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eBook – Mockito – NPI EA (tag = Mockito)
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eBook – Java Concurrency – NPI EA (cat=Java Concurrency)
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eBook – Reactive – NPI EA (cat=Reactive)
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eBook – Java Streams – NPI EA (cat=Java Streams)
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Since its introduction in Java 8, the Stream API has become a staple of Java development. The basic operations like iterating, filtering, mapping sequences of elements are deceptively simple to use.

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Course – LSD – NPI EA (tag=Spring Data JPA)
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Partner – Moderne – NPI EA (cat=Spring Boot)
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Refactor Java code safely — and automatically — with OpenRewrite.

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1. Overview

In this quick tutorial, we’ll explore the concept of the def keyword in Groovy. It provides an optional typing feature to this dynamic JVM language.

2. Meaning of the def Keyword

The def keyword is used to define an untyped variable or a function in Groovy, as it is an optionally-typed language.

When we’re unsure of the type of a variable or field, we can leverage def to let Groovy decide types at runtime based on the assigned values:

def firstName = "Samwell"  
def listOfCountries = ['USA', 'UK', 'FRANCE', 'INDIA']

Here, firstName will be a String, and listOfCountries will be an ArrayList.

We can also use the def keyword to define the return type of a method:

def multiply(x, y) {
    return x*y
}

Here, multiply can return any type of object, depending on the parameters we pass to it.

3. def Variables

Let’s understand how def works for variables.

When we use def to declare a variable, Groovy declares it as a NullObject and assign a null value to it:

def list
assert list.getClass() == org.codehaus.groovy.runtime.NullObject
assert list.is(null)

The moment we assign a value to the list, Groovy defines its type based on the assigned value:

list = [1,2,4]
assert list instanceof ArrayList

Let’s say that we want to have our variable type dynamic and change with an assignment:

int rate = 20
rate = [12] // GroovyCastException
rate = "nill" // GroovyCastException

We cannot assign List or String to an int typed variable, as this will throw a runtime exception.

So, to overcome this problem and invoke the dynamic nature of Groovy, we’ll use the def keyword:

def rate
assert rate == null
assert rate.getClass() == org.codehaus.groovy.runtime.NullObject

rate = 12
assert rate instanceof Integer
        
rate = "Not Available"
assert rate instanceof String
        
rate = [1, 4]
assert rate instanceof List

4. def Methods

The def keyword is further used to define the dynamic return type of a method. This is handy when we can have different types of return values for a method:

def divide(int x, int y) {
    if (y == 0) {
        return "Should not divide by 0"
    } else {
        return x/y
    }
}

assert divide(12, 3) instanceof BigDecimal
assert divide(1, 0) instanceof String

We can also use def to define a method with no explicit returns:

def greetMsg() {
    println "Hello! I am Groovy"
}

5. def vs. Type

Let’s discuss some of the best practices surrounding the use of def.

Although we may use both def and type together while declaring a variable:

def int count
assert count instanceof Integer

The def keyword will be redundant there, so we should use either def or a type.

Additionally, we should avoid using def for untyped parameters in a method.

Therefore, instead of:

void multiply(def x, def y)

We should prefer:

void multiply(x, y)

Furthermore, we should avoid using def when defining constructors.

6. Groovy def vs. Java Object

As we’ve seen most of the features of the def keyword and its uses through examples, we might wonder if it’s similar to declaring something using the Object class in Java. Yes, def can be considered similar to Object:

def fullName = "Norman Lewis"

Similarly, we can use Object in Java:

Object fullName = "Norman Lewis";

7. def vs. @TypeChecked

As many of us would be from the world of strictly-typed languages, we may wonder how to force compile-time type checking in Groovy. We can easily achieve this using the @TypeChecked annotation.

For example, we can use @TypeChecked over a class to enable type checking for all of its methods and properties:

@TypeChecked
class DefUnitTest extends GroovyTestCase {

    def multiply(x, y) {
        return x * y
    }
    
    int divide(int x, int y) {
        return x / y
    }
}

Here, the DefUnitTest class will be type checked, and compilation will fail due to the multiply method being untyped. The Groovy compiler will display an error:

[Static type checking] - Cannot find matching method java.lang.Object#multiply(java.lang.Object).
Please check if the declared type is correct and if the method exists.

So, to ignore a method, we can use TypeCheckingMode.SKIP:

@TypeChecked(TypeCheckingMode.SKIP)
def multiply(x, y)

8. Conclusion

In this quick tutorial, we’ve seen how to use the def keyword to invoke the dynamic feature of the Groovy language and have it determine the types of variables and methods at runtime.

This keyword can be handy in writing dynamic and robust code.

The code backing this article is available on GitHub. Once you're logged in as a Baeldung Pro Member, start learning and coding on the project.
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Once the early-adopter seats are all used, the price will go up and stay at $33/year.

eBook – HTTP Client – NPI EA (cat=HTTP Client-Side)
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eBook – Java Concurrency – NPI EA (cat=Java Concurrency)
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eBook – Java Streams – NPI EA (cat=Java Streams)
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Since its introduction in Java 8, the Stream API has become a staple of Java development. The basic operations like iterating, filtering, mapping sequences of elements are deceptively simple to use.

But these can also be overused and fall into some common pitfalls.

To get a better understanding on how Streams work and how to combine them with other language features, check out our guide to Java Streams:

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eBook – Persistence – NPI EA (cat=Persistence)
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Course – LS – NPI EA (cat=REST)

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Partner – Moderne – NPI EA (tag=Refactoring)
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Modern Java teams move fast — but codebases don’t always keep up. Frameworks change, dependencies drift, and tech debt builds until it starts to drag on delivery. OpenRewrite was built to fix that: an open-source refactoring engine that automates repetitive code changes while keeping developer intent intact.

The monthly training series, led by the creators and maintainers of OpenRewrite at Moderne, walks through real-world migrations and modernization patterns. Whether you’re new to recipes or ready to write your own, you’ll learn practical ways to refactor safely and at scale.

If you’ve ever wished refactoring felt as natural — and as fast — as writing code, this is a good place to start.

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eBook Jackson – NPI EA – 3 (cat = Jackson)