Semi-automatic identification of features in requirement specifications

Reuse of requirements leads to reduction in time spent for specification of new products. Variant management of requirement documents is an essential prerequisite in terms of a successful reuse of requirements. It supports the decisions if available requirements can be reused or not. One possibility to document the variability is feature modelling. One main challenge while introducing feature modelling in a grown environment is to extract product features from large natural language specifications. The current practice is a manual review of specifications conducted by domain experts. This procedure is very costly in terms of time. A promising approach to optimize feature identification is a semi-automatic identification of features in natural language specifications based on lexical analysis. This paper presents the current approaches used for handling variability in automotive specifications at Daimler passenger car development along with first experiences gained in using the optimized approach for feature identification using a lexical analysis.