19 citations · 30 across the 8 of their papers we have counts for
10 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,…
Towards Continuous Experiment-driven MLOps
Keerthiga Rajenthiram, Milad Abdullah, Ilias Gerostathopoulos +5
Despite advancements in MLOps and AutoML, ML development still remains challenging for data scientists. First, there is poor support for and limited control over optimizing and evo…
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…
Towards characterization of edge-cloud continuum
Danylo Khalyeyev, Tomáš Bureš, Petr Hnětynka
Internet of Things and cloud computing are two technological paradigms that reached widespread adoption in recent years. These paradigms are complementary: IoT applications often r…
Towards fuzzification of adaptation rules in self-adaptive architectures
Tomáš Bureš, Petr Hnětynka, Martin Kruliš +5
In this paper, we focus on exploiting neural networks for the analysis and planning stage in self-adaptive architectures. The studied motivating cases in the paper involve existing…
Forming Ensembles at Runtime: A Machine Learning Approach
Tomáš Bureš, Ilias Gerostathopoulos, Petr Hnětynka +1
Smart system applications (SSAs) built on top of cyber-physical and socio-technical systems are increasingly composed of components that can work both autonomously and by cooperati…
Managing Latency in Edge-Cloud Environment
Lubomír Bulej, Tomáš Bureš, Adam Filandr +5
Modern Cyber-physical Systems (CPS) include applications like smart traffic, smart agriculture, smart power grid, etc. Commonly, these systems are distributed and composed of end-u…
Towards an Automated Requirements-driven Development of Smart Cyber-Physical Systems
Jiri Vinarek, Petr Hnetynka
The Invariant Refinement Method for Self Adaptation (IRM-SA) is a design method targeting development of smart Cyber-Physical Systems (sCPS). It allows for a systematic translation…