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Model driven architecture (MDA) concentrates on the use of models during software development. An approach using models as the central development artifact is more abstract, more compact and thus more effective and probably also less error…
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.…
Manually creating Planning Domain Definition Language (PDDL) descriptions is difficult, error-prone, and requires extensive expert knowledge. However, this knowledge is already embedded in engineering models and can be reused. Therefore,…
The notion of complex systems is common to many domains, from Biology to Economy, Computer Science, Physics, etc. Often, these systems are made of sets of entities moving in an evolving environment. One of their major characteristics is the…
Enterprise Integration Patterns (EIP) are a collection of widely used stencils for integrating enterprise applications and business processes. These patterns represent a "de-facto" standard reference for design decisions when integrating…
A number of companies are trying to migrate large monolithic software systems to Service Oriented Architectures. A common approach to do this is to first identify and describe desired services (i.e., create a model), and then to locate…
Engineering workflows such as design optimization, simulation-based diagnosis, control tuning, and model-based systems engineering (MBSE) are iterative, constraint-driven, and shaped by prior decisions. Yet many AI methods still treat these…
Software Repositories contain knowledge on how software engineering teams work, communicate, and collaborate. It can be used to develop a data-informed view of a team's development process, which in turn can be employed for process…
Computing systems are omnipresent; their sustainability has become crucial for our society. A key aspect of this sustainability is the ability of computing systems to cope with the continuous change they face, ranging from dynamic operating…
This work examines how AI, especially agentic systems, is being adopted in engineering and manufacturing workflows, what value it provides today, and what is needed for broader deployment. This is an exploratory and qualitative…
Uncertain, unpredictable, real time, and lifelong evolution causes operational failures in intelligent software systems, leading to significant damages, safety and security hazards, and tragedies. To fully unleash the potential of such…
Classical approaches like process algebras or labelled transition systems deal with static composition to model non-trivial concurrent or distributed systems; this is not sufficient for systems with dynamic architecture and with variable…
Agile development gets more appreciation from the market due to the flexible nature and more productivity. Among the Agile processes, Scrum gives better management of the processes, which are practiced in an organization. Though Scrum…
Deploying artificial intelligence (AI) models on edge devices involves a delicate balance between meeting stringent complexity constraints, such as limited memory and energy resources, and ensuring reliable performance in sensitive…
Providing an appropriate level of accessibility and traceability to data or process elements (so-called Items) in large volumes of data, often Cloud-resident, is an essential requirement in the Big Data era. Enterprise-wide data systems…
Companies implement different frameworks and best practices with the objective to improve the project management success rate and improve the business adaptability to the changing business environment. Project management framework (PRINCE2)…
The advent of IoT is a great opportunity to reinvigorate Computing by focusing on autonomous system design. This certainly raises technology questions but, more importantly, it requires building new foundation that will systematically…
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…
One of the strength of Virtual Organisations is their ability to dynamically and rapidly adapt in response to changing environmental conditions. Dynamic adaptability has been studied in other system areas as well and system management…
This paper takes a look at the general characteristics of business or economic intelligence system. The role of the user within this type of system is emphasized. We propose two models which we consider important in order to adapt this…