On identifying possible artificial intelligence applications in requirements engineering processes

Managing an ever-growing number of requirements is a time consuming and highly complex activity in product development projects. With the rise of Artificial Intelligence (AI) in the last decades, algorithms are now capable of supporting Requirements Engineering (RE) tasks. The algorithm's ability to intelligently process natural language data as well as the application in RE have been published extensively. In established RE processes however, it is often unclear, where AI algorithms can be utilized. The result is a significant imbalance between state-of-the-art AI algorithms and their application rates in real RE processes. One of the reasons is, that current models of RE processes aren't able to convey the needed information for the identification of suitable tasks. Therefore, this paper aims to provide a framework of finite and standardized process steps with a data processing-oriented perspective, that can be used to systematically identify the points in the RE processes where AI algorithms can be applied. With the standardized process steps of this framework, established RE processes can be abstracted and expressed in a way that is compatible with the scope of AI algorithms. Due to the finite number of standardized process steps, libraries of suitable AI algorithms for the defined process steps can be built, so that their applicability can be efficiently assessed. The presented framework was developed collaboratively during a research project with industry participation.