Agile Software Architecture in Advanced Data Analytics

Abstract

Requirements evolve over the development lifecycle of a software project. Agile practices are designed specifically to address this challenge while showing early and continuous progress towards project goals. Applying an agile approach allows stakeholders to adapt the scope and capabilities of a development release to changing market needs. More recently, an agile approach has been recommended for developing the architecture of software systems, enabling the design to support current requirements and early releases while evolving to meet future expectations. Our experience defining emergent software systems to build a product line architecture for advanced data analytics demonstrates the benefits that can be gained from prioritizing work activities and delaying architecture decisions. This paper proposes a process and ontology for agile architecture development. Only the necessary aspects for each evolutionary release are designed and prototyped, as determined by expectations of the identified application domain scenarios. Feedback from implementing the scenarios using the architecture extends our understanding of the requirements and provides the backlog for successive design iterations.