About
66
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Introduction
Luca Berardinelli is a PhD in Computer Science and a postdoctoral researcher at the WIN-SE department, JKU Linz. His current research activity concerns the integration of Model Driven Engineering, DevOps, and AI methodologies. He is participating to national and international funded project on these topics.
He was a post-doc at TU Wien, Austria, and University of L'Aquila, Italy as well as a Technical Lead at Braintribe Technology.
He received his Ms and PhD degrees in Computer Science from the University of L’Aquila, Italy.
His up to date research activities and publications can be found on his Google Scholar and LinkedIn profiles as well.
Current institution
Additional affiliations
April 2011 - March 2015
October 2010 - February 2015
Position
- Lecturer
Description
- UML Modeling and Profiling Labs Seminars for the Advanced Software Engineering class
Education
October 2007 - July 2011
September 2004 - April 2008
September 2001 - August 2004
Publications
Publications (66)
Digital twins are virtual representations of real-world entities or systems. Their primary goal is to help organizations understand and predict the behaviour and properties of these entities or systems. Additionally, digital twins enhance activities such as monitoring, verification, validation, and testing. However, the inherent complexity of digit...
Simulations have long been part of hardware-centric system domains. Similarly, architecture design is a common practice for complex industrial systems, which comprise many components that can be arranged in different layouts according to given requirements. Configuring simulation models and choosing the architecture design can be time-consuming act...
Technical systems are becoming increasingly complex due to the increasing number of components, functions, and involvement of different disciplines. In this regard, model-driven engineering techniques and practices tame complexity during the development process by using models as primary artifacts. Modeling can be carried out through domain-specifi...
Producing accurate software models is crucial in model-driven software engineering (MDE). However, modeling complex systems is an error-prone task that requires deep application domain knowledge. In the past decade, several automated techniques have been proposed to support academic and industrial practitioners by providing relevant modeling operat...
Designing modern Cyber-Physical Systems (CPSs) is posing new challenges to both industrial practitioners and academics. In this context, adopting cutting-edge paradigms, such as Model-Based Systems Engineering (MBSE), DevOps, and Artificial Intelligence (AI), can offer new opportunities for improving CPS design automation. While such paradigms are...
The paper presents the AIDOaRT project, a 3 years long H2020-ECSEL European project involving 32 organizations, grouped in clusters from 7 different countries, focusing on AI-augmented automation supporting modeling, coding, testing, monitoring, and continuous development in Cyber-Physical Systems (CPS). To this end, the project proposes to combine...
The advent of complex Cyber-Physical Systems (CPSs) creates the need for more efficient engineering processes. Recently, DevOps promoted the idea of considering a closer continuous integration between system development (including its design) and operational deployment. Despite their use being still currently limited, Artificial Intelligence (AI) t...
DevOps tools are often scattered over a multitude of technologies, and thus, their integration is a challenging endeavour.
The existing DevOps integration platforms, e.g., Keptn, often employ a family of languages for this purpose. However, as we have learnt from UML, SysML, and many others, a family of languages requires inter-model constraints t...
With JSON's increasing adoption, the need for structural constraints and validation capabilities led to JSON Schema, a dedicated meta-language to specify languages which are in turn used to validate JSON documents. Currently, the standardisation process of JSON Schema and the implementation of adequate tool support (e.g., validators and editors) ar...
With the emergence of Cyber-Physical Systems (CPS), the increasing complexity in development and operation demands for an efficient engineering process. In the recent years DevOps promotes closer continuous integration of system development and its operational deployment perspectives. In this context, the use of Artificial Intelligence (AI) is bene...
Context: Managing Non-Functional Requirements (NFRs) in software projects is challenging, and projects that adopt Model-Driven Development (MDD) are no exception. Although several methods and techniques have been proposed to face this challenge, there is still little evidence on how NFRs are handled in MDD by practitioners. Knowing more about the s...
Context awareness is a first-class attribute of today software systems. Indeed, many applications need to be aware of their context in order to adapt their structure and behavior for offering the best quality of service even in case the software and hardware resources are limited. Modeling the context, its evolution, and its influence on the servic...
CAEX is one of the most promising standards when it comes to data exchange between engineering tools in the production system automation domain. This is also reflected by the current emergence of AutomationML, which uses CAEX as its core representation language. However, with the increasing use of CAEX, important language engineering challenges ari...
Modern Cyber-Physical Systems (CPS) and Internet of Things (IoT) systems consist of both loosely and tightly interactions among various resources in IoT networks, edge servers and cloud data centers. These elements are being built atop virtualization layers and deployed in both edge and cloud infrastructures. They also deal with a lot of data throu...
Today’s crucial applications in, e.g., smart cities, logistics, health-care and manufacturing rely on complex Internet of Things (IoT) and cloud system infrastructures. Such infrastructures consist of IoT devices, distributed storage, processing, and management services that need to elastic, i.e., adaptable to evolving physical and execution enviro...
This presentation is about reporting experiences and challenges on combining model-driven engineering (MDE) methodologies with elastic execution models to design and test the uncertainty of real-world CPS.
Today’s cyber-physical systems (CPS) span IoT and cloud-based
datacenter infrastructures, which are highly heterogeneous with
various types of uncertainty. Thus, testing uncertainties in these
CPS is a challenging and multidisciplinary activity. We need several
tools for modeling, deployment, control, and analytics to test and
evaluate uncertaintie...
To engineer large, complex, and interdisciplinary systems, modeling is considered as the universal technique to understand and simplify reality through abstraction, and thus, models are in the center as the most important artifacts throughout interdisciplinary activities within model-driven engineering processes. Model-Driven Systems Engineering (M...
In multi-disciplinary engineering (MDE) projects, information models play an important role as inputs to and outputs of engineering processes. In MDE projects, engineers collaborate from various disciplines, such as mechanical, electrical, and software engineering. These disciplines use general-purpose and domain-specific models in their engineerin...
AutomationML is an emerging IEC standard for storing and exchang- ing engineering data among the heterogeneous software tools involved in the en- gineering of production systems. One important subset of such engineering data is the plant behavior. To make this data exchangeable, AutomationML uses the existing industry data format PLCopen XML. Howev...
Data exchange is a critical issue within the multidisciplinary engineering process of cyber physical production systems (CPPS). AutomationML (AML) is an emerging standard in the this field to represent and exchange artifacts between heterogeneous engineering tools used in different domains, such as mechanical, electrical, and software engineering....
AutomationML (AML) is an emerging standard in the automation domain to represent and exchange artifacts between heterogeneous engineering tools used in different disciplines, such as mechanical and electrical engineering. The Systems Modeling Language (SysML) is a modeling standard influenced by software modeling languages, such as UML, typically a...
AutomationML (Automation Markup Language) is a neutral data format based on XML for the storage and exchange of plant engineering information, which is provided as open standard. Goal of AutomationML is to interconnect the heterogeneous tool landscape of modern engineering tools in their different disciplines, e.g. mechanical plant engineering, ele...
System models are essential in planning, designing,
realizing, and maintaining production systems. AutomationML
(AML) is an emerging standard to represent and exchange
heterogeneous artifacts throughout the complete system life cycle
and is more and more used as a modeling language. AML is
designed as a flexible, prototype-based language able to re...
Wireless Sensor Networks (WSN) are nowadays applied to a wide set of domains (e.g., security, health). WSN are networks of spatially distributed, radio-communicating, battery-powered, autonomous sensor nodes. WSN are characterized by scarcity of resources, hence an application running on them should carefully manage its resources. The most critical...
Identifying performance problems is critical in the software design, mostly because the results of performance analysis (i.e., mean values, variances, and probability distributions) are difficult to be interpreted for providing feedback to software designers. Performance antipatterns support the interpretation of performance analysis results and he...
The growing request for high-quality applications for em-bedded systems demands model-driven approaches that facilitate their design as well as the verification and validation activities. In this paper we present MOSES, a model-driven performance analysis methodology based on Foundational UML (fUML). Implemented as an executable model library, MOSE...
The growing request for high-quality applications for wireless sensor network (wsn) demands model-driven approaches that facilitate the design and the early validation of extra-functional properties by combining design and analysis models. for this purpose, uml and several analysis-specific languages can be chosen and weaved through translational a...
Wireless Sensor Networks are becoming one of the most successful choices for the development and deployment of a wide range of applications, from intelligent homes to environment monitoring. In response to the growing demand for fast development of WSN applications, we extend an existing UML-based approach for the design and code generation of Agil...
For developing software systems it is crucial to consider non-functional properties already in an early development stage to guarantee that the system will satisfy its non-functional requirements. Following the model-based engineering paradigm facilitates an early analysis of non-functional properties of the system being developed based on the elab...
Supporting the execution of service-oriented applications over ubiquitous networks specifically calls for a service-oriented middleware (SOM), which effectively enables ubiquitous networking while benefiting from the diversity and richness of the networking infrastructure. However, developing ubiquitous applications that exploit the specific featur...
Model-driven software engineering not only enables the efficient development of software but also facilitates the analysis of non-functional properties (NFPs). As UML, the most adopted modeling language for designing software, lacks in formal execution semantics, current approaches translate UML models into dedicated analysis models, before NFPs ca...
In this chapter, we describe the most important network protocols supporting modern applications in mobile cellular networks, wireless sensor networks (WSN) and mobile ad hoc networks (MANETs). We first focus on the handover procedure in mobile cellular networks and the network failures due this procedure. The current solutions to enable seamless h...
Context is an application-specific set of heterogeneous data that a context-aware system should be capable to sense to accordingly adapt its behavior. Context evolution may affect the qualities of the functionalities provided by context-aware systems, in terms of variations of its non-functional properties. In this paper we propose a distributed to...
In this paper we briefly describe a case study, i.e. the Mobile eHealth (MeH), developed in the context of the IST PLASTIC project aimed at supporting self-adapting and context-aware services. The goal of the case study is to show how to model a service-based application and to demonstrate that model-based solutions are suitable to generate Quality...
In this paper, we report on our experience with the application of validated models to assess performance, reliability, and adaptability of a complex mission critical system that is being developed to dynamically monitor and control the position of an oil-drilling platform. We present real-time modeling results that show that all tasks are schedula...
Cognitive behavioral systems would definitely benefit from a supporting technology able to automatically recognize the context where humans operate, their gestures and even facial expressions. Such capability poses challenges for many researchers in various fields because the ultimate goal is to transfer to machines the human capability of represen...
In this paper, we report on our experience with the application of validated models to assess performance, reliability, and adaptability of a complex mission critical system that is being developed to dynamically monitor and control the position of an oil-drilling platform. We present real-time modeling results that show that all tasks are schedula...
In this paper, we report on our experience with the application of validated models to assess performance, reliability, and adaptability of a complex mission critical system that is being developed to dynamically monitor and control the position of an oil-drilling platform. We present real-time modeling results that show that all tasks are schedula...
The development of software for Wireless Sensor Networks (WSN) is mostly based on code-and-fix techniques. Up today model-driven engineering techniques have only been limitedly considered in this domain, although they would enable a set of activities aimed at improving the quality of software. In this paper we investigate the possibility to adapt a...
The limitation of hardware resources has brought to develop specific releases of software products for mobile devices that require limited amounts of resources. However, some resources are not only limited, but their available amounts can change during the device usage. Hence, more recently this characteristic has been tackled by providing to softw...
In this paper, we report on our experience with the application of validated models to assess performance, reliability, and adaptability of a complex mission critical system that is being developed to dynamically monitor and control the position of an oil-drilling platform. We present real-time modeling results that show that all tasks are schedula...
Software services, in the near future, will be deployed on mobile, resource-limited devices that communicate through heterogeneous B3G (Beyond 3rd Generation) networks. They shall adapt themselves according to context and requirement changes without degrading software-related QoS. Supporting the development and maintenance of such services involves...
Context-awareness is becoming a first class attribute of software systems. In fact, applications for mobile devices need to
be aware of their context in order to adapt their structure and behavior and offer the best quality of service even in case
the (software and hardware) resources are limited. Although performance is a key non-functional proper...
The modeling and validation of Non-Functional Properties (NFPs) is a crucial task for software systems to satisfy user expectations then for software projects to succeed. Nevertheless this research field still suffers the heterogene-ity of hermetic approaches aiming to the modeling and validation of one single non-functional property without sharin...
Modeling context-awareness is becoming a primary activity for software engineers that design applications for mobile devices. In fact, software applications running on such devices need to be aware of their context (that may rapidly change) to adapt their services and offer the best quality (intended as a combination of non-functional proper- ties)...
Software services in the near ubiquitous future will need to cope with variability, as they are deployed on an increasingly large diversity of computing platforms, operate in different execution environments, and communicate through Beyond 3G (B3G) networks. Heterogeneity of the underlying communication and computing infrastructure, physical mobili...
