TALK 1 ABSTRACT

Managing Testing Data

(jChampions Talk - In-person and also live streamed here)

Have you ever tried to troubleshoot an issue taking a looking at the log files? I bet you did! And it turns out the issue is related to data usage because, you know, users will use real data! Developers won't! A good thing about your recent troubleshooting is that you can understand the data. It's not a bunch of numbers or UUIDs in the name field. How about your development environment? Probably you use either hard-coded data or random strings. We must fix that!

This presentation showed us how to manage testing data in two different ways.

The first way is the creation of a Test Data Factory approach, where we used the Factory Pattern to easily create any objects we want with understandable and reliable data. This approach will make you in control of your own data, so you can find any bug in the early stages of the SDLC and the DataFaker library will help us to generate good random data in every execution.

In a second way, we learned and applied the Data-Driven Testing approach, where the same requirement can be applied to different sets of data, generating different results. This approach can reduce the amount of code and the execution time. With the support of JUnit 5 you will learn how to do it in 5 different ways: value source, internal method source, external method source, argument provider, and CVS source.

In-person talk streamed LIVE to jChampions Conference

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Drinks and food courtesy of our partners, Integral Ad Science, Stack and Co, FINEOS and tcube Dublin.

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TALK 2 ABSTRACT

DataFaker: the most powerful fake data generator library

(Bonus Talk - In-person attendees only)

Data generators in software testing play a critical role in creating realistic and diverse datasets for testing scenarios. However, they present challenges, such as ensuring data diversity, maintaining quality, facilitating validation, and ensuring long-term maintainability.

While many engineers are familiar with these challenges, they often resort to non-specialized tools like the RandomStringUtils class from Apache Commons or the Random class, concatenating fixed data with it. This approach lacks scalability and may not yield a valid dataset.

Thankfully we have DataFaker, a library for Java and Kotlin to generate fake data, based on generators, that can be very helpful when generating test data to fill a database, to generate data for a stress test, or to anonymize data from production services.

Meet Elias

Senior Principal Software Engineer at Backbase

Elias is a Java Champion, Oracle ACE Pro, Java Magazine NL and Senior Principal Software Engineer at Backbase.

He shares content related to Java, OSS and Quality Engineering at conferences, meetups, articles and open-source conferences.

Linkedin: https://www.linkedin.com/in/eliasnogueira/

X / Twitter: https://x.com/eliasnogueira

About the Dublin Java User Group Since 2006, the Dublin Java User Group, aka DubJUG, has been working with the global Java community to amplify technical knowledge for the benefit of Irish based developers and businesses.