are conventions and patterns you should stick to.

If your product or service doesn't exist without the UI then why bother with a REST API at all? Write a nice stateful application that is rendered server side. There are great frameworks for this in almost every language.

A good REST API is consumed by applications and developers and they expect you to stick to the conventions or they will turn to another provider if they can.

In REST, the API is the front-end. You can still do the front-to-back approach, mocking the data etc until you get the interface right. Then you work on how the application delivers data to the interface, which is the backend.

If you are designing a REST interface then I recommend a domain driven design approach. I've had a fair bit of success with that.

I also like to think in terms of denotational semantics which works rather well with REST APIs. The entities represent the domain objects which model what the system does. The state transfer operations become the game between the client and the system. If the domain maps cleanly the client and the server never have to guess or assume the state of the other. You can follow the operations from the URLs (HATEOS, etc).

What I find happens to some systems where the design is driven by the UI are domain models that span both the client and the server. This leads to routes that fill data for specific UIs, entities that have different representations based on which route they're fetched from, and the dreaded "RPC over HTTP," that the OP seems aware of.

A lot of this can be avoided if you never intend to expose your REST API to external developers. Just don't have one. Less to worry about.

Designing front-to-back that way makes a lot of sense. I just find that if you do that from a UI through a REST API that a lot of teams and developers skip on maintaining the REST conventions and then end up sad when their project becomes difficult to maintain and onboard new developers to.

I like building pretty skeletons of a product first, which helps to dream up natural interfaces uninfluenced by the structure of a "backend". I've seen a lot of people conforming their frontend to some predetermined backend structure completely ruining the end user experience.

Also found there to be a motivational aspect to this. Since I can't push the buttons or turn the knobs because its just UI at this point, I can't help but breathe life into it so that I can actually use it.

That’s what is usually called “top-down programming”, right?

Casey Muratori once made a similar point in https://caseymuratori.com/blog_0025.

Personally I think the approach is very similar to TDD and so for some of us it's easier to dive first on the front-end. It's like translating user specifications to tests and then writing the code for the tests to pass.

I think one should start with whatever extension in the API between front and back is needed. That is the point to make the compromise between the two. On the one hand one wants to make exactly the data that the front end needs available but on the other hand one wants something that makes sense to request to the data. Once one has that compromise front and back end can be developed separately.

Okay, but this is one of those "I've discovered I can work like this" sort of posts that doesn't take into account the vast range of projects and project teams.

So, sure: It's useful to be aware that you can work front-to-back, back-to-front, front-and-back-to-middle, etc. But you still can't make this choice without consideration and one size absolutely does not fit all.

How do you build your service layer first but your APIs last? Aren't APIs part of the service layer? The interesting thing about DynamoDB single-table design that I'm really starting to like is it forces you to start with API calls. I literally start with an excel spreadsheet of API declarations and corresponding HASH/SORT keys.

Everybody is sharing how they go about their app design. This is the order that works for me:

1. Data Models 2. Data Stores 3. Business Logic 4. Processes 6. Application Interfaces (resource level) 7. Presentation Interfaces 8. UI

I like to build software "middle-out" from the interfaces.

Totally agree with this. At yazz.com we take exactly the Visual Basic approach too of building software from front to back and it works for simple things

I think a better approach is back-front-back, or front-front-back; or front-front-back and then side-to-side.

I would figure you simply break it down into three components. Front end (presenters) middle (plugin's) and back end (managers). The managers know nothing of the front end and the presenters know nothing of the managers. That way you can always swap out your UI for a different one, right?

If this is the case then you should develop the plugins first.

Oh man, Stephen, you're gonna get a lot of conflicting views on this one, posting it here. :)

For what it's worth I am on your side given a bunch of constraints that match my prior experience. So I have typically worked on small scrappy IT teams at companies that are working on something else -- whether maintaining a Roku channel or putting together the heating ducts and plumbing assemblies for a building or making sure your marketing companies are not making illegal promises to customers that you can't fulfill. Inside those teams there is some sort of pain that we are meant to alleviate -- say, executives are spending too much time telling accounting in slipshod fashion their estimates for how much money they anticipate will be coming in from various prospective contracts, and roughly when it will come. The idea is born: an app which accounting can grab information from, automatic emails to the executives, and a user interface that fits the executives like a glove so that this is a better-than-painless experience for the people who actually use it.

Given this context, I agree that you want to repeatedly iterate on the frontend of the product over and over until the actual users start to change the nature of their complaints. Their complaints started with: "I need to put in a Flotsam which is also a Jetsam, how do I do that?" / "What do you mean, I thought flotsam and jetsam were different things?" / "Well for established Wakes they are, but not when we are looking at a new Surf. Then sometimes they are different but sometimes something is both, until that Surf becomes a Wake." So it is a failure of your domain model to match theirs.

And you are right, being able to have that domain model in a couple of JSON structures really helps with your ability to refactor everything around, especially if you have a type system which can just tell you "look that function is still designed around the last iteration and it's gonna break now with this new structure."

Those problems are really hard to fix when that data structure has already been broken apart into tables to be stored in a relational database and then ossified into various Data Access Objects and API calls which perform the updates.

By contrast with this approach you have a time where the product has succeeded in matching the user's domain model, which comes when they say something like "hey I changed this in this other system but I am not seeing the change in your app" or maybe just "hey I ran into a bug where it looks like the software is no longer saving my changes." Something that reveals that they think this software is in beta rather than pre-alpha development. You have a conversation like, "It was never saving your changes, that's a forthcoming feature." / "Uh, how was this ever supposed to work if it didn't save my changes?" / "No, like, that has been part of the design from day one, but that turns out to be a really costly part of the development effort so we wanted to get you to sign off that this is exactly the app you want before we start to build that layer of persistence." / "Oh. Well where can I sign up? I really want this app!"

Also really good for the idea of "build one to throw away", once you have fixed up your domain model then it can be nice to start from a clean slate.

Let me also say where you are limited: sometimes you do have a reasonably good guess at the domain model. For example you might be doing anthropological work as a developer, sitting in on meetings and getting a sense for how people talk about a system, before building the app. Or, you are interfacing with an external API and its domain model is presented to you directly in its documentation. Or, you are designing a game engine and the decisions are up to you -- the "users" are people who will have to play the game later.

Here it is helpful to build back-to-front. In fact there is a really nice REST principle which you may wish to emulate if you can, called HATEOAS. If you can do it, it makes things so much simpler. The basic idea about HATEOAS is the exact inversion of what you are saying: a polymorphic frontend, rather than a frontend which knows what API calls to make and in what sequence. So the idea is to have an intentionally crappy frontend -- it is crappy because it is generic, the backend tells it "here are the many different sorts of objects tracked by the system, and here are the things you can do with them," and it configures up a crappy UI based on this skeleton which the backend gives it. UIs created procedurally by robots reading data structure descriptions will never be as pretty and fits-your-hands-exactly as ones you create yourself. And the key technology which enables this front-end polymorphism is precisely linking: a web browser is able to show all web sites and is agnostic about how exactly everything connects because the web server tells it how everything connects. So if you have a survey app, when you get a survey from the backend the backend also tells you something about "to submit a new response to this survey, POST it to this URL, and validate the contents against this schema first." The crappy UI probably shows you the 10 questions for the survey up above, and then down by the "submit new response" form it contains 10 answer fields and you have to scroll between the top and the bottom for each question. Very inconvenient, because it is generic.

But on the flip-side, you usually get a good-enough-for-developers-for-now UI on the frontend, and now you can modify the domain model and services purely on the backend.

My white whale is probably to combine both of these together someday. :)

Hey thanks for the in-depth feedback/discussion! I've definitely fallen prey to the anti-pattern you lay out here. And it's super hard to not fall in to a kind of sunk-cost fallacy where you begin to limp along until eventually giving in and - as you mention - throw it out to build with a better understanding of the domain.

> nice REST principle which you may wish to emulate if you can, called HATEOAS. If you can do it, it makes things so much simpler. The basic idea about HATEOAS is the exact inversion of what you are saying: a polymorphic frontend

Huh. I'd never really thought of HATEOAS in this way. I've used it before to build an API that can be consumed by another service in a flexible way, but have never really reached for it when building a UI. I guess this would solve the problem by only guaranteeing relationships rather than guaranteeing the full API?

This would definitely protect against churn when the structure of the URL's change, but doesn't this still depend on having a solid understanding of the domain from the get-go?

Look at it a different way: why is our domain model hard to change?

Is it, I suspect, mostly because we failed DRY and repeated ourselves at the various layers? (i.e. our domain model is echoed in our DB, Redis cache, API structure, App structure, stylesheets...)

If that's the core problem, it's solvable two ways... an app with no backend, or a front-end that is fully generic serving up a backend that calls the domain model shots.

all software is build for users, and users interact with the front end. it makes sense to define the requirements with the front end and iterate until its ideal before starting any backend.

I don't think front-to-back or back-to-front are correct. From my experience, it's always from what I've seen outside-in

This means understanding the problem domain. What does the app solve? Better yet, how does the app either (1) save money/resources for the problem, or (2) generate revenue streams?

When you start from this approach, things become much more clear. Generally speaking, start with the UX low fidelity wireframes first. What are the user-stories for the user? Can they log in? Can they do some CRUD functionality relative to the problem domain?

Okay, what data does this user need for these pages? What sort of user-activity are they going under? Create a set of datatables describing the problem domain.

It needs a user table? check. It needs a license table? Just map out all the data needed, and group them into appropiate tables.

Fromo there, map out the relationships in a relational format to get a better prospective on the bigger feature

Are these features even needed according to the frontend? Okay, go from there. What is the cost to implement each feature, and how does this impact the development velocity / budget of the project? Go and find the sweet point of what's defined as a MVP, and then proceed to figure out what a stage 2 looks like.

Does the original data model have a migrationary upgrade path? Imagine if your developing the backend. Do you forsee problems running the migrations?

Now you need to think about scalability and whether that actually matters here. Changes are it doesn't for the vast majority of apps.

Do you need subscribers to aggregate bulkInsertions to the database? Do you need a redis cache to prevent unnecessary calls to database? Or do you need something more complex, because the end user is a developer and your providing a high scalable Web API service?

Just keep cycling outside-> in until you've satisfied all the results into a proper MVP database and a MVP UX pen paper design.

At this point, you'll want to define the API and how the frontend will consume it. How will the backend handle it? For instance, if you spec it graphql, prepare for a world of pain on the backend and an easy life on the frontend.

You should think about your API design, and use design patterns to think about how you can keep the frontend as simple as possible. The state of truth should of an application should live closest to its data source(s), so tread with this path in mind. Sometimes the frontend does the same work (e.g. financial calculations) to reduce the total number of calls to the backend. You might want to consider everything else here at this point, e.g. whether websockets are needed etc. And other factors in the application such as third party providers.

There's many right solutions to a problem domain, but there are just as many wrong solutions as well. Go from the business side first, and go outside-in. The best answer is the simplest one that satisfies all criteria, both in UX and how scalable it needs to be

I've got a way of doing it, where the server is basically just consisting of 4 types of endpoints:

- CRUD on table records, which makes the data schema independent

- Actions which can update multiple tables, call 3rd party etc

- Queries which can go more complex things than GET or GET list, such a search, or filtering, or sorting

- Selections, which are gets or queries run over multiple tables and combining the results

I'm addition each endpoint returns in JSON, but can have a

/with/:view

suffix attached to template that into HTML

I find this organizes well and covers all use cases

If anyone wants to see a Node template of this, it's

https://github.com/cris691/servedata

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