Content-based recommendation techniques for requirements engineering

Abstract

Assuring quality in software development processes is often a complex task. In many cases there are numerous needs which cannot be fulfilled with the limited resources given. Consequently it is crucial to identify the set of necessary requirements for a software project which needs to be complete and conflict-free. Additionally, the evolution of single requirements (artifacts) plays an important role because the quality of these artifacts has an impact on the overall quality of the project. To support stakeholders in mastering these tasks there is an increasing interest in AI techniques. In this paper we presents two content-based recommendation approaches that support the Requirements Engineering (RE) process. First, we propose a Keyword Recommender to increase requirements reuse. Second, we define a thesaurus enhanced Dependency Recommender to help stakeholders finding complete and conflict-free requirements. Finally, we present studies conducted at the Graz University of Technology to evaluate the applicability of the proposed recommendation technologies.