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.
Get started with mocking and improve your application tests using our Mockito guide:
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:
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:
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:
Explore Spring Boot 3 and Spring 6 in-depth through building a full REST API with the framework:
Yes, Spring Security can be complex, from the more advanced functionality within the Core to the deep OAuth support in the framework.
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.
You can explore the course here:
Spring Data JPA is a great way to handle the complexity of JPA with the powerful simplicity of Spring Boot.
Get started with Spring Data JPA through the guided reference course:
Refactor Java code safely — and automatically — with OpenRewrite.
Refactoring big codebases by hand is slow, risky, and easy to put off. That’s where OpenRewrite comes in. The open-source framework for large-scale, automated code transformations helps teams modernize safely and consistently.
Each month, the creators and maintainers of OpenRewrite at Moderne run live, hands-on training sessions — one for newcomers and one for experienced users. You’ll see how recipes work, how to apply them across projects, and how to modernize code with confidence.
Join the next session, bring your questions, and learn how to automate the kind of work that usually eats your sprint time.
Distributed systems often come with complex challenges such as service-to-service communication, state management, asynchronous messaging, security, and more.
Dapr (Distributed Application Runtime) provides a set of APIs and building blocks to address these challenges, abstracting away infrastructure so we can focus on business logic.
In this tutorial, we'll focus on Dapr's pub/sub API for message brokering. Using its Spring Boot integration, we'll simplify the creation of a loosely coupled, portable, and easily testable pub/sub messaging system:
1. Introduction
In this article, we’ll go through an overview of Artificial Intelligence (AI) libraries in Java.
Some theoretical knowledge of AI would be helpful in understanding the use of these libraries.
AI is a very wide field, so we will be focusing on some of the most popular fields today, like Natural Language Processing, Machine Learning, and Neural Networks. In the end, we’ll see some interesting AI challenges where we can practice our understanding of AI.
2. Expert Systems
2.1. Apache Jena
Apache Jena is an open-source Java framework for building semantic web and linked data applications from RDF data. It provides an API to extract data from and write to RDF graphs.
2.2. PowerLoom Knowledge Representation and Reasoning System
PowerLoom is a platform for the creation of intelligent, knowledge-based applications. It provides a Java API with detailed documentation.
2.3. d3web
d3web is an open-source reasoning engine for developing, testing, and applying problem-solving knowledge onto a given problem situation, with many algorithms already included.
2.4. Eye
Eye is an open-source reasoning engine for performing semi-backward reasoning.
2.5. Tweety
Tweety is a collection of Java frameworks for logical aspects of AI and knowledge representation.
2.6. OptaPlanner
OptaPlanner is a Java-based constraint solver. It can serve a number of use cases like vehicle routing, employee rostering, maintenance scheduling, and school timetabling, to name a few.
2.7. Timefold
Timefold is an open-source solver AI for Java. It optimizes vehicle routing, maintenance scheduling, shift scheduling, field service routing, last-mile delivery, job shop scheduling, and other NP-hard problems.
3. Neural Networks
3.1. Neuroph
Neuroph is an lightweight Java framework for neural network creation. It comes with an open-source Java library and a GUI editor for quickly creating Java neural network components
3.2. Deeplearning4j
Deeplearning4j is a deep learning library for the JVM, and it also provides an API for neural network creation.
4. Natural Language Processing
4.1. Apache OpenNLP
Apache OpenNLP is an open-source Natural Language Processing Java library. It features an API for use cases like Named Entity Recognition, Sentence Detection, POS tagging and Tokenization.
4.2. Stanford CoreNLP
Stanford CoreNLP is a popular Java NLP framework that provides various tools for performing NLP tasks.
5. Machine Learning
5.1. RapidMiner
RapidMiner is a data science platform that provides various machine learning algorithms through GUI and Java API. It has a big community with many tutorials and extensive documentation.
5.2. Weka
Weka is a collection of machine learning algorithms for data mining tasks. It provides tools for a number of use cases like data clustering and association rules mining visualization.
5.3. Encog Machine Learning Framework
Encong is a Java machine learning framework that supports many ML algorithms. It’s developed by Jeff Heaton from Heaton Research.
5.4. Deep Java Library (DJL)
Deep Java Library is an open-source library developed by AWS Labs. It provides an intuitive, framework-independent Java API for training and testing learning models.
6. Genetic Algorithms
6.1. Jenetics
Jenetics is an advanced genetic algorithm written in Java. It provides a clear separation of the genetic algorithm concepts.
6.2. Watchmaker Framework
Watchmaker Framework is a framework for implementing genetic algorithms in Java.
6.3. ECJ 23
ECJ 23 is a Java-based research framework with strong algorithmic support for genetic algorithms. It is highly flexible, with most of the settings being dynamically determined at runtime.
6.4. Java Genetic Algorithms Package (JGAP)
JGAP is a genetic programming component provided as a Java framework.
6.5. Eva
Eva is a simple Java OOP evolutionary algorithm framework.
7. Automatic Programming
7.1. Spring Roo
7.2. Acceleo
Acceleo is an open-source code generator for Eclipse that generates code from EMF models defined from any metamodel (UML, SysML, and others).
8. Challenges
We can find many online challenges and competitions related to AI. Here’s a list of some competitions where we can train and test our skills:
9. Conclusion
AI is a very wide field that is evolving at a rapid rate. In this article, we presented various Java AI frameworks that can make our applications better and more innovative.
