Extracting software product line feature models from natural language specifications

Abstract

The specification of a family of software products may include documents written in natural language. Automatically extracting knowledge from these documents is a challenging problem that requires using Natural Language Processing (NLP) techniques. This knowledge can be formalized as a Feature Model (FM), a diagram capturing the key features and the relationships among them. In this paper, we first review previous works that have presented tools for extracting FMs from textual specifications and compare their strengths and limitations. Then, we propose a framework for feature and relationship extraction, which overcomes the identified limitations and is built upon state-of-the-art open-source NLP tools. This framework is evaluated against previous works using several case studies, showing improved results.