Due to the high interest and controversy concerning this blog post, we believe that it is worth adding some context on how we work and make decisions at Allegro. Each of more than 50 development teams at Allegro has the freedom to choose technologies from those supported by our PaaS. We mainly code in Java, Kotlin, Python and Golang. The point of view presented in the article results from the author’s experience.

Kotlin is popular, Kotlin is trendy. Kotlin gives you compile-time null-safety and less boilerplate. Naturally, it’s better than Java. You should switch to Kotlin or die as a legacy coder. Hold on, or maybe you shouldn’t? Before you start writing in Kotlin, read the story of one project. The story about quirks and obstacles becoming so annoying that we decided to rewrite.

We gave Kotlin a try, but now we are rewriting to Java 10

I have my favorite set of JVM languages. Java in /main and Groovy in /test are the best-performing duo for me. In summer 2017 my team started a new microservice project, and as usual, we talked about languages and technologies. There are a few Kotlin advocating teams at Allegro, and we wanted to try something new, so we decided to give Kotlin a try. Since there is no Spock counterpart for Kotlin, we decided to stick with Groovy in /test (Spek isn’t as good as Spock). In winter 2018, after few months of working with Kotlin on a daily basis, we summarized pros and cons and arrived at the conclusion that Kotlin made us less productive. We started rewriting this microservice to Java.

Here are the reasons why.

Name shadowing

Shadowing was my biggest surprise in Kotlin. Consider this function:

fun inc ( num : Int ) { val num = 2 if ( num > 0 ) { val num = 3 } println ( "num: " + num ) }

What will be printed when you call inc(1) ? Well, in Kotlin, method arguments are values, so you can’t change the num argument. That’s good language design because you shouldn’t change method arguments. But you can define another variable with the same name and initialize it to whatever you wish. Now you have two variables named num in the method level scope. Of course, you can access only the one num at a time, so effectively, the value of the num is changed. Checkmate.

In the if body, you can add another num , which is less shocking (new block-level scope).

Okay, so in Kotlin, inc(1) prints 2. The equivalent code in Java, won’t compile:

void inc ( int num ) { int num = 2 ; //error: variable 'num' is already defined in the scope if ( num > 0 ) { int num = 3 ; //error: variable 'num' is already defined in the scope } System . out . println ( "num: " + num ); }

Name shadowing wasn’t invented by Kotlin. It’s common in programming languages. In Java, we get used to shadowing class fields with methods arguments:

public class Shadow { int val ; public Shadow ( int val ) { this . val = val ; } }

In Kotlin, shadowing goes too far. Definitely, it’s a design flaw made by Kotlin team. IDEA team tried to fix this by showing you the laconic warning on each shadowed variable: Name shadowed. Both teams work in the same company, so maybe they can talk to each other and reach a consensus on the shadowing issue? My hint — IDEA guys are right. I can’t imagine a valid use case for shadowing a method argument.

Type inference

In Kotlin, when you declare a var or val , you usually let the compiler guess the variable type from the type of expression on the right. We call it local variable type inference, and it’s a great improvement for programmers. It allows us to simplify the code without compromising static type checking.

For example, this Kotlin code:

var a = "10"

would be translated by the Kotlin compiler into:

var a : String = "10"

It was the real advantage over Java. I deliberately said was, because — good news — Java 10 has it and Java 10 is available now.

Type inference in Java 10:

var a = "10" ;

To be fair, I need to add, that Kotlin is still slightly better in this field. You can use type inference also in other contexts, for example, one-line methods.

More about Local-Variable Type Inference in Java 10.

Compile time null-safety

Null-safe types are Kotlin’s killer feature. The idea is great. In Kotlin, types are by default non-nullable. If you need a nullable type you need to add ? to it, for example:

val a : String ? = null // ok val b : String = null // compilation error

Kotlin won’t compile if you use a nullable variable without the null check, for example:

println ( a . length ) // compilation error println ( a ?. length ) // fine, prints null println ( a ?. length ?: 0 ) // fine, prints 0

Once you have these this two kind of types, non-nullable T and nullable T? , you can forget about the most common exception in Java — NullPointerException. Really? Unfortunately, it’s not that simple.

Things get nasty when your Kotlin code has to get along with Java code (libraries are written in Java, so it happens pretty often I guess). Then, the third kind of type jumps in — T! . It’s called platform type, and somehow it means T or T? . Or if we want to be precise, T! means T with undefined nullability. This weird type can’t be denoted in Kotlin, it can be only inferred from Java types. T! can mislead you because it’s relaxed about nulls and disables Kotlin’s null-safety net.

Consider the following Java method:

public class Utils { static String format ( String text ) { return text . isEmpty () ? null : text ; } }

Now, you want to call format(String) from Kotlin. Which type should you use to consume the result of this Java method? Well, you have three options.

First approach. You can use String , the code looks safe but can throw NPE.

fun doSth ( text : String ) { val f : String = Utils . format ( text ) // compiles but assignment can throw NPE at runtime println ( "f.len : " + f . length ) }

You need to fix it with Elvis:

fun doSth ( text : String ) { val f : String = Utils . format ( text ) ?: "" // safe with Elvis println ( "f.len : " + f . length ) }

Second approach. You can use String? , and then you are null-safe:

fun doSth ( text : String ) { val f : String ? = Utils . format ( text ) // safe println ( "f.len : " + f . length ) // compilation error, fine println ( "f.len : " + f ?. length ) // null-safe with ? operator }

Third approach. What if you just let the Kotlin do the fabulous local variable type inference?

fun doSth ( text : String ) { val f = Utils . format ( text ) // f type inferred as String! println ( "f.len : " + f . length ) // compiles but can throw NPE at runtime }

Bad idea. This Kotlin code looks safe, compiles, but allows nulls for the unchecked journey through your code, pretty much like in Java.

There is one more trick, the !! operator. Use it to force inferring f type as String :

fun doSth ( text : String ) { val f = Utils . format ( text ) !! // throws NPE when format() returns null println ( "f.len : " + f . length ) }

In my opinion, Kotlin’s type system with all these scala-like ! , ? , and !! is too complex. Why Kotlin infers from Java T to T! and not to T? ? It seems like Java interoperability spoils Kotlin’s killer feature — the type inference. Looks like you should declare types explicitly (as T? ) for all Kotlin variables populated by Java methods.

Class literals

Class literals are common when using Java libraries like Log4j or Gson.

In Java, we write the class name with .class suffix:

Gson gson = new GsonBuilder (). registerTypeAdapter ( LocalDate . class , new LocalDateAdapter ()). create ();

In Groovy, class literals are simplified to the essence. You can omit the .class and it doesn’t matter if it’s a Groovy or Java class.

def gson = new GsonBuilder (). registerTypeAdapter ( LocalDate , new LocalDateAdapter ()). create ()

Kotlin distinguishes between Kotlin and Java classes and has the syntax ceremony for it:

val kotlinClass : KClass < LocalDate > = LocalDate :: class val java Class : Class < LocalDate > = LocalDate :: class . java

So in Kotlin, you are forced to write:

val gson = GsonBuilder (). registerTypeAdapter ( LocalDate :: class . java , LocalDateAdapter ()). create ()

Which is ugly.

Reversed type declaration

In the C-family of programming languages, we have the standard way of declaring types of things. Shortly, first goes a type, then goes a typed thing (variable, fields, method, and so on).

Standard notation in Java:

int inc ( int i ) { return i + 1 ; }

Reversed notation in Kotlin:

fun inc ( i : Int ): Int { return i + 1 }

This disorder is annoying for several reasons.

First, you need to type and read this noisy colon between names and types. What is the purpose of this extra character? Why are names separated from their types? I have no idea. Sadly, it makes your work in Kotlin harder.

The second problem. When you read a method declaration, first of all, you are interested in the name and the return type, and then you scan the arguments.

In Kotlin, the method’s return type could be far at the end of the line, so you need to scroll:

private fun getMetricValue ( kafkaTemplate : KafkaTemplate < String , ByteArray >, metricName : String ) : Double { .. . }

Or, if arguments are formatted line-by-line, you need to search. How much time do you need to find the return type of this method?

@Bean fun kafkaTemplate ( @Value ( "\${interactions.kafka.bootstrap-servers-dc1}" ) bootstrapServersDc1 : String , @Value ( "\${interactions.kafka.bootstrap-servers-dc2}" ) bootstrapServersDc2 : String , cloudMetadata : CloudMetadata , @Value ( "\${interactions.kafka.batch-size}" ) batchSize : Int , @Value ( "\${interactions.kafka.linger-ms}" ) lingerMs : Int , metricRegistry : MetricRegistry ): KafkaTemplate < String , ByteArray > { val bootstrapServer = if ( cloudMetadata . datacenter == "dc1" ) { bootstrapServersDc1 } .. . }

The third problem with reversed notation is poor auto-completion in an IDE. In standard notation, you start from a type name, and it’s easy to find a type. Once you pick a type, an IDE gives you several suggestions about a variable name, derived from selected type. So you can quickly type variables like this:

MongoExperimentsRepository repository

Typing this variable in Kotlin is harder even in IntelliJ, the greatest IDE ever. If you have many repositories, you won’t find the right pair on the auto-completion list. It means typing the full variable name by hand.

repository : MongoExperimentsRepository

Companion object

A Java programmer comes to Kotlin.

“Hi, Kotlin. I’m new here, may I use static members?” He asks.

“No. I’m object-oriented and static members aren’t object-oriented,” Kotlin replies.

“Fine, but I need the logger for MyClass , what should I do?”

“No problem, use a companion object then.”

“And what’s a companion object?”

“It’s the singleton object bounded to your class. Put your logger in the companion object,” Kotlin explains.

“I see. Is it right?”



class MyClass { companion object { val logger = LoggerFactory . getLogger ( MyClass :: class . java ) } }

“Yes!“

“Quite verbose syntax,” the programmer seems puzzled, “but okay, now I can call my logger like this — MyClass.logger , just like a static member in Java?”

“Um… yes, but it’s not a static member! There are only objects here. Think of it as the anonymous inner class already instantiated as the singleton. And in fact this class isn’t anonymous, it’s named Companion , but you can omit the name. See? That’s simple.“



I appreciate the object declaration concept — singletons are useful. But removing static members from the language is impractical. In Java, we are using static loggers for years. It’s classic. It’s just a logger, so we don’t care about object-oriented purity. It works, and it never did any harm.

Sometimes, you have to use static. Old good public static void main() is still the only way to launch a Java app. Try to write this companion object spell without googling.

class AppRunner { companion object { @JvmStatic fun main ( args : Array < String >) { SpringApplication . run ( AppRunner :: class . java , * args ) } } }

Collection literals

In Java, initializing a list requires a lot of ceremony:

import java.util.Arrays ; ... List < String > strings = Arrays . asList ( "Saab" , "Volvo" );

Initializing a Map is so verbose, that lot of people use Guava:

import com.google.common.collect.ImmutableMap ; ... Map < String , String > string = ImmutableMap . of ( "firstName" , "John" , "lastName" , "Doe" );

In Java, we are still waiting for the new syntax to express collection and map literals. The syntax, which is so natural and handy in many languages.

JavaScript:

const list = [ ' Saab ' , ' Volvo ' ] const map = { ' firstName ' : ' John ' , ' lastName ' : ' Doe ' }

Python:

list = [ 'Saab' , 'Volvo' ] map = { 'firstName' : 'John' , 'lastName' : 'Doe' }

Groovy:

def list = [ 'Saab' , 'Volvo' ] def map = [ 'firstName' : 'John' , 'lastName' : 'Doe' ]

Simply, the neat syntax for collection literals is what you expect from a modern programming language, especially if it’s created from scratch. Instead of collection literals, Kotlin offers the bunch of built-in functions: listOf() , mutableListOf() , mapOf() , hashMapOf() , and so on.

Kotlin:

val list = listOf ( "Saab" , "Volvo" ) val map = mapOf ( "firstName" to "John" , "lastName" to "Doe" )

In maps, keys and values are paired with the to operator, which is good, but why not use well-known : for that? Disappointing.

Maybe? Nope

Functional languages (like Haskell) don’t have nulls. Instead, they offer the Maybe monad (if you are not familiar with monads, read this article by Tomasz Nurkiewicz).

Maybe was introduced to the JVM world the long time ago by Scala as Option, and then, became adopted in Java 8 as Optional. Now, Optional are quite popular way of dealing with nulls in return types at API boundaries.

There is no Optional equivalent in Kotlin. It seems that you should use bare Kotlin’s nullable types. Let’s investigate this issue.

Typically, when you have an Optional, you want to apply a series of null-safe transformations and deal with null at the and.

For example, in Java:

public int parseAndInc ( String number ) { return Optional . ofNullable ( number ) . map ( Integer: : parseInt ) . map ( it -> it + 1 ) . orElse ( 0 ); }

No problem one might say, in Kotlin, for mapping you can use the let function:

fun parseAndInc ( number : String ?): Int { return number . let { Integer . parseInt ( it ) } . let { it -> it + 1 } ?: 0 }

Can you? Yes, but it’s not that simple. The above code is wrong and throws NPE from parseInt() . The monadic-style map() is executed only if the value is present. Otherwise, null is just passed by. That’s why map() is so handy. Unfortunately, Kotlin’s let doesn’t work that way. It’s just called on everything from the left, including nulls.

So in order make this code null-safe, you have to add ? before each let :

fun parseAndInc ( number : String ?): Int { return number ?. let { Integer . parseInt ( it ) } ?. let { it -> it + 1 } ?: 0 }

Now, compare readability of the Java and Kotlin versions. Which one do you prefer?

Read more about Optionals at Stephen Colebourne’s blog.

Data classes

Data classes are Kotlin’s way to reduce the boilerplate that is inevitable in Java when implementing Value Objects (aka DTO).

For example, in Kotlin, you write only the essence of a Value Object:

data class User ( val name : String , val age : Int )

and Kotlin generates good implementations of equals() , hashCode() , toString() , and copy() .

It’s really useful when implementing simple DTOs. But remember, Data classes come with the serious limitation — they are final. You cannot extend a Data class or make it abstract. So probably, you won’t use them in a core domain model.

This limitation is not Kotlin’s fault. There is no way to generate the correct value-based equals() without violating the Liskov Principle. That’s why Kotlin doesn’t allow inheritance for Data classes.

Open classes

In Kotlin, classes are final by default. If you want to extend a class, you have to add the open modifier to it.

Inheritance syntax looks like this:

open class Base class Derived : Base ()

Kotlin changed the extends keyword into the : operator, which is already used to separate variable name from its type. Back to C++ syntax? For me it’s confusing.

What is controversial here is making classes final by default. Maybe Java programmers overuse inheritance. Maybe you should think twice before allowing for extending your class. But we live in the frameworks world, and frameworks love AOP. Spring uses libraries (cglib, jassist) to generate dynamic proxies for your beans. Hibernate extends you entities to enable lazy loading.

If you are using Spring, you have two options. You can put open in front of all bean classes (which is rather boring), or use this tricky compiler plugin:

buildscript { dependencies { classpath group: 'org.jetbrains.kotlin' , name: 'kotlin-allopen' , version: "$versions.kotlin" } }

Steep learning curve

If you think that you can learn Kotlin quickly because you already know Java — you are wrong. Kotlin would throw you in the deep end. In fact, Kotlin’s syntax is far closer to Scala. It’s the all-in bet. You would have to forget Java and switch to the completely different language.

On the contrary, learning Groovy is a pleasant journey. Groovy would lead you by the hand. Java code is correct Groovy code, so you can start by changing the file extension from .java to .groovy . Each time when you learn a new Groovy feature, you can decide. Do you like it or do you prefer to stay with the Java way? That’s awesome.

Final thoughts

Learning a new technology is like an investment. We invest our time and then the technology should pay off. I’m not saying that Kotlin is a bad language. I’m just saying that in our case, the costs outweighed the benefits.

Funny facts about Kotlin

In Poland, Kotlin is one of the best selling brands of ketchup. This name clash is nobody’s fault, but it’s funny. Kotlin sounds to our ears like Heinz.