Analyzing the Software Architecture of ML-based Covid-19 Detection System: Future Challenges and Opportunities

Abstract

  Two major study topics have emerged because of the challenges in software architecture and ML working together, as modern software systems produce a vast amount of data that is supported particularly by machine learning (ML), and artificial intelligence (AI) to produce useful insights. Software architecture for machine learning systems that primarily concerned with creating architectural methods for creating ML systems more effectively; ii) ML for Software architectures is concerned with creating ML methods for better-developing software systems. This study focuses on the ML-based software systems' architecture to highlight the many architectural methods currently in use. To more clearly identify a set of acceptable standards for designing ML-based software systems, we explore four crucial components of software architecture in this work that demand the focus of ML and software developers. These areas are based on an ML-based software system for addressing challenges in the COVID-19 detecting system.