InfoQ Homepage Java Content on InfoQ
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Testing RxJava2
You are ready to explore reactive opportunities in your code but you are wondering how to test out the reactive idiom in your codebase. In this article Java Champion Andres Almiray provides techniques and tools for testing RxJava2.
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Deterministic Execution on the JVM
For many use cases (for example cryptocurrency ledgers), we need to ensure that any action will execute deterministically and terminate. In this article, Ben Evans reviews the theory behind the WhitelistClassLoader.
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The Future of Java in the Enterprise - InfoQ’s Opinion
As part of ongoing work to review InfoQ’s editorial focus for the next year, we’ve been looking at the Java landscape in some detail. This article summarises our view of Java's role in the enterprise
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RXJava2 by Example
In the ongoing evolution of paradigms for simplifying concurrency under load, the most promising addition is reactive programming, a specification that provides tools for handling asynchronous streams of data and for managing flow-control, making it easier to reason about overall program design. In this article we overcome the learning curve with a gentle progression of examples.
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More Than React: Why You Shouldn’t Use ReactJS for Complex Interactive Front-End Projects, Part I
Does React function as well in complex interactive front-end projects as it does in simple interactive websites? In this article, Yang Bo introduces several problems encountered when using React in large projects and why he decided to develop a new framework to compete.
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Building Reactive Applications with Akka Actors and Java 8
Akka and Java 8 make it possible to create distributed microservice-based systems that just a few years ago were the stuff of dreams. Actor based systems enable developers to create quickly evolving microservice architectures that can elastically scale systems to support huge volumes of data.
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Refactoring to Reactive - Anatomy of a JDBC migration
Reactive programming offers built-in solutions for some of the most difficult challenges in programming, including concurrency management and flow control. So you might ask - how do I get there; can I introduce it in phases? In this article we transform a legacy application to a reactive model using RxJava.
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Polymorphism of MVC-esque Web Architecture: Real Time Reactive Fulfillment
The reactive ideal of the MVC architectural approach was diminished in web applications during the first two decades of the web age. Recent advancements have revitalized the reactive idea of the MVC architecture. In this article, Brent Chen and Victor Chen show how developers can leverage the dWMVC and pWMVC architectural paradigms to create real time reactive application behaviors.
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Key Takeaway Points and Lessons Learned from QCon San Francisco 2016
The 10th annual QCon San Francisco was the biggest yet, bringing together over 1500 team leads, architects, project managers, and engineering directors. Over 125 practitioner-speakers presented 92 full-length technical sessions and 32 in-depth tutorials, providing deep insights into real-world architectures and state of the art software development practices from a practitioner’s perspective.
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Book Review: Learn Apache JMeter by Example
JMeter is an indispensable tool for testing load and functionality of multi-tiered applications comprised of web front ends, JVM servers and a wealth of NoSQL and relational databases. This book is the manual that should have been included to help surmount the learning curve.
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Article Series: Getting a Handle on Data Science as a Software Developer
Software developers and managers are realizing that they need data science among their skills, to be able to tackle pressing problems. In this series, field experts provide guidance to help us navigate among the available data analysis options. They explore ways of understanding where data science is needed and where it’s not, and how to turn it into an asset.
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Data Science up and down the Ladder of Abstraction
Although Clojure lacks the extensive toolbox and analytic community of the most popular data science languages, R and Python, it provides a powerful environment for developing statistical thinking and for practicing effective data science.