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Companies dealing with Artificial Intelligence (AI) models in Autonomous Systems (AS) face several problems, such as users' lack of trust in adverse or unknown conditions, gaps between software engineering and AI model development, and…
As our lives, our businesses, and indeed our world economy become increasingly reliant on the secure operation of many interconnected software systems, the software engineering research community is faced with unprecedented research…
Self-adaptive systems (SASs) are capable of adjusting its behavior in response to meaningful changes in the operational con-text and itself. The adaptation needs to be performed automatically through self-managed reactions and…
The prevalence of software systems has become an integral part of modern-day living. Software usage has increased significantly, leading to its growth in both size and complexity. Consequently, software development is becoming a more…
In this extended abstract, we propose a novel research topic in the field of agentic AI, which we refer to as self-coding information systems. These systems will be able to dynamically adapt their structure or behavior by evaluating…
In the modern world, we are permanently using, leveraging, interacting with, and relying upon systems of ever higher sophistication, ranging from our cars, recommender systems in e-commerce, and networks when we go online, to integrated…
Over the years, research in system identification has provided a rich set of methods for learning dynamical models, together with well-established theoretical guarantees. In practice, however, the choice of model class, training algorithm,…
Architectural monitoring and adaptation allows self-management capabilities of autonomic systems to realize more powerful adaptation steps, which observe and adjust not only parameters but also the software architecture. However, monitoring…
Software systems are increasingly making decisions on behalf of humans, raising concerns about the fairness of such decisions. Such concerns are usually attributed to flaws in algorithmic design or biased data, but we argue that they are…
Context: Championed by IBM's vision of autonomic computing paper in 2003, the autonomic computing research field has seen increased research activity over the last 20 years. Several conferences and workshops have been established and have…
To accurately make adaptation decisions, a self-adaptive system needs precise means to analyze itself at runtime. To this end, runtime verification can be used in the feedback loop to check that the managed system satisfies its requirements…
Advanced systems such as IoT comprise many heterogeneous, interconnected, and autonomous entities operating in often highly dynamic environments. Due to their large scale and complexity, large volumes of monitoring data are generated and…
Autonomously detecting and recovering from faults is one approach for reducing the operational complexity and costs associated with managing computing environments. We present a novel methodology for autonomously generating investigation…
Runtime resource management for many-core systems is increasingly complex. The complexity can be due to diverse workload characteristics with conflicting demands, or limited shared resources such as memory bandwidth and power. Resource…
Robotic systems are complex and safety-critical software systems. As such, they need to be tested thoroughly. Unfortunately, robot software is intrinsically hard to test compared to traditional software, mainly since the software needs to…
Static code analysis is a powerful approach to detect quality deficiencies such as performance bottlenecks, safety violations or security vulnerabilities already during a software system's implementation. Yet, as current software systems…
Software is omnipresent within all factors of society. It is thus important to ensure that software are well tested to mitigate bad user experiences as well as the potential for severe financial and human losses. Software testing is however…
The increasing prevalence of security attacks on software-intensive systems calls for new, effective methods for detecting and responding to these attacks. As one promising approach, game theory provides analytical tools for modeling the…
Organizations rely heavily on time series metrics to measure and model key aspects of operational and business performance. The ability to reliably detect issues with these metrics is imperative to identifying early indicators of major…
Software systems impact society at different levels as they pervasively solve real-world problems. Modern software systems are often so sophisticated that their complexity exceeds the limits of human comprehension. These systems must…