A5065505519- Advanced Software Engineering Methodologies
- Software System Performance and Reliability
- Service-Oriented Architecture and Web Services
- Model-Driven Software Engineering Techniques
- Software Engineering Research
- Business Process Modeling and Analysis
- Software Reliability and Analysis Research
- Scientific Computing and Data Management
- Software Engineering Techniques and Practices
- Distributed systems and fault tolerance
- Distributed and Parallel Computing Systems
- Safety Systems Engineering in Autonomy
- Advanced Database Systems and Queries
- Simulation Techniques and Applications
- Cloud Computing and Resource Management
- Context-Aware Activity Recognition Systems
- Complex Systems and Decision Making
- Explainable Artificial Intelligence (XAI)
- Educational Games and Gamification
- Reinforcement Learning in Robotics
- Data Stream Mining Techniques
- Real-Time Systems Scheduling
- Evolutionary Algorithms and Applications
- Digital Games and Media
- AI in Service Interactions
Durham University
2021-2025
National Grid (United Kingdom)
2024
Los Alamitos Medical Center
2022
Aston University
2013-2021
Institut national de recherche en informatique et en automatique
2011-2020
Michigan State University
2019
Imperial College London
2019
Politecnico di Milano
2019
National Institute of Informatics
2019
University of California, Irvine
2019
Runtime adaptation mechanisms that leverage software models extend the applicability of model-driven engineering techniques to runtime environment. Contemporary mission-critical systems are often expected safely adapt changes in their execution Given critical roles these play, it is inconvenient take them offline functionality. Consequently, required, when feasible, behavior at with little or no human intervention. A promising approach managing complexity environments develop models,...
Self-adaptive systems have the capability to autonomously modify their behaviour at run-time in response changes environment. Self-adaptation is particularly necessary for applications that must run continuously, even under adverse conditions and changing requirements; sample domains include automotive systems, telecommunications, environmental monitoring systems. While a few techniques been developed support analysis of requirements adaptive limited attention has paid actual creation...
Requirements are sensitive to the context in which system-to-be must operate. Where such is well understood and static or evolves slowly, existing RE techniques can be made work well. Increasingly, however, development projects being challenged build systems operate contexts that volatile over short periods ways imperfectly understood. Such need able adapt new environmental dynamically, but contextual uncertainty demands this self-adaptive ability makes it hard formulate, validate manage...
Self-adaptation is emerging as an increasingly important capability for many applications, particularly those deployed in dynamically changing environments, such ecosystem monitoring and disaster management. One key challenge posed by adaptive systems (DASs) the need to handle changes requirements corresponding behavior of a DAS response varying environmental conditions. Berry et al. previously identified four levels RE that should be performed DAS. In this paper, we propose modeling reify...
Computational reflection is a well-established technique that gives program the ability to dynamically observe and possibly modify its behaviour. To date, however, mainly applied either software architecture or implementation. We know of no approach fully supports requirements reflection- is, making available as runtime objects. Although there body literature on monitoring, such work typically generates artefacts from so themselves are not directly accessible at runtime. In this paper, we...
More than a decade ago, the research topic models@run.time was coined. Since then, area has received increasing attention. Given prolific results during these years, current outcomes need to be sorted and classified. Furthermore, many gaps categorized in order further develop by experts of but also newcomers. Accordingly, paper discusses principles requirements state art line. To make discussion more concrete, taxonomy is defined used compare main approaches last including ancestor...
Dynamic software product lines extend the concept of conventional SPLs by enabling software-variant generation at runtime. Recent studies yield insights into current state DSPL field, research trends, and major gaps to address.
Engineering adaptive software is an increasingly complex task. Here, we demonstrate Genie, a tool that supports the modelling, generation, and operation of highly reconfigurable, component-based systems. We showcase how Genie used in two case-studies: i) development flood warning system, ii) service discovery application. In this context, adaptation enabled by Gridkit reflective middleware platform.
In earlier work we proposed the idea of requirements-aware systems that could introspect about extent to which their goals were being satisfied at runtime. When combined with requirements monitoring and self adaptive capabilities, awareness should help optimize goal satisfaction even in presence changing run-time context. this paper describe initial progress towards realization REAssuRE. REAssuRE focuses on explicit representation assumptions made design time. such are shown not hold, can...
Bayesian decision theory is increasingly applied to support decision-making processes under environmental variability and uncertainty. Researchers from application areas like psychology biomedicine have these techniques successfully. However, in the area of software engineering specifically self-adaptive systems (SASs), little progress has been made theory. We believe that based on Networks (BNs) are useful for dynamically adapt themselves at runtime a changing environment, which usually...
In the specific area of Software Engineering (SE) for self-adaptive systems (SASs) there is a growing research awareness about synergy between SE and Artificial Intelligence (AI). However, just few significant results have been published so far. this paper, we propose novel formal Bayesian definition surprise as basis quantitative analysis to measure degrees uncertainty deviations from normal behavior. A measures how observed data affects models or assumptions world during runtime. The key...