Non-functional requirements for machine learning
Khan Mohammad Habibullah, Gregory Gay, Jennifer Horkoff
Abstract
Systems that rely on Machine Learning (ML systems) have differing demands on quality---non-functional requirements (NFRs)---compared to traditional systems. NFRs for ML systems may differ in their definition, scope, and importance. Despite the importance of NFRs for ML systems, our understanding of their definitions and scope---and of the extent of existing research---is lacking compared to our understanding in traditional domains.
Topics & Concepts
Scope (computer science)Computer scienceNon-functional requirementQuality (philosophy)Artificial intelligenceRisk analysis (engineering)Machine learningSoftware systemSoftwareProgramming languageMedicineEpistemologySoftware constructionPhilosophySoftware Engineering ResearchSoftware Reliability and Analysis ResearchSoftware System Performance and Reliability