Paper Info
Title
CardyGAn: Tool Support for Cardinality-based Feature Models.
Abstract
Cardinality-based feature models (CFM) constitute a crucial and non-trivial extension to FODA feature models in terms of UML-like feature multiplicities and corresponding cardinality constraints. CFM allow for specifying configuration choices of software systems incorporating multiple instances (copies) of features, e.g., for tailoring customer-specific and even potentially unrestricted application resources. Nevertheless, the improved expressiveness of CFM compared to FODA feature models complicates configuration semantics, including sub-tree cloning and potentially unbounded configuration spaces. As a consequence, entirely novel anomalies might arise such as dead cardinality intervals, false unboundedness, and cardinality gaps, which are not properly treated by recent feature-modeling tools. In this paper, we present comprehensive tool support for assisting specification, validation, and configuration of CFM. Our tool CARDYGAN, therefore, incorporates capabilities for CFM editing, automated CFM validation including anomaly detection based on a combination of ILP and SMT solvers, as well as a CFM configuration engine based on ALLOY.
Year
DOI
Venue
2016
10.1145/2866614.2866619
TENTH INTERNATIONAL WORKSHOP ON VARIABILITY MODELLING OF SOFTWARE-INTENSIVE SYSTEMS (VAMOS 2016)
Keywords
Field
DocType
Extended Feature Models,Automated Validation
Anomaly detection,Data mining,Computer science,Cardinality,Software system,Semantics,Expressivity
Conference
Citations 
PageRank 
References 
4
0.38
17
Authors
5
Name
Order
Citations
PageRank
Thomas Schnabel190.77
Markus Weckesser2203.07
Roland Kluge3235.06
Malte Lochau454835.64
Andy Schürr52195230.25