3 citations · 3 across the 5 of their papers we have counts for
5 papers
Vibe-Coding: Feedback-Based Automated Verification with no Human Code Inspection, a Feasibility Study
Michal Töpfer, František Plášil, Tomáš Bureš +1
Vibe coding inherently assumes iterative refinement of LLM-generated code through feedback loops. While effective for conventional software tasks, its reliability in runtime-adapti…
Feedback-based Automated Verification in Vibe Coding of CAS Adaptation Built on Constraint Logic
Michal Töpfer, František Plášil, Tomáš Bureš +1
In CAS adaptation, a challenge is to define the dynamic architecture of the system and changes in its behavior. Implementation-wise, this is projected into an adaptation mechanism,…
Tutoring LLM into a Better CUDA Optimizer
Matyáš Brabec, Jiří Klepl, Michal Töpfer +1
Recent leaps in large language models (LLMs) caused a revolution in programming tools (like GitHub Copilot) that can help with code generation, debugging, and even performance opti…
Ensemble-based modeling abstractions for modern self-optimizing systems
Michal Töpfer, Milad Abdullah, Tomáš Bureš +2
In this paper, we extend our ensemble-based component model DEECo with the capability to use machine-learning and optimization heuristics in establishing and reconfiguration of aut…
Online ML Self-adaptation in Face of Traps
Michal Töpfer, František Plášil, Tomáš Bureš +3
Online machine learning (ML) is often used in self-adaptive systems to strengthen the adaptation mechanism and improve the system utility. Despite such benefits, applying online ML…