Related papers: Software Architecture for ML-based Systems: What E…
Engineers are deploying ML models as parts of real-world systems with the upsurge of AI technologies. Real-world environments challenge the deployment of such systems because these environments produce large amounts of heterogeneous data,…
Mining Software Repositories (MSR) has become an essential activity in software development. Mining architectural information to support architecting activities, such as architecture understanding, has received significant attention in…
Machine Learning (ML) techniques, such as Neural Network, are widely used in today's applications. However, there is still a big gap between the current ML systems and users' requirements. ML systems focus on improving the performance of…
Linear Software Models is a systematic effort to formulate a theory of software systems neatly based upon standard mathematics, viz. linear algebra. It has appeared in a series of papers dealing with various aspects of the theory. But one…
Advances in machine learning (ML) in recent years have enabled a dizzying array of applications such as data analytics, autonomous systems, and security diagnostics. ML is now pervasive---new systems and models are being deployed in every…
Models are used in both Software Engineering (SE) and Artificial Intelligence (AI). SE models may specify the architecture at different levels of abstraction and for addressing different concerns at various stages of the software…
The Mining Software Repositories (MSR) field focuses on analysing the rich data contained in software repositories to derive actionable insights into software processes and products. Mining repositories at scale requires techniques capable…
As complex software and systems development projects need models as an important planning, structuring and development technique, models now face issues resolved for software earlier: models need to be versioned, differences captured,…
Predictive models are one of the most important techniques that are widely applied in many areas of software engineering. There have been a large number of primary studies that apply predictive models and that present well-preformed studies…
Machine Learning is transitioning from an art and science into a technology available to every developer. In the near future, every application on every platform will incorporate trained models to encode data-based decisions that would be…
Large Language Models (LLMs) are rapidly becoming ubiquitous both as stand-alone tools and as components of current and future software systems. To enable usage of LLMs in the high-stake or safety-critical systems of 2030, they need to…
Recent technical advances has made machine learning (ML) a promising component to include in end user facing systems. However, user experience (UX) practitioners face challenges in relating ML to existing user-centered design processes and…
The purpose of this paper is to evaluate the impact of emerging network-centric software systems on the field of software architecture. We first develop an insight concerning the term "network-centric" by presenting its origin and its…
The growing use of large machine learning models highlights concerns about their increasing computational demands. While the energy consumption of their training phase has received attention, fewer works have considered the inference phase.…
Recently software development companies started to embrace Machine Learning (ML) techniques for introducing a series of advanced functionality in their products such as personalisation of the user experience, improved search, content…
Recent advancements in quantum computing (QC) and machine learning (ML) have fueled significant research efforts aimed at integrating these two transformative technologies. Quantum machine learning (QML), an emerging interdisciplinary…
The development and maintenance of cloud software is complicated by complex but crucial technological requirements that are tightly coupled with each other and with the softwares actual business functionality. Consequently, the complexity…
Modern software development methodologies include reuse of open source code. Reuse can be facilitated by architectural knowledge of the software, not necessarily provided in the documentation of open source software. The effort required to…
What is Software Architecture? The rules, paradigmen, pattern that help to construct, build and test a serious piece of software. It is the practical experience boiled down to abstract level. Software Architecture builds on System…
The aviation literature gives relatively little guidance to practitioners about the specifics of architecting systems for safety, particularly the impact of architecture on allocating safety requirements, or the relative ease of system…