Title
Feature modeling of two large-scale industrial software systems: Experiences and lessons learned
Abstract
Feature models are frequently used to capture the knowledge about configurable software systems and product lines. However, feature modeling of large-scale systems is challenging as many models are needed for diverse purposes. For instance, feature models can be used to reflect the perspectives of product management, technical solution architecture, or product configuration. Furthermore, models are required at different levels of granularity. Although numerous approaches and tools are available, it remains hard to define the purpose, scope, and granularity of feature models. In this paper we thus present experiences of developing feature models for two large-scale industrial automation software systems. Specifically, we extended an existing feature modeling tool to support models for different purposes and at multiple levels. We report results on the characteristics and modularity of the feature models, including metrics about model dependencies. We further discuss lessons learned during the modeling process.
Year
DOI
Venue
2015
10.1109/MODELS.2015.7338270
2015 ACM/IEEE 18th International Conference on Model Driven Engineering Languages and Systems (MODELS)
Keywords
Field
DocType
feature modeling,industrial software systems,experience report
Systems engineering,Feature-oriented domain analysis,Unified Modeling Language,Computer science,Solution architecture,Automation,Software system,Product management,Feature model,Modularity
Conference
Citations 
PageRank 
References 
6
0.44
33
Authors
4
Name
Order
Citations
PageRank
Daniela Lettner11527.25
Klaus Eder280.80
Paul Grünbacher32007118.84
Herbert Prähofer418917.00