Today I am presenting the CBTF (Caught by the Fuzz!) package at the useR! 2026 conference in Warsaw.

Only two weeks after our previous release, we are proud to announce the release of version 1.2.1 of the Luminescence R package. This is a minor release made upon request by CRAN, as we’ll explain further down. Nonetheless, there are a few interesting changes and some regression fixes (mainly cosmetic) that make it worthwhile to update. In total we solved 25 issues in 60 commits.

We are very excited to announce the release of version 1.2.0 of the Luminescence R package. This is a major release that, once again, comes exactly 3 months after our previous release.

There are a lot of exciting things to discuss about this release, many of which related to consistency in function argument names and behaviour, but also new functionalities and some quality of life improvements. In total we solved 112 issues in 415 commits.

From 4 to 6 March 2026, the REPLAY project team convened for its second annual meeting at Schloss Rauischholzhausen, a historic 19th-century hunting lodge near Giessen.

It has been a while since our previous update concerning RLumShiny. However, work on that front has continued and in the last month we had not only one but two releases (more on that below).

The work leading to the RLumShiny 0.2.7 release concentrated on adding three new apps and improving the internal infrastructure to import more file types.

The next release of Luminescence (which we expect in March) will bring some small but potentially breaking changes to users. This post is meant to give some advance warnings and provide solutions so that updating the package version will not cause excessive pain.

Another 3 months exact from our previous release, we are very proud to announce the release of version 1.1.2 of the Luminescence R package.

This release comes with a many (mostly rare) crashes being fixed, a number of cosmetic improvements to the plots, and a massive speed boost in the analyse_IRSAR.RF() function. Behind the scenes, during these past months we have introduced some improvements to our test infrastructure and continued our process of deprecation of redundant functions. In total we addressed 109 issues in 523 commits.

We have moved this website under our new subdomain at the Institute of Geography of the University of Heidelberg. From now you will find us at this URL:

https://replay.geog.uni-heidelberg.de/

The old links will continue to work.

Exactly 3 months from our previous release, we are excited to announce the release of version 1.1.1 of the Luminescence R package.

We were initially wondering whether this should be a minor or a major release, as we put a lot of effort in to make the package more solid and refined; we decided to call it a minor release just because there are not many new features in this version. However, there are some important regression fixes, many graphical improvements and also some performance speed-ups. In total we addressed 69 issues in 371 commits.

One of the challenges I faced as I started working on the Luminescence R package was how to navigate the very large set of functions that the package provides (by the last count, there are 155 functions that are exposed to the user, plus several internal helpers).

As I fumbled my way through it, I started noticing that when a function failed on a certain input, similar failures would also occur elsewhere. However, finding manually which other functions were affected was frustrating and time-consuming. Wouldn’t it be great if we could (quickly and with limited manual intervention) go through all the functions in the package and being told which are the ones that need to be fixed?

This got me to think about fuzz testing, and how that approach could be adapted for my purposes.