Tag: Optional

Your null parameter is hostile

I hope we all agree that emitting null values is a hostile move. If you are not convinced, please ask the inventor of the null pointer, Sir Tony Hoare. Or just listen to him giving you an elaborate answer to your question:

https://www.infoq.com/presentations/Null-References-The-Billion-Dollar-Mistake-Tony-Hoare/

So, every time you pass a null value across your code’s boundary, you essentially outsource a problem to somebody else. And even worse, you multiply the problem, because every client of yours needs to deal with it.

But what about the entries to your functionality? The parameters of your methods? If somebody passes null into your code, it’s clearly their fault, right?

Let’s look at an example of pdfbox, a java library that deals with the PDF file format. If you want to merge two or more PDF documents together, you might write code like this:

File left = new File("C:/temp/document1.pdf");
File right = new File("C:/temp/document2.pdf");

PDFMergerUtility merger = new PDFMergerUtility();
merger.setDestinationFileName("C:/temp/combined.pdf");

merger.addSource(left);
merger.addSource(right);

merger.mergeDocuments(null);

If you copy this code verbatim, please be aware that proper exception and resource handling is missing here. But that’s not the point of this blog entry. Instead, I want you to look at the last line, especially the parameter. It is a null pointer and it was my decision to pass it here. Or was it really?

If you look at the Javadoc of the method, you’ll notice that it expects a StreamCacheCreateFunction type, or “a function to create an instance of a stream cache”. If you don’t want to be specific, they tell you that “in case of null unrestricted main memory is used”.

Well, in our example code above, we don’t have the necessity to be specific about a stream cache. We could implement our own UnrestrictedMainMemoryStreamCacheCreator, but it would just add cognitive load on the next reader and don’t provide any benefit. So, we decide to use the convenience value of null and don’t overthink the situation.

But that’s the same as emitting null from your code over a boundary, just in the other direction. We use null as a way to communicate a standard behaviour here. And that’s deeply flawed, because null is not standard and it is not convenient.

Offering an interface that encourages clients to use null for convience or abbreviation purposes should be considered just as hostile as returning null in case of errors or “non-results”.

How could this situation be defused by the API author? Two simple solutions come to mind:

  1. There could be a parameter-less method that internally delegates to the parameterized one, using the convenient null value. This way, my client code stays clear from null values and states its intent without magic numbers, whereas the implementation is free to work with null internally. Working with null is not that big of a problem, as long as it doesn’t pass a boundary. The internal workings of a code entity is of nobody’s concern as long as it isn’t visible from the outside.
  2. Or we could define the parameter as optional. I mean in the sense of Optional<StreamCacheCreateFunction>. It replaces null with Optional.empty(), which is still a bit weird (why would I pass an empty box to a code entity?), but communicates the situation better than before.

Of course, the library could also offer a variety of useful standard implementations for that interface, but that would essentially be the same solution as the self-written implementation, minus the coding effort.

In summary, every occurrence of a null pointer should be treated as toxic. If you handle toxic material inside your code entity without spilling it, that’s on you. If somebody spills toxic material as a result of a method call, that’s an hostile act.

But inviting your clients to use toxic material for convenience should be considered as an hostile attitude, too. It normalizes harmful behaviour and leads to a careless usage of the most dangerous pointer value in existence.

Optional polymorphism by delegation

A code design pattern I’ve used a lot in recent times is the “optional-based polymorphism” that looks like a delegation to another type that might not be available. It might be an implementation of the FCoI-principle (Favour Composition over Inheritance).

Let’s look at an example: An application has several different engines that move stuff around. Some engines are based on limit switches. They move until they are stopped by a physical switch. The application can make these engines move from one predefined position to the next, but not anywhere in between. Another type of engines is based on a relative position. You give the engine the new target position and it positions itself there, without any limit switches or predefined positions.

Traditional approach

A typical implementation using inheritance would be a common supertype “Engine” that provides the functionality both engine types exhibit. From there, we would define two subtypes that extend the functionality in their desired way. One subtype would be the “LimitSwitchEngine”, the other one the “PositionableEngine”.

Our client code that wants to use a particular engine has two possibilities: It only requires the common functionality of an engine and can work with the supertype. Or it needs to perform a downcast after checking the actual type of the engine.

Cast methods

The optional-based polymorphism guides the client code towards the specific subtype by providing all possibilities in the common interface:

public interface Engine {

	/* Common functionality */
	
	boolean isMoving();
	
	void emergencyStop();
	
	/* optional-based polymorphism */
	
	Optional<LimitSwitchEngine> boundToLimitSwitches();
	
	Optional<PositionableEngine> freelyPositionable();
}

The client code uses the Engine’s interface only as a stepping stone for the specific engine that is required for your use case. If the engine object cannot provide that functionality, you’ll get an empty Optional. Else you retrieve your reference to the specific type and work with it.

Disadvantages

One disadvantage of this approach is the fact that the supertype is aware and even dependent on the different subtypes. You limit the scope of your type hierarchy to the types offered in the “entrance interface”. You can still use the traditional downcast way as described in the introduction for all other types, but that separates them into “featured” and “non-featured” subtypes. So this approach will violate the Open/Closed principle by not being open to extension without modification.

Another disadvantage is that your typical navigation in the IDE doesn’t work as well anymore. If you want to know about all the different types of engines in the system, you can’t just look at the type hierarchy of the Engine type anymore. This is because of the first advantage this pattern brings:

Advantages

Not only gets this style rid of the downcast, it frees your type system up in two different dimensions: The LimitSwitchEngine and PositionableEngine don’t need to be subtypes of Engine. They can be totally independent types with no real connection to the Engine. And they can be different instances. Of course, there is no need to use any of these freedoms. You can still inherit PositionableEngine from Engine and implement both types in the same object. But it isn’t mandatory anymore.

Another advantage is discoverability. Your typical type hierarchy lookup in the IDE is replaced with code completion lookup. If you get the names right, this pattern feels like writing code on rails, because your code completion proposals will lead you to the correct place.

Your opinion

What is your opinion on this pattern? What would you expect from a code design that provides those “casting” methods? Tell us in the comments!

The Optional Wildcast

This blog post presents a particular programming technique that I happen to use more often in recent months. It doesn’t state that this technique is superior or more feasible than others. It’s just a story about a different solution to an old programming problem.

Let’s program a class hierarchy for animals, in particular for mammals and birds. You probably know where this leads up to, but let’s start with a common solution.

Both mammals and birds behave like animals, so they are subclasses of it. Birds have the additional behaviour of laying eggs for reproduction. We indicate this feature by implementing the Egglaying interface.

Mammals feed their offsprings by giving them milk. There are two mammals in our system, a cow and the platypus. The cow behaves like the typical mammal and gives a lot of milk. The platypus also feeds their young with milk, but only after they hatched from their egg. Yes, the platypus is a rare exception in that it is both a mammal and egglaying. We indicate this odd fact by implementing the Egglaying interface, too.

If our code wants to access the additional methods of the Egglaying interface, it has to check if the given object implements it and then upcasts it. I call this type of cast “wildcast” because they seem to appear out of nowhere when reading the code and seemingly don’t lead up or down the typical type hierarchy. Why would a mammal lay eggs?

One of my approaches that I happen to use more often recently is to indicate the existence of real wildcast with a Optional return type. In theory, you can wildcast from anywhere to anyplace you want. But only some of these jumps have a purpose in the domain. And an explicit casting method is a good way to highlight this purpose:

public abstract class Mammal {
	public Optional<Egglaying> asEgglaying() {
		return Optional.empty();
	}
}

The “asEgglaying()” method might return an Egglaying object, or it might not. As you can see, on default, it returns only an empty Optional. This means that no cow, horse, cat or dog has to think about laying eggs, they just aren’t into it by default.

public class Platypus extends Mammal implements Egglaying {
	@Override
	public Optional<Egglaying> asEgglaying() {
		return Optional.of(this);
	}
}

The platypus is another story. It is the exception to the rule and knows it. The code “Optional.of(this)” is typical for this coding technique.

A client that iterates over a collection of mammals can now incorporate the special case with more grace:

for (Mammal each : List.of(mammals())) {
	each.lactate();
	each.asEgglaying().ifPresent(Egglaying::breed);
}

Compare this code with a more classic approach using a wildcast:

for (Mammal each : List.of(mammals())) {
	each.lactate();
	if (each instanceof Egglaying) {
		((Egglaying) each).breed();
	}
}

My biggest grief with the classic approach is that the instanceof is necessary for the functionality, but not guided by the domain model. It comes as a surprise and has no connection to the Mammal type. In the Optional wildcast version, you can look up the callers of “asEgglaying()” and see all the special code that is written for the small number of mammals that lay eggs. In the classic approach, you need to search for conditional upcasts or separate between code for birds and special mammal code when looking up the callers.

In my real-world projects, this “optional wildcast” style facilitates domain discovery by code completion and seems to lead me to more segregated type systems. These impressions are personal and probably biased, so I would like to hear from your experiences or at least opinions in the comments.

Java’s OptionalInt et al. versus Optional<T>

In Java 8 the Optional type was introduced to avoid the (ab)use of nullable types and null to indicate the absence of a value. It allows the programmer to clearly indicate whether the potential absence of a value is intentional or accidental.

Such option types, sometimes also called Maybe types, have been established in other programming languages, mostly in statically typed functional programming languages like ML and derivatives, but are also emerging in more mainstream languages like Swift.

Java’s Optional type is, to put it mildly, not the most sophisticated implementation of this concept, mostly due to limitations of Java’s existing type system. The Optional type is nullable itself, it’s not a sum type, so it has to rely on runtime exceptions to signal invalid access of a non-existent value, but it’s still useful. Static analysers, usually built into IDEs, can do what the compiler doesn’t and warn if the value is accessed without checking for its presence first.

The Optional type suffers from another limitation of Java’s type system: the fact that primitive types like int, long, double etc. and reference types, derived from Object, aren’t unified in a single type hierarchy. Related to that, primitive types can’t be used as generic type parameters in Java. The language works around this with additional boxed types like Integer, Long and Double for each primitive type.

When the stream API and the Optional type were introduced in Java 8, those primitive types were once again treated with special types: there’s not just Stream<T>, but also IntStream, LongStream, DoubleStream, there’s not just Optional<T>, but also OptionalInt, OptionalLong, OptionalDouble, the same for consumers, suppliers, predicates and functions.

This was done to avoid boxing and unboxing, but also makes it unpleasant to use. What’s worse is that the Optional variants for the primitive types don’t offer the same functionality as Optional<T>: they are lacking the filter, map and flatMap methods as well as the ofNullable factory method. All in all they are less useful than the real Optional, and there’s no convenient way to convert back and forth between, for example, an OptionalInt and Optional<Integer>.

The above mentioned annoyances are the reason why we prefer the generic variant over the special ones for the primitive types by default. Hopefully a future Java release will mitigate this dichotomy between those types, at least by adding the missing methods, but we are not aware of any plans for this yet.

Recap of the Schneide Dev Brunch 2016-12-11

If you couldn’t attend the Schneide Dev Brunch at 11th of December 2016, here is a summary of the main topics.

brunch64-borderedLast week at sunday, we held another Schneide Dev Brunch, a regular brunch on the second sunday of every other (even) month, only that all attendees want to talk about software development and various other topics. This brunch was so well-attended that we had to cramp around our conference table and gather all chairs on the floor. As usual, the main theme was that if you bring a software-related topic along with your food, everyone has something to share. Because we were so many, we established a topic list and an agenda for the event. As usual, a lot of topics and chatter were exchanged. This recapitulation tries to highlight the main topics of the brunch, but cannot reiterate everything that was spoken. If you were there, you probably find this list inconclusive:

Finland

We started with a report of one of our attendees who had studied in Finland for the last two years. He visited the Aalto university and shared a lot of cultural details about Finland and the Finnish people with us.

The two most important aspects of the report were sauna and singing. The Finnish love to visit a sauna, in fact, nearly every building has a functioning sauna. Every office building has a company sauna that will get visited often. So it might happen that your first visit of a company starts right in the sauna, naked with the bosses.

And the Finnish love singing so much that they usually start singing during the sauna session. There are open social events organized around singing together.

Alcohol plays a big role in Finland, mostly because the taxes makes it incredibly expensive to obtain a proper buzz. In the southern regions, much alcohol is imported from Russia or Estonia by ferry. There are even special ferry routes designed to be cost-neutral when shopping for alcohol. But alcohol isn’t the only thing that is made expensive with special taxes. Sugar and sugary food/drinks are heavily taxed, too. So it’s actually more expensive to eat unhealthy, which sounds like a good concept to counter some civilizational diseases.

The Finnish students often wear a special boilersuit during official events that identifies their affilition with their field of study and university. They apply patches and stickers to their suit when they have completed certain tasks or chores. It’s actually a lot like a military uniform with rank and campaign insignia. Only that the Finnish student boilersuit may not be cleaned or washed other than jumping into a body of water with you in it. And the Finnish lakes are frozen most of the year, with temperatures of -27 °C being nothing extraordinary.

As you probably have guessed right now, costs for rent and electricity are high. Our attendee enjoyed his time there, but is also glad to have the singing separated from the alcohol for the most part.

Lambdas and Concurrency

The next question revolved around the correlation between lambda expressions and concurrent execution of source code. The Vert.x framework relies heavily on lambdas and provides reactive programming patterns for Java. As such, it is event driven and non blocking. That makes it hard to debug or to reason about the backstory if an effect occurs in production. The traditional tools like stacktraces don’t tell the story anymore.

We took a deep dive into the concepts behind Optionals, Promises and Futures (but forgot to talk about the Expected type in C++). There is a lot of foggy implementation details in the different programming languages around these concepts and it doesn’t help that the Java Optional tries to be more than the C++ Optional, but doesn’t muster up the courage to be a full Monad. Whether deprecating the get()-method will make things better is open for discussion.

To give a short answer to a long discussion: Lambdas facilitate concurrent programming, but don’t require or imply it.

React.js and Tests

It was only a small step from the reactive framework Vert.x to the React.js framework in Javascript. One attendee reported his experiences with using different types of tests with the React framework. He also described the origin of the framework, mentioning the concept of Flux and Redux along the way.

Sorry if I’m being vague, but each written sentence about Javascript frameworks seem to have a halflife time of about six weeks. My take on the Javascript world is to lean back, grab some popcorn and watch the carnival from the terrace, because while we’re stuck with it forever, it is tragically unfortunate. Even presumed simple things like writing a correct parser for JSON end in nightmares.

It should be noted, though, that the vue.js framework entered the “assess” stage of the Thoughtworks Techradar, while AngularJS (or just Angular, as it should be called now) is in the “hold” stage.

Code Analysis

We also talked about source code analysis tools and plugins for the IDE. The gist of it seems to be that the products of JetBrains (especially the IntelliJ IDEA IDE) have all the good things readily included, while there are standalone products or plugins for other IDEs.

Epilogue

As usual, the Dev Brunch contained a lot more chatter and talk than listed here. The number of attendees makes for an unique experience every time. We are looking forward to the next Dev Brunch at the Softwareschneiderei in February 2017. We even have some topics already on the agenda (like a report about first-hand experiences with the programming language Rust). And as always, we are open for guests and future regulars. Just drop us a notice and we’ll invite you over next time.