Abstract Recommender systems for requirements are typically built on the assumption that similar can be used as proxies to retrieve software. When a stakeholder proposes new requirement, natural language processing (NLP)-based similarity metrics exploited existing requirements, and in turn, identify previously developed code. Several NLP approaches computation between available. However, there ...