Aaron Molt

[Tobias Heß @h3ssto]

We were in contention for Best Paper!

[Tobias Heß @h3ssto]

In his second talk in the same (!) session, @AaronMolt presents our novel metric for comparing 2-wise samples: #pickme - this work is based on his Bachelor's thesis.

By the way, Aaron will be looking for a PhD position in 2026, so talk to him! #SPLC25

[Tobias Heß @h3ssto]

First talk of @AaronMolt at #SPLC25!
Aaron is presenting our work towards enabling efficient deterministic BDD compilation - this time around through eliminating atomic sets during preprocessing.

[Tobias Heß @h3ssto]

Aaand the extended version got accepted into #SPLC25 🎉

Title "Improving Deterministic BDD Compilation with Counting-Free Computation of Atomic Sets"

Joint work with @AaronMolt who will also present it at the conference.

Abstract ⤵️

[Tobias Heß @h3ssto]

Our work "Pick Me: Judging Sample Quality with Binary Decision Diagrams" has been accepted into @splcconf'25 🎉.

This work is based on the Bachelor's Thesis of my amazing student @AaronMolt (who will be looking for a PhD position soon 😉).

Details and preprint below ⬇️ #SPLC25

[Tobias Heß @h3ssto]

It has been more than 20 years since @sergio_segura2 proposed to exploit atomic sets for preprocessing feature models. Over the holidays, we came up with

"A Fast Counting-Free Algorithm for Computing Atomic Sets in Feature Models"

Paper: https://t.co/QlitK648pu
w/ @Aargon06