IDENTIFYING DEAD FEATURES AND THEIR CAUSES IN PRODUCT LINE MODELS: AN ONTOLOGICAL APPROACH
Feature Models (FMs) are a notation to represent differences and commonalities between products derived from a product line. However, product line modelers could unintentionally incorporate dead features in FMs. A dead feature is a type of defect, which implies that one or more features are not present in any product of the product line. Some authors have used ontologies in product lines, but they have not exploited ontology reasoning to identify and explain causes for defects in FMs in natural language. In this paper, we propose an ontology that represents FMs in OWL (Web Ontology Language). Then, we use SQWRL (Semantic Query-enhanced Web Rule Language) to identify dead features in a FM and identify and explain certain causes of this defect in natural language. Our preliminary empirical evaluation confirms the benefits of our approach.
Main Authors: | , , |
---|---|
Format: | Digital revista |
Language: | English |
Published: |
Universidad Nacional de Colombia
2014
|
Online Access: | http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0012-73532014000100008 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Summary: | Feature Models (FMs) are a notation to represent differences and commonalities between products derived from a product line. However, product line modelers could unintentionally incorporate dead features in FMs. A dead feature is a type of defect, which implies that one or more features are not present in any product of the product line. Some authors have used ontologies in product lines, but they have not exploited ontology reasoning to identify and explain causes for defects in FMs in natural language. In this paper, we propose an ontology that represents FMs in OWL (Web Ontology Language). Then, we use SQWRL (Semantic Query-enhanced Web Rule Language) to identify dead features in a FM and identify and explain certain causes of this defect in natural language. Our preliminary empirical evaluation confirms the benefits of our approach. |
---|