Hibernate is a great Object Relational Mapping (ORM) library for accessing data in a relational database. It is one of the leading implementations of Java Persistence (formerly known as JPA). Using JPQL (based on HQL, which is still a nice syntax guide) one can access and update the data in the database through your ORM objects in a simplified SQL way. However, when implemented incorrectly one can run into serious performance problems. They can all be avoided though. Here are some important things to consider to make your queries performant.

It’s the year 2023. JDriven colleagues have gathered to discuss the new trends and deprecations of our work to put on the latest TechRadar. Once everybody is seated, everyone contributes their latest opinions. Very soon discussions run high. Lombok is dropped at the table of discussion as well. After some debate, it is decided. Lombok is put on HOLD!

When developing software I find it very useful to stick to a number of rules. They are all commonly known, but it can be very convenient to have list of them. Sticking to these rules will enhance the quality of your code drastically.

In part 1 of this blog data was exfiltrated from a workstation to GitHub using Git. In part 2, we’ll dive into investigating the data on a Windows 10 workstation to determine whether any sensitive data was exfiltrated to GitHub using Git. The investigation focuses on analyzing traces left on the device, excluding network activity logs.

When Maven needs to download artifacts from a remote repository, it logs the progress of the download. This can lead to a lot of noise in the output. Luckily, we can suppress the logging of the download progress. Since Maven 3.6.1. we can use the command-line option --no-transfer-progress to disable the logging of the download progress. There is also a short version of the option: -ntp.

In a previous blog post we learned about the default input sources that are used by Helidon SE. The list of input sources is different based on which artifacts are on the classpath of our application. When we write tests for code in our application that uses the default configuration created by Config.create() we must take into account that different input sources are used. Also here it is based on the artifacts that are on the classpath. That means that different files with configuration data are loaded, eg. a file application-test.conf when we have the artifact helidon-config-hocon and a file application-test.yml if the artifact helidon-config-yaml is on the classpath.

Blogtober, een jaarlijks terugkerend initiatief waarin onze collega’s elke (werk)dag in oktober (veelal technische) blogs delen! Echt iets voor onze developers, mensen vanuit de inhoud, die hun kennis op deze manier met de wereld delen. Tot vorige week mijn collega Erik Pronk als ‘geintje met een seintje’ liet vallen dat hij nog wacht op een blog van mij. Mijn eerste gedachte: grappig, niks voor mij. Mijn tweede gedachte: challenge accepted!

In my previous blog post Prompt Engineering: Tool or Threat to Software Engineering?, I discussed what Prompt Engineering is and how it can be used to help us as software engineers. In this follow-up blog I will dive into Claude 3, the latest AI from Anthropic, and how it can impact us as software engineers.

In this two-part blog post, we’ll explore how data exfiltration to GitHub can be carried out from a Windows 10 workstation and how to investigate such incidents. Part 1 focuses on how data can be exfiltrated using Git and GitHub. In Part 2, we’ll dive into forensic techniques to retrieve evidence of data exfiltration and determine what was sent from the workstation.