Java Web Development (JSP/Servlets) Services

In my previous article, I demonstrated how to implement OIDC4VCI (credential issuance) and OIDC4VP (credential presentation) using Spring Boot and an Android wallet. This follow-up focuses on a critical security enhancement now mandated by EUDI standards: DPoP (Demonstrating Proof-of-Possession).

The Problem With Bearer Tokens

Traditional Bearer tokens have an inherent weakness: anyone who obtains the token can use it. If an attacker intercepts or steals a Bearer token, they can impersonate the legitimate client until the token expires (or is revoked).

One of the core factors in API test automation is verifying the response body for data integrity. It is a crucial step in the functional validation of the API to confirm that it is returning the correct data as desired.

This verification of the response body can be of a POST, GET, PUT, or PATCH API request. The same logic can be applied to any API response for verifying the data returned by the API.

Working with dates and time has always been one of the trickiest parts of Java development. For years, developers wrestled with java.util.Date, Calendar, and the never-ending confusion around mutability, time zones, thread safety, and formatting quirks. When Java 8 introduced the java.time package, it finally brought a modern and much more intuitive date-time API inspired by Joda-Time. Yet even with this improved API, many developers still find themselves constantly converting between different date representations, especially when integrating legacy systems, REST interfaces, databases, or front-end clients.

In this article, I want to walk through the best practical approaches for date conversion in Java 8+, focusing on clarity and reliability. These are patterns I’ve seen consistently used in production systems, and they help avoid many silent bugs that come from incorrect time zone assumptions, accidental loss of precision, and misuse of the older date classes.

Java remains one of the most popular languages for enterprise applications running on the cloud. While languages like Go, Rust, JavaScript, and Python have a high profile for cloud application developers, the RedMonk language rankings have ranked Java in the top three most popular languages throughout the history of the ranking.

When deploying applications to the cloud, there are a few key differences between deployment environments and development environments. Whether you’re spinning up a microservice application on Kubernetes or launching virtual machine instances, it is important to tune your Java Virtual Machine (JVM) to ensure that you are getting your money’s worth from your cloud spend. It pays to know how the JVM allocates resources and to ensure you use them efficiently.

What is Virtual Thread

Multi-threading is a widely used feature across the industry for developing Java-based applications. It allows us to run operations in parallel, enabling faster task execution. The number of threads created by any Java application is limited by the number of parallel operations the OS can handle; in other words, the number of threads in a Java application is equal to the number of OS threads. Until now, this limitation has created a bottleneck on further scaling any application, considering the current fast-paced ecosystem. 

To overcome this limitation, Java has introduced the concept of Virtual Thread in JDK21. A Java application creates a Virtual Thread and is not associated with any OS thread. It means every Virtual Thread does not need to be dependent on a Platform Thread (aka OS thread). Virtual Thread will work on any task independently and will acquire a Platform Thread only when it needs to perform any I/O operation.