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Azure Container Apps is a fully managed serverless container service that enables you to build and deploy modern, cloud-native Java applications and microservices at scale. It offers a simplified developer experience while providing the flexibility and portability of containers.

Of course, Azure Container Apps has really solid support for our ecosystem, from a number of build options, managed Java components, native metrics, dynamic logger, and quite a bit more.

To learn more about Java features on Azure Container Apps, visit the documentation page.

You can also ask questions and leave feedback on the Azure Container Apps GitHub page.

Partner – Microsoft – NPI EA (cat= Spring Boot)
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Azure Container Apps is a fully managed serverless container service that enables you to build and deploy modern, cloud-native Java applications and microservices at scale. It offers a simplified developer experience while providing the flexibility and portability of containers.

Of course, Azure Container Apps has really solid support for our ecosystem, from a number of build options, managed Java components, native metrics, dynamic logger, and quite a bit more.

To learn more about Java features on Azure Container Apps, you can get started over on the documentation page.

And, you can also ask questions and leave feedback on the Azure Container Apps GitHub page.

Partner – Orkes – NPI EA (cat=Spring)
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Modern software architecture is often broken. Slow delivery leads to missed opportunities, innovation is stalled due to architectural complexities, and engineering resources are exceedingly expensive.

Orkes is the leading workflow orchestration platform built to enable teams to transform the way they develop, connect, and deploy applications, microservices, AI agents, and more.

With Orkes Conductor managed through Orkes Cloud, developers can focus on building mission critical applications without worrying about infrastructure maintenance to meet goals and, simply put, taking new products live faster and reducing total cost of ownership.

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Partner – Orkes – NPI EA (tag=Microservices)
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Modern software architecture is often broken. Slow delivery leads to missed opportunities, innovation is stalled due to architectural complexities, and engineering resources are exceedingly expensive.

Orkes is the leading workflow orchestration platform built to enable teams to transform the way they develop, connect, and deploy applications, microservices, AI agents, and more.

With Orkes Conductor managed through Orkes Cloud, developers can focus on building mission critical applications without worrying about infrastructure maintenance to meet goals and, simply put, taking new products live faster and reducing total cost of ownership.

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eBook – Guide Spring Cloud – NPI EA (cat=Spring Cloud)
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eBook – Mockito – NPI EA (tag = Mockito)
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Mocking is an essential part of unit testing, and the Mockito library makes it easy to write clean and intuitive unit tests for your Java code.

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eBook – Java Concurrency – NPI EA (cat=Java Concurrency)
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Spring 5 added support for reactive programming with the Spring WebFlux module, which has been improved upon ever since. Get started with the Reactor project basics and reactive programming in Spring Boot:

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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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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 – Jackson – NPI EA (cat=Jackson)
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Explore Spring Boot 3 and Spring 6 in-depth through building a full REST API with the framework:

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I built the security material as two full courses - Core and OAuth, to get practical with these more complex scenarios. We explore when and how to use each feature and code through it on the backing project.

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Partner – MongoDB – NPI EA (tag=MongoDB)
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Traditional keyword-based search methods rely on exact word matches, often leading to irrelevant results depending on the user's phrasing.

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Partner – LambdaTest – NPI EA (cat=Testing)
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1. Overview

In a previous article, we learned how to use XStream to serialize Java objects to XML. In this tutorial, we will learn how to do the reverse: deserialize XML to Java objects. These tasks can be accomplished using annotations or programmatically.

To learn about the basic requirements for setting up XStream and its dependencies, please reference the previous article.

2. Deserialize an Object from XML

To start with, suppose we have the following XML:

<com.baeldung.pojo.Customer>
    <firstName>John</firstName>
    <lastName>Doe</lastName>
    <dob>1986-02-14 03:46:16.381 UTC</dob>
</com.baeldung.pojo.Customer>

We need to convert this to a Java Customer object:

public class Customer {
 
    private String firstName;
    private String lastName;
    private Date dob;
 
    // standard setters and getters
}

The XML can be input in a number of ways, including File, InputStream, Reader, or String. For simplicity, we’ll assume that we have the XML above in a String object.

Customer convertedCustomer = (Customer) xstream.fromXML(customerXmlString);
Assert.assertTrue(convertedCustomer.getFirstName().equals("John"));

3. Security Aspects

Because XStream uses undocumented Java features as well as Java Reflection, it may be vulnerable to an Arbitrary Code Execution or Remote Command Execution attacks.

In-depth security considerations are out of the scope of this tutorial, but we do have a dedicated article that explains the threat. Also, it’s worth checking out XStream’s official page.

For the purpose of our tutorial, let’s assume that all our classes are “safe”. Consequently, we need to configure XStream:

XStream xstream = new XStream();
xstream.allowTypesByWildcard(new String[]{"com.baeldung.**"});

4. Aliases

In the first example, the XML had the fully-qualified name of the class in the outermost XML tag, matching the location of our Customer class. With this setup, XStream easily converts the XML to our object without any extra configuration. But we may not always have these conditions. We might not have control over the XML tag naming, or we might decide to add aliases for fields.

For example, suppose we modified our XML to not use the fully-qualified class name for the outer tag:

<customer>
    <firstName>John</firstName>
    <lastName>Doe</lastName>
    <dob>1986-02-14 03:46:16.381 UTC</dob>
</customer>

We can covert this XML by creating aliases.

4.1. Class Aliases

We register aliases with the XStream instance either programmatically or using annotations. We can annotate our Customer class with @XStreamAlias:

@XStreamAlias("customer")
public class Customer {
    //...
}

Now we need to configure our XStream instance to use this annotation:

xstream.processAnnotations(Customer.class);

Alternatively, if we wish to configure an alias programmatically, we can use the code below:

xstream.alias("customer", Customer.class);

4.2. Field Aliases

Suppose we have the following XML:

<customer>
    <fn>John</fn>
    <lastName>Doe</lastName>
    <dob>1986-02-14 03:46:16.381 UTC</dob>
</customer>

The fn tag doesn’t match any fields in our Customer object, so we will need to define an alias for that field if we wish to deserialize it. We can achieve this using the following annotation:

@XStreamAlias("fn")
private String firstName;

Alternatively, we can accomplish the same goal programmatically:

xstream.aliasField("fn", Customer.class, "firstName");

5. Implicit Collections

Let’s say we have the following XML, containing a simple list of ContactDetails:

<customer>
    <firstName>John</firstName>
    <lastName>Doe</lastName>
    <dob>1986-02-14 04:14:20.541 UTC</dob>
    <ContactDetails>
        <mobile>6673543265</mobile>
        <landline>0124-2460311</landline>
    </ContactDetails>
    <ContactDetails>...</ContactDetails>
</customer>

We want to load the list of ContactDetails into a List<ContactDetails> field in our Java object. We can achieve this by using the following annotation:

@XStreamImplicit
private List<ContactDetails> contactDetailsList;

Alternatively, we can accomplish the same goal programmatically:

xstream.addImplicitCollection(Customer.class, "contactDetailsList");

6. Ignore Fields

Let’s say we have following XML:

<customer>
    <firstName>John</firstName>
    <lastName>Doe</lastName>
    <dob>1986-02-14 04:14:20.541 UTC</dob>
    <fullName>John Doe</fullName>
</customer>

In the XML above, we have extra element <fullName> which is missing from our Java Customer object.

If we try to deserialize the above xml without taking any care for extra element, program throws an UnknownFieldException.

No such field com.baeldung.pojo.Customer.fullName

As the exception clearly states, XStream does not recognize the field fullName.

To overcome this problem we need to configure it to ignore unknown elements:

xstream.ignoreUnknownElements();

7. Attribute Fields

Suppose we have XML with attributes as part of elements that we’d like to deserialize as a field in our object. We will add a contactType attribute to our ContactDetails object:

<ContactDetails contactType="Office">
    <mobile>6673543265</mobile>
    <landline>0124-2460311</landline>
</ContactDetails>

If we want to deserialize the contactType XML attribute, we can use the @XStreamAsAttribute annotation on the field we’d like it to appear in:

@XStreamAsAttribute
private String contactType;

Alternatively, we can accomplish the same goal programmatically:

xstream.useAttributeFor(ContactDetails.class, "contactType");

8. Conclusion

In this article, we explored the options we have available when deserializing XML to Java objects using XStream.

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.
Baeldung Pro – NPI EA (cat = Baeldung)
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Baeldung Pro comes with both absolutely No-Ads as well as finally with Dark Mode, for a clean learning experience:

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Once the early-adopter seats are all used, the price will go up and stay at $33/year.

Partner – Microsoft – NPI EA (cat = Baeldung)
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Azure Container Apps is a fully managed serverless container service that enables you to build and deploy modern, cloud-native Java applications and microservices at scale. It offers a simplified developer experience while providing the flexibility and portability of containers.

Of course, Azure Container Apps has really solid support for our ecosystem, from a number of build options, managed Java components, native metrics, dynamic logger, and quite a bit more.

To learn more about Java features on Azure Container Apps, visit the documentation page.

You can also ask questions and leave feedback on the Azure Container Apps GitHub page.

Partner – Microsoft – NPI EA (cat = Spring Boot)
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Azure Container Apps is a fully managed serverless container service that enables you to build and deploy modern, cloud-native Java applications and microservices at scale. It offers a simplified developer experience while providing the flexibility and portability of containers.

Of course, Azure Container Apps has really solid support for our ecosystem, from a number of build options, managed Java components, native metrics, dynamic logger, and quite a bit more.

To learn more about Java features on Azure Container Apps, visit the documentation page.

You can also ask questions and leave feedback on the Azure Container Apps GitHub page.

Partner – Orkes – NPI EA (cat = Spring)
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Modern software architecture is often broken. Slow delivery leads to missed opportunities, innovation is stalled due to architectural complexities, and engineering resources are exceedingly expensive.

Orkes is the leading workflow orchestration platform built to enable teams to transform the way they develop, connect, and deploy applications, microservices, AI agents, and more.

With Orkes Conductor managed through Orkes Cloud, developers can focus on building mission critical applications without worrying about infrastructure maintenance to meet goals and, simply put, taking new products live faster and reducing total cost of ownership.

Try a 14-Day Free Trial of Orkes Conductor today.

Partner – Orkes – NPI EA (tag = Microservices)
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Modern software architecture is often broken. Slow delivery leads to missed opportunities, innovation is stalled due to architectural complexities, and engineering resources are exceedingly expensive.

Orkes is the leading workflow orchestration platform built to enable teams to transform the way they develop, connect, and deploy applications, microservices, AI agents, and more.

With Orkes Conductor managed through Orkes Cloud, developers can focus on building mission critical applications without worrying about infrastructure maintenance to meet goals and, simply put, taking new products live faster and reducing total cost of ownership.

Try a 14-Day Free Trial of Orkes Conductor today.

eBook – HTTP Client – NPI EA (cat=HTTP Client-Side)
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The Apache HTTP Client is a very robust library, suitable for both simple and advanced use cases when testing HTTP endpoints. Check out our guide covering basic request and response handling, as well as security, cookies, timeouts, and more:

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eBook – Java Concurrency – NPI EA (cat=Java Concurrency)
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Handling concurrency in an application can be a tricky process with many potential pitfalls. A solid grasp of the fundamentals will go a long way to help minimize these issues.

Get started with understanding multi-threaded applications with our Java Concurrency guide:

>> Download the eBook

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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Working on getting your persistence layer right with Spring?

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Partner – MongoDB – NPI EA (tag=MongoDB)
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Traditional keyword-based search methods rely on exact word matches, often leading to irrelevant results depending on the user's phrasing.

By comparison, using a vector store allows us to represent the data as vector embeddings, based on meaningful relationships. We can then compare the meaning of the user’s query to the stored content, and retrieve more relevant, context-aware results.

Explore how to build an intelligent chatbot using MongoDB Atlas, Langchain4j and Spring Boot:

>> Building an AI Chatbot in Java With Langchain4j and MongoDB Atlas

Course – LS – NPI EA (cat=REST)

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Get started with Spring Boot and with core Spring, through the Learn Spring course:

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