Implementation visibility – Part I

Somewhere in my take on programming, there lingers the concept of “implementation visibility”, that I’m not quite sure to be able to express clearly, but I’ll try.

Let’s say you are writing an academic text like a bachelor thesis and your professor makes it clear that she regards the list of literature a very important part of your work. What are you going to do? Concentrate on your cool topic and treat the literature as a secondary task? Or will you shift your focus and emphasize your extensive literature research, highlighting promising cross-references in your text? You’ll probably adjust your resources to make your list of literature more prominent, more visible. You respond to the priorities of your stakeholders.

Now imagine that your customer wants you to program a web application, but has one big requirement: All actions of the users need to be reassured with a confirmation question (as in “do you really want to delete this?”). He makes it clear that this is a mandatory feature that needs to be implemented with utmost care and precision. What would you do? We responded by adjusting our system’s architecture to incorporate the requirement into the API. You can read about our approach in this blog post from 2015. The gist of it is that every possible client of the system will be immediately aware of the requirement and has a much easier time conforming to it. It is harder to ignore or forget the requirement than to adhere to it because the architecture pushes you into the right direction.

The implementation of the customer’s requirement in the example above is very visible. You’ll take one look at the API and know about it. It isn’t hidden into well-meaning but out-dated developer documentation or implicitly stated because every existing action has a confirmation step and you should be sentient enough to know that this means your new one needs one, too. The implementation visibility of the customer’s requirement is maximized with our approach.

Stages of visibility

I have identified some typical stages (or levels) of implementation visibility that I want to present in this blog post series. That doesn’t mean that there won’t or can’t be others. I’m not even sure if the level system is as one-dimensional as I’m claiming here. I invite you to think about the concept, make your own observations and evolve from there. This is a starting point, not an absolute truth.

The following stages typically appear in my projects:

  • level 0: Inline
    • level 0+: Inline with comment
    • level 0++: Inline with apologetic comment
  • level 1: separate method
  • level 2: separate class
    • level 2+: new type in domain model
  • level 3: separate aggregate
  • level 4: separate package or module
  • level 5: separate application or service

In my day-to-day work, the levels 1 to 3 are the most relevant, but that’s probably not universally applicable. Our example above with the requirement-centered API isn’t even located on this list. I suggest it’s at level 6 and called separate concept or something similar.

An example to explain the visibility levels

Let’s assume a customer wants us to program a generic webshop. We are not very versed in commerce or e-commerce things and just start implementing requirements one after one.

After the first few iterations with demonstrated and usable artifacts, our customer calls us and explains that all prices in the webshop are netto prices and that there need to be some kind of brutto price calculation. You, being accustomed to prices that don’t change once you put products into your shopping cart, ask a few questions and can finally grasp the concept of value added taxes. Now you want to implement it into the webshop.

The first approach to the whole complex is to show the brutto prices right besides the netto prices when the user views his shopping cart. You can then validate the results with your customer and discuss problems or misconceptions that are now visible and therefore tangible.

The original code of your shopping cart renderer might look like this:

public class ShowShoppingCart {
  public ShoppingCartRenderModel render(Iterable<Product> inCart) {
    final ShoppingCartRenderModel result = new ShoppingCartRenderModel();
    for (Product each : inCart) {
      return result;

A quick explanation of the code: The class ShowShoppingCart takes some products and converts them into a ShoppingCartRenderModel that contains the shopping cart data in a presentable form so the GUI just needs to take the render model and paste it into some kind of template. For each product, there is one line with a description and the (already renamed) netto price on the page.

Visibility level 0: It’s just code anyway

Let’s start with the lowest and most straight-forward implementation visibility level: The inline implementation.

public class ShowShoppingCart {
  public ShoppingCartRenderModel render(Iterable<Product> inCart) {
    final ShoppingCartRenderModel result = new ShoppingCartRenderModel();
    for (Product each : inCart) {
      final Euro bruttoPrice = each.nettoPrice().multiplyWith(1.19D);
    return result;

The new code is in lines 5 and 9. As you can see, the programmer chose to implement exactly what he understood from the discussion about netto and brutto prices with the customer. A brutto price is a netto price with value added tax. The VAT rate is 19 percent at the time of writing, so a multiplication with 1.19 is a valid implementation.

Our problem with this approach isn’t the usage of floating point numbers in the calculations or that calculations even exist in a method that should do nothing more than render some products, but that the visibility of the requirement is minimal. If you, I or somebody else doesn’t know exactly where this code hides, we will have a hard time finding it once the VAT is changed or anything else should be done with brutto prices or VATs.

Technically, the customer’s requirement is implemented and the brutto prices will show up. But because the concept of taxes (or VAT) is important for the customer, we likely made the code too invisible to be maintainable.

Visibility level 0+: Hey, I even wrote a comment

To make some part of the code stick out of the mess, we have the tool of inline code comments. Let’s apply them to our example and raise our visibility level from 0 to 0+:

public class ShowShoppingCart {
  public ShoppingCartRenderModel render(Iterable<Product> inCart) {
    final ShoppingCartRenderModel result = new ShoppingCartRenderModel();
    for (Product each : inCart) {
      // AN-17: calculating the brutto price from the netto price
      final Euro bruttoPrice = each.nettoPrice().multiplyWith(1.19D);
    return result;

The new code is in lines 5, 6 and 10. You can see that the programmer chose the same approach as before, but realized that the code would be buried if not marked. Given that the requirement identifier is “AN-17”, the code can be found by a text search of this number. And if you happen to stumble upon this part of the application, you can deduct meaning about what you see from the comment.

Except that you cannot really be sure what the AN-17 code really is. Is the result.addProductLine() part of AN-17 or not? Would you expect the calculation of taxes and prices in a method called render() in a class named ShowShoppingCart? Is this implementation really correct? Aren’t there different tax rates for different products? Did the original author think about that? Is the customer content with this functionality?

Note that you cannot really test the brutto price calculation. You have to invent some products, render them and then scrape the brutto prices from the render model. That’s tedious at best and a clear sign that the implementation visibility is still too low. On to the next level

Visibility level 0++: This sucks, but I’ve got to go now

This level tries to make you a partner in crime by explicitly stating what’s obviously wrong with the code at hand. Now it’s your responsibility to fix it. You wouldn’t leave a broken window be, would you?

public class ShowShoppingCart {
  public ShoppingCartRenderModel render(Iterable<Product> inCart) {
  final ShoppingCartRenderModel result = new ShoppingCartRenderModel();
  for (Product each : inCart) {
    // AN-17: calculating the brutto price from the netto price
    // TODO: take different tax factors into account
    final Euro bruttoPrice = each.nettoPrice().multiplyWith(1.19D);
  return result;

The new code is in lines 5, 6, 7 and 11. The new comment line 6 is typical for this visibility level: The original programmer knew that his implementation isn’t adequate but couldn’t be bothered with improving it. Perhaps he had external circumstances force him to do it. Whatever it was, this code is the equivalent to a soiled public toilet. The difference is, this time we can determine who made the mess.

The apologetic “I know I made a mess” comment often begins with TODO or FIXME. This isn’t directed towards the original author, it’s pointed at you, the person that happens to read the comment. Now, what are you going to do? Pretend you didn’t read the comment? Leave the toilet soiled? Clean up the mess of your predecessor? You probably have work to do, too. And doesn’t it work the way it is? Never change a running system!

We will see how you can improve the implementation visibility of the requirement in the next blog post of this series. Stay tuned!

How do I start a project

On my quest to build better software for people and their needs I try to move my current agile project approach to a more user centered and outcome oriented one.

This starts right at the beginning of a project. After getting the go from the client I start with meeting the project leads on the client side, the ones who will make decisions and control the way of the project.
I like to take an assumption driven process or learning focussed one to ask questions and clear my assumptions on my way.
The first questions I have are:

  • who will use the software
  • who will be affected by the software/project
  • what are their goals/expected outcomes, what if they could choose only one
  • what do they expect from the software
  • what will happen if the project stalls or even fails

The people using the software aka the users are one of the main focus during the project but also the people who get benefits from the software without directly using it are really important and should not be neglected. These can be the people responsible for operating the software or managers getting reports from actual users. I keep them in mind so that other parts which are often missed during a user centered approach are considered.
All these people have some expectations how the software will affect them, some even have goals or need something to come out of the project. These outcomes cover a great range: from measureable business goals like increasing revenue or retention rate, to personal benefits like visibility. It is important to get a rough priority, I use a narrowing question like ‘what if you could choose only one’.
Besides from goals and outcomes people have also imaginations how the software will be used by them, in which context and how often.
These are the positive effects of the project and the software but all is not sunshine, so I also look at what will happen if the project is delayed, stops or even *shudder* fails. These are the risks that I need to consider and may be even plan for.
All these questions help me frame the project from the end. I know what goals to aim for and in which direction the journey goes.
This is my first step to build a shared understanding among the project participants. The steps to learn about what picture they have in mind. My questions and their answers help me to clarify the direction. After that I need to plan the first phase. For this I have to clear my mind and start with a beginner’s mind to find my hidden assumptions. Every assumption I or other have need to be called out explicitly. I have to capture it and formulate a corresponding learning step.

But this is a topic for another post…

The definition of done

From large to small, from projects to issues, a team needs to define when they are considered done.
This decision differs from team to team, some have steps to done, others just one state. Even the words used in your issue tracker reflect your choices: what does ‘fixed’ mean, what is ‘closed’ used for…
Even some practices like test driven development define a state of done: the code is done if all tests are green and it is refactored.

What’s your definition of done?

Let’s take a look at some examples:

  • tests are green and code is refactored
  • QA says ok
  • customer/stakeholder/product owner accepts the issue
  • developer thinks the code reflects the description in the issue
  • a predefined spec, maybe even with an acceptance test, is fulfilled
  • no bugs were found while clicking through
  • the code is merged with the master branch
  • the continuous integration tool has found no errors

The problem with this ‘definition of done’s is that either they look for an external person to accept by their opinion/guideline or concentrate on some output. But the people needing the software do not want the software in its own regard. They want to reach a goal through the software. The software is a mean to an end: their goals. Without defining the goals and needs beforehand you are either doomed to guess them and are at the mercy of arbitariness (from your point of view) or concentrate on some measurable output like code, tests or a completed feature.

Defining what the user wants to do with this new feature or project should be the first thing in a project right after the initial introductions. Who will use the app or the feature? (the intended audience, the users) What do they expect from it? (the benefits) What goal do they want to reach?
With this questions and answers you have a target. After completing the issues or project you can see if the target has been reached, if the goals are met. It might be the same with an acceptance process from a stakeholder but here you know the target beforehand not after.

About API astonishments

Nowadays we developers tend to stand on the shoulders of giants: We put powerful building-blocks from different libraries together to build something worth man-years in hours. Or we fill-in the missing pieces in a framework infrastructure to create a complete application in just a few days.

While it is great to have such tools in the form of application programmer interfaces (API) at your disposal it is hard to build high quality APIs. There are many examples for widely used APIs, good and bad. What does “bad API” mean? It depends on your view point:

Bad API for the API user

For the application programmer a bad API means things like:

  • Simple tasks/use cases are complicated
  • Complex tasks are impossible or require patching
  • Easy to misuse producing bugs

A very simple real life example of such an API is a C++ camera API I had to use in a project. Our users were able to change the area of interest (AOI) of the picture to produce images consisting of only a part of full resolution images. Our application did crash or not work as expected without obvious reasons. It took many hours of debugging to spot the subtle API misuse that could be verified be reading the documentation:

The value of camera.Width.GetMax() changed instead of being constant! The reason is that AOI was meant and not the sensor resolution width. The full resolution width we actually wanted is obtained by calling camera.WidthMax.GetValue(). This kind of naming makes the properties almost undistinguishable and communicates nothing of the implications. Terms like AOI or sensor width or full resolution just do not appear in this part of the API.

Small things like the example above may really hurt productivity and user experience of an API.

Bad API for the API programmer

API programmers can easily produce APIs that are bad for themselves because they take away too much freedom away resulting in:

  • Frequent breaking changes
  • API rewrites
  • Unimplementable features
  • Confusing, not fitting interfaces

Design your interfaces small and focused. Use types in the interface that leave as much freedom as possible without hurting usability (see Iterable vs. Collection vs. List vs. ArrayList for example). Try to build composable and extendable types because adding types or methods is less of a problem than changing them.


Developers should put extra care in interfaces they want to publish for others to use. Once the API is out there breaking it means angry users. Be aware that good API design is hard and necessary for a painless evolution of an API. Consider reading books like “Practical API Design” or “Build APIs You Won’t Hate” if you want to target a wider audience.

Evolvability of Code: Uniform Access Principle

Most programmers like freedom. So there are many means of hiding implementations in modern programming languages, e.g. interfaces in Java, header files in C/C++ and visibility modifiers like private and protected in most object-oriented languages. Even your ordinary functions or public class interface gives you the freedom to change the implementation without needing to touch the clients. Evolvability in this sense means you can change and refine your implementations without requiring others, namely clients of your code, to change.

Changing the class interface or function signatures within a project is often possible and feasible, at least if you have access to all client code and use powerful refactoring tools. If you published your code as a library or do not want to break all client code or forcing them to adapt to your changes you have to consider your interface code to be fixed. This takes away some of your precious freedom. So you have to design your interfaces carefully with evolability in mind.

Some programming languages implement the uniform access principle (UAP) that eases evolvability in that it allows you to migrate from public attributes to properties/method calls without changing the clients: Read and write access to the attribute uses the same syntax as invoking corresponding methods. For clarification an example in Python where you may start with a class like:

class Person(object):
  def __init__(self, name, age): = name
    self.age = age

Using the above class is trivial as follows

>>> pete = Person("pete", 32)
>>> print pete.age
# a year has passed
>>> pete.age = 33
>>> print pete.age

Now if the age is not a plain value anymore but needs checking, like always being greater zero or is calculated based on some calendar you can turn it to a property like so:

class Person(object):
  def __init__(self, name, age): = name
    self._age = age

  def age(self):
    return self._age

  def age(self, new_age):
    if new_age < 0:
      raise ValueError("Age under 0 is not possible")
    self._age = new_age

Now the nice thing is: The above client code still works without changes!

Scala uses a similar and quite concise mechanism for implementing the UAP wheres .NET provides some special syntax for properties but still migration from public fields easily possible.

So in languages supporting the UAP you can start really simple with public attributes holding the plain value without worrying about some potential future. If you later need more sophisticated stuff like caching, computation of the value, validation or even remote retrieval you can add it using language features without touching or bothering clients.

Unfortunately some powerful and widespread languages like Java and C++ lack support for UAP. Changing a public field to a more complex property means the introduction of getter and setter methods and changing all clients. Therefore you see, especially in Java, many data classes littered with trivial getter and setter pairs doing nothing interesting and introducing unnecessary bloat to maintain the evolvability of the code.

Why I’m not using C++ unnamed namespaces anymore

Well okay, actually I’m still using them, but I thought the absolute would make for a better headline. But I do not use them nearly as much as I used to. Almost exactly a year ago, I even described them as an integral part of my unit design. Nowadays, most units I write do not have an unnamed namespace at all.

What’s so great about unnamed namespaces?

Back when I still used them, my code would usually evolve gradually through a few different “stages of visibility”. The first of these stages was the unnamed-namespace. Later stages would either be a free-function or a private/public member-function.

Lets say I identify a bit of code that I could reuse. I refactor it into a separate function. Since that bit of code is only used in that compile unit, it makes sense to put this function into an unnamed namespace that is only visible in the implementation of that unit.

Okay great, now we have reusability within this one compile unit, and we didn’t even have to recompile any of the units clients. Also, we can just “Hack away” on this code. It’s very local and exists solely to provide for our implementation needs. We can cobble it together without worrying that anyone else might ever have to use it.

This all feels pretty great at first. You are writing smaller functions and classes after all.

Whole class hierarchies are defined this way. Invisible to all but yourself. Protected and sheltered from the ugly world of external clients.

What’s so bad about unnamed namespaces?

However, there are two sides to this coin. Over time, one of two things usually happens:

1. The code is never needed again outside of the unit. Forgotten by all but the compiler, it exists happily in its seclusion.
2. The code is needed elsewhere.

Guess which one happens more often. The code is needed elsewhere. After all, that is usually the reason we refactored it into a function in the first place. Its reusability. When this is the case, one of these scenarios usually happes:

1. People forgot about it, and solve the problem again.
2. People never learned about it, and solve the problem again.
3. People know about it, and copy-and-paste the code to solve their problem.
4. People know about it and make the function more widely available to call it directly.

Except for the last, that’s a pretty grim outlook. The first two cases are usually the result of the bad discoverability. If you haven’t worked with that code extensively, it is pretty certain that you do not even know that is exists.

The third is often a consequence of the fact that this function was not initially written for reuse. This can mean that it cannot be called from the outside because it cannot be accessed. But often, there’s some small dependency to the exact place where it’s defined. People came to this function because they want to solve another problem, not to figure out how to make this function visible to them. Call it lazyness or pragmatism, but they now have a case for just copying it. It happens and shouldn’t be incentivised.

A Bug? In my code?

Now imagine you don’t care much about such noble long term code quality concerns as code duplication. After all, deduplication just increases coupling, right?

But you do care about satisfied customers, possibly because your job depends on it. One of your customers provides you with a crash dump and the stacktrace clearly points to your hidden and protected function. Since you’re a good developer, you decide to reproduce the crash in a unit test.

Only that does not work. The function is not accessible to your test. You first need to refactor the code to actually make it testable. That’s a terrible situation to be in.

What to do instead.

There’s really only two choices. Either make it a public function of your unit immediatly, or move it to another unit.

For functional units, its usually not a problem to just make them public. At least as long as the function does not access any global data.

For class units, there is a decision to make, but it is simple. Will using preserve all class invariants? If so, you can move it or make it a public function. But if not, you absolutely should move it to another unit. Often, this actually helps with deciding for what to create a new class!

Note that private and protected functions suffer many of the same drawbacks as functions in unnamed-namespaces. Sometimes, either of these options is a valid shortcut. But if you can, please, avoid them.

4 questions you need to ask yourself constantly while programming

Most of today’s general purpose progamming languagues come with plethora of features. Often there are different levels of abstractions and intended use cases. Some features are primarily for library designers, others ease implementation of domain specific languages and application developers use mostly another feature set.

Some language communities are discussing “language profiles / levels” to ban certain potentionally harmful constructs. The typical audience like application programmers does not need them but removing them from the language would limit its usefulness in other cases. Examples are Scala levels (a bit dated), the Google C++ Style Guide or Profiles in the C++ Core Guidelines.

In the wild

When reading other peoples code I often see novice code dealing with low-level threading. Or they go over board with templates, reflection or meta programming.

I have even seen custom ClassLoaders in Java written by normal application programmers. People are using threads when workers, tasks, actors or other more high-level abstractions would fit much better.

Especially novices seem to be unable to recognize their limits and to stay off of inappropriate and potentially dangerous features.

How do you decide what is appropriate in your situation?

Well, that is a difficult question. If you find the task at hand seems hard you should probably take a step back because:

There are two hard things in computer science: cache invalidation, naming things, and off-by-one errors.

-Jeff Atwood

Then ask yourself some simple questions:

  1. Someone must have done it before. Have I searched thoroughly for hints or solutions?
  2. Is there a (better) library, data structure or abstraction?
  3. Do I really have to do this? There must be a better/easier way!
  4. What do I gain using feature/library/tool X and what are its costs? What about the alternatives?


You need some experience to recognize that you are on the wrong path, solving problems you would not even have if doing the right thing in the first place.

Experience is what you got by not having it when you needed it.

-Author Unknown

Try to know and admit your limits – there is nothing wrong with struggling to get things working but it helps to frequently check your direction by taking a step back and reflecting.