SoftVarE Group
@softvare_uulm
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Working Group for Software Variability and Evolution led by Prof. @ThomasThuem at institute @sp_uulm at university @uni_ulm host of https://t.co/f0Dmhe80xc
Ulm, Germany
Joined December 2020
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
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Congratulations to the authors for winning the "Best Research Paper Award" at #SPLC24!
Sandra Greiner (@sandragreiner) presenting our foundational work on optimizing the accuracy of retroactive feature-tracing techniques with pinpointed proactive knowledge exploitation. Part of the @VariantSync project. Authors ⬇️
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Tobias Pett is presenting our work on improving the practicability of t-wise sampling by distinguishing between critical and non-critical and increasing t and coverage of the more critical features. Paper: https://t.co/CeX9waTMTh Extended Preprint: https://t.co/KIFNXDR3ni
#SPLC2024 Session Validation and Testing MulTi-Wise Sampling: Trading Uniform T-Wise Feature Interaction Coverage for Smaller Samples (Short Paper) by Tobias Pett, Sebastian Krieter, @ThomasThuem and @i_schaefer
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👉 @ChicoSundermann is pulling double duty today and presents our collection and inspection of knowledge compilation targets and their capabilities when applied in the analysis of feature models. (journal-first paper), authors ⬇️
#SPLC2024 Session Variability Analysis On the Benefits of Knowledge Compilation for Feature-Model Analyses (Journal First in Annals of Mathematics and Artificial Intelligence) by @ChicoSundermann, @ekuiter , @h3ssto, Heiko Raab, Sebastian Krieter and @ThomasThuem
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Tobias Heß (@h3ssto) presenting a novel deterministic variable ordering algorithm based on the detection of XOR groups and the scalability improvements it yields when compiling binary decision diagrams from real-world feature models. #SPLC24
#SPLC2024 Session Variability Analysis Towards Deterministic Compilation of Binary Decision Diagrams From Feature Models (Research Track) by @h3ssto, Sean Niklas Semmler, @ChicoSundermann, Jacobo Torán and @ThomasThuem
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The models are provided in their original format + UVL and DIMACS, together with information on their origins, structural, and empirical properties. We have also included tooling you may use to inspect and filter the models in order to create the benchmark of your dreams.
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👉 @ChicoSundermann presenting the result of hundreds of hours of work: A comprehensive collection of feature-model instances from research and industry with the goal of improving the validity and relevance of future empirical works in product-line research. #SPLC24 Authors ⬇️
#SPLC2024 Session Validation and Testing Collecting Feature Models from the Literature: A Comprehensive Dataset for Benchmarking (Research Track) by @ChicoSundermann, Vincenzo Francesco Brancaccio, @ekuiter, Sebastian Krieter, @h3ssto and @ThomasThuem
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Sandra Greiner (@sandragreiner) presenting our foundational work on optimizing the accuracy of retroactive feature-tracing techniques with pinpointed proactive knowledge exploitation. Part of the @VariantSync project. Authors ⬇️
#SPLC2024 Session Variability Implementation I Give an Inch and Take a Mile? Effects of Adding Reliable Knowledge to Heuristic Feature Tracing (Research Track) by @sandragreiner, @SchultheissAlex, @PaulMBittner , @ThomasThuem and @timokehrer
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Tobias Heß (@h3ssto) presenting our work on configuring feature-models in space and time. #RE_VOLUTION24 #SPLC24 Joint work with Simon Karrer, @lukas_osti Paper: https://t.co/ymcQpyj9UP Demo¹: https://t.co/Hbd2kNFi4L ¹: Limited demo, updates coming soon.
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And, of course, the Visual Studio LSP Plugin: https://t.co/SGlW2C4LaZ
github.com
Language server protocol for the Universal Variability Language (UVL) - Universal-Variability-Language/uvl-lsp
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And in case you are new to UVL altogether: UVL Page: https://t.co/dCm1EGENBF UVL Playground:
universal-variability-language.github.io
Community-driven language for specifying variability models
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If you want to play around with it, without the hazzle of downloading and building over Hotel WIFI, look at the pre-release of the generator:
github.com
This is the demo showcased at MODEVAR'24. To run: java -Djava.library.path=bin/ -jar uvlgenerator.jar demo.json
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We showcased our novel UVL Feature-Model Generator (with support for _all_ UVL language levels) at #SPLC24! Paper: https://t.co/pmbvxKhtpo Tool: https://t.co/LeupLGDwLf Authors: @ChicoSundermann, @h3ssto, Rahel Sundermann, @ekuiter, Sebastian Krieter, @ThomasThuem.
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We are super happy and grateful for receiving the @FSEconf best demo paper award at #FSE2024! Shout-out to my co-authors @SchultheissAlex , Benjamin Moosherr, Timo Kehrer, and @ThomasThuem ! Preprint:
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Interested in large scale empirical analyses of version histories in configurable software? Let's meet at 12:12 at @FSEconf tomorrow where I'll present our tool DiffDetective! #FSE2024 Check out our tool website here: https://t.co/ghlStltS9N
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In other news, our (w/ Simon Karrer, @lukas_osti) paper "Multi-Version Decision Propagation for Configuring Feature Models in Space and Time" was just accepted at Re:Volution @splcconf. #SPLC24 Abstract ⬇️
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The #GPCE24 deadlines have been extended to: Abstract Submission: June 11, 2024 Paper Submission: June 18, 2024 CfP: https://t.co/Jt91KDPl7H Please help to spread the news!
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Delighted to announce that a corner stone of my PhD research has been accepted into @splcconf. "Towards Deterministic Compilation of BDDs From Feature Models" Joint work w/ Sean Semmler, @ChicoSundermann, Jacobo Torán, @ThomasThuem Abstract ⬇️
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