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Generative AI enables personalized computer science education at scale, yet questions remain about whether such personalization supports or undermines learning. This scoping review synthesizes 32 studies (2023-2025) purposively sampled from…
Microservice is a popular software architecture that relies on decentralized teams and clear service ownership to support modularity and scalability. However, in practice, developers frequently contribute across multiple services, creating…
Microservice applications are created as loosely coupled application components and they leverage cloud elasticity to reduce costs and increase development speed. However, microservice applications exhibit complex interactions among…
Satellites face a multitude of security risks that set them apart from hardware on Earth. Small satellites may face additional challenges, as they are often developed on a budget and by amateur organizations or universities that do not…
Microservices architectures are an integral part of modern software development. Their adoption brings significant changes to database management. Instead of relying on a single database, a microservices architecture is typically composed…
Machine Learning-as-a-Service (MLaaS) has become a widespread paradigm, making even the most complex machine learning models available for clients via e.g. a pay-per-query principle. This allows users to avoid time-consuming processes of…
Serverless technologies, also known as FaaS (Function as a Service), are promoted as solutions that provide dynamic scalability, speed of development, cost-per-consumption model, and the ability to focus on the code while taking attention…
Context. Despite the increasing adoption of Machine Learning Operations (MLOps), teams still encounter challenges in effectively applying this paradigm to their specific projects. While there is a large variety of available tools usable for…
Microservice Architecture (MSA) is an architectural style for service-based software systems. MSA puts a strong emphasis on high cohesion and loose coupling of the services that provide systems' functionalities. As a result of this,…
Background: Distributed data-intensive systems are increasingly designed to be only eventually consistent. Persistent data is no longer processed with serialized and transactional access, exposing applications to a range of potential…
The Microservices Architecture (MSA) design pattern has become a staple for modern applications, allowing functionalities to be divided across fine-grained microservices, fostering reusability, distribution, and interoperability. As…
Although the prevention of AI vulnerabilities is critical to preserve the safety and privacy of users and businesses, educational tools for robust AI are still underdeveloped worldwide. We present the design, implementation, and assessment…
This paper demonstrates the use of the Multi-Agent MicroServices (MAMS) architectural style through a case study based around the development of a prototype traffic simulation in which agents model a population of individuals who travel…
Machine learning models are increasingly being adopted across various fields, such as medicine, business, autonomous vehicles, and cybersecurity, to analyze vast amounts of data, detect patterns, and make predictions or recommendations. In…
Algorithm design is a vital skill developed in most undergraduate Computer Science (CS) programs, but few research studies focus on pedagogy related to algorithms coursework. To understand the work that has been done in the area, we present…
The study assesses the impact of cloud-based microservices architectures on application performance. Several aspects of performance evaluation are discussed, including response time, throughput, scalability, and reliability. This article…
Security bugs are errors in code that, when exploited, can lead to serious software vulnerabilities. These bugs could allow an attacker to take over an application and steal information. One of the ways to address this issue is by means of…
Motivated by developer productivity, serverless computing, and microservices have become the de facto development model in the cloud. Microservices decompose monolithic applications into separate functional units deployed individually. This…
Context: An increasing demand is observed in various domains to employ Machine Learning (ML) for solving complex problems. ML models are implemented as software components and deployed in Machine Learning Software Systems (MLSSs). Problem:…
Serverless computing has achieved widespread adoption, with over 70% of AWS organizations using serverless solutions [1]. Meanwhile, machine learning inference workloads increasingly migrate to Function-as-a-Service (FaaS) platforms for…