Problem: The goal of a software product line is to aid quick and quality delivery of software products, sharing common features. Effectively achieving the above-mentioned goals requires reuse analysis of the product line features. Existing requirements reuse analysis approaches are not focused on recommending product line features, that can be reused to realize new customer requirements.

Hypothesis: Given that the customer requirements are linked to product line features’ description satisfying them: then the customer requirements can be clustered based on patterns and similarities, preserving the historic reuse information. New customer requirements can be evaluated against existing customer requirements and reuse of product line features can be recommended.

Contributions: We treated the problem of feature reuse analysis as a text classification problem at the requirements-level. We use Natural Language Processing and clustering to recommend reuse of features based on similarities and historic reuse information. The recommendations can be used to realize new customer requirements.

Muhammad Abbas is a Researcher at RISE Research Institutes of Sweden and an Industrial PhD student at Mälardalen University. His research is focused on requirements engineering for variant intensive cyber-physical systems.