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Robot person following (RPF) is a core capability in human-robot interaction, enabling robots to assist users in daily activities, collaborative work, and other service scenarios. However, achieving practical RPF remains challenging due to…
The increasing level of autonomy of robots poses challenges of trust and social acceptance, especially in human-robot interaction scenarios. This requires an interpretable implementation of robotic cognitive capabilities, possibly based on…
In this survey, we study how recent advances in machine intelligence are disrupting the world of business processes. Over the last decade, there has been steady progress towards the automation of business processes under the umbrella of…
The growing adoption of IT-systems for modeling and executing (business) processes or services has thrust the scientific investigation towards techniques and tools which support more complex forms of process analysis. Many of them, such as…
Modern software development and operations rely on monitoring to understand how systems behave in production. The data provided by application logs and runtime environment are essential to detect and diagnose undesired behavior and improve…
One major problem in maintaining a software system is to understand how many functional features in the system and how these features are implemented. In this paper a novel approach for locating features in code by semantic and dynamic…
The rapid advancement of Generative Artificial Intelligence (AI), such as Large Language Models (LLMs) and Multimodal Large Language Models (MLLM), has the potential to revolutionize the way we work and interact with digital systems across…
Novel end-user programming (EUP) tools enable on-the-fly (i.e., spontaneous, easy, and rapid) creation of interactions with robotic systems. These tools are expected to empower users in determining system behavior, although very little is…
Software system can include redundant implementation elements, such as, different methods that can produce indistinguishable results. This type of redundancy is called intrinsic if it is already available in the software, although not…
Software model checking constitutes an undecidable problem and, as such, even an ideal tool will in some cases fail to give a conclusive answer. In practice, software model checkers fail often and usually do not provide any information on…
Mistake analysis in procedural activities is a critical area of research with applications spanning industrial automation, physical rehabilitation, education and human-robot collaboration. This paper reviews vision-based methods for…
Runtime verification is checking whether a system execution satisfies or violates a given correctness property. A procedure that automatically, and typically on the fly, verifies conformance of the system's behavior to the specified…
Prescriptive Process Monitoring is a prominent problem in Process Mining, which consists in identifying a set of actions to be recommended with the goal of optimising a target measure of interest or Key Performance Indicator (KPI). One…
Recruitment in large organisations often involves interviewing a large number of candidates. The process is resource intensive and complex. Therefore, it is important to carry it out efficiently and effectively. Planning the selection…
Programs with dynamic allocation are able to create and use an unbounded number of fresh resources, such as references, objects, files, etc. We propose History-Register Automata (HRA), a new automata-theoretic formalism for modelling such…
This paper introduces an innovative Applicant Tracking System (ATS) enhanced by a novel Robotic process automation (RPA) framework or as further referred to as MLAR. Traditional recruitment processes often encounter bottlenecks in resume…
Training robust bimanual manipulation policies via imitation learning requires demonstration data with broad coverage over robot poses, contacts, and scene contexts. However, collecting diverse and precise real-world demonstrations is…
A robot as a coworker or a cohabitant is becoming mainstream day-by-day with the development of low-cost sophisticated hardware. However, an accompanying software stack that can aid the usability of the robotic hardware remains the…
Perhaps surprisingly, it is possible to predict how long an algorithm will take to run on a previously unseen input, using machine learning techniques to build a model of the algorithm's runtime as a function of problem-specific instance…
With the increasing sophistication of Advanced Persistent Threats (APTs), the demand for effective detection and mitigation strategies and methods has escalated. Program execution leaves traces in the system audit log, which can be analyzed…