Related papers: Autonomic Model for Self-Configuring C#.NET Applic…
The performance of an algorithm often critically depends on its parameter configuration. While a variety of automated algorithm configuration methods have been proposed to relieve users from the tedious and error-prone task of manually…
Software systems are increasingly used in application domains characterised by uncertain environments, evolving requirements and unexpected failures; sudden system malfunctioning raises serious issues of security, safety, loss of comfort or…
When configuring customizable software, it is useful to provide interactive tool-support that ensures that the configuration does not breach given constraints. But, when is a configuration complete and how can the tool help the user to…
Many variability management techniques rely on sophisticated language extension or tools to support it. While this can provide dedicated syntax and operational mechanism but it struggling practical adaptation for the cost of adapting new…
Internet of Things (IoT) is a pivotal technology in application domains that require connectivity and interoperability between large numbers of devices. IoT systems predominantly use a software-defined network (SDN) architecture as their…
When designing new web applications, developers must cope with different kinds of constraints relative to the resources they rely on: software, hardware, network, online micro-services, or any combination of the mentioned entities.…
We introduce a method for Intrusion Detection based on the classification, understanding and prediction of behavioural deviance and potential threats, issuing recommendations, and acting to address eminent issues. Our work seeks a practical…
A reliable executable environment is the foundation for ensuring that large language models solve software engineering tasks. Due to the complex and tedious construction process, large-scale configuration is relatively inefficient. However,…
Customized processors are attractive solutions for vast domain-specific applications due to their high energy efficiency. However, designing a processor in traditional flows is time-consuming and expensive. To address this, researchers have…
When designing simulation models, it is favourable to reuse existing models as far as possible to reduce the effort from the first idea to simulation results. Thanks to the OMNeT++ community, there are several toolboxes available covering a…
This paper proposes a shift from compliance-centered web accessibility to a care-driven model that prioritizes user autonomy, using neurodivergent users as a catalyst case for broader personalization needs. While accessibility standards…
Most of current Software-as-a-Service (SaaS) applications are developed as customizable service-oriented applications that serve a large number of tenants (users) by one application instance. The current rapid evolution of SaaS applications…
With the advent of large language models, research in automated software engineering has increasingly focused on leveraging these models to achieve a deeper semantic understanding of code or to engineer sophisticated agent-based processes.…
Technologies for composition of loosely-coupled web services in a modular and flexible way are in high demand today. On the one hand, the services must be flexible enough to be reused in a variety of contexts. On the other hand, they must…
This article surveys Cognitive Edge Computing as a practical and methodical pathway for deploying reasoning-capable Large Language Models (LLMs) and autonomous AI agents on resource-constrained devices at the network edge. We present a…
Formal Methods are mathematically-based techniques for software design and engineering, which enable the unambiguous description of and reasoning about a system's behaviour. Autonomous systems use software to make decisions without human…
Deep Neural Networks (DNNs) are intensively used to solve a wide variety of complex problems. Although powerful, such systems require manual configuration and tuning. To this end, we view DNNs as configurable systems and propose an…
Autonomous driving systems are typically verified based on scenarios. To represent the positions and movements of cars in these scenarios, diagrams that utilize icons are typically employed. However, the interpretation of such diagrams is…
Automated Machine Learning (AutoML) is an important industrial solution for automatic discovery and deployment of the machine learning models. However, designing an integrated AutoML system faces four great challenges of configurability,…
We present a new method for scaling automatic configuration of computer networks. The key idea is to relax the computationally hard search problem of finding a configuration that satisfies a given specification into an approximate objective…