Paper Info
Title
Custom-Tailored Variability Mining for Block-Based Languages
Abstract
Block-based modeling languages, such as MATLAB/Simulink or state charts, reduce the complexity inherent to developing large-scale software systems. When creating variants for largely similar yet different software systems, the common practice is to copy models and modify them to different requirements. While this allows companies to save costs in the short-term, these so-called clone-and-own approaches cause problems regarding long-term evolution and system quality as the relation between the variants of the resulting software family is lost so that the variants have to be maintained in isolation. To recreate information regarding the variants' relations, variability mining identifies common and varying parts of cloned variants but, currently, the respective algorithms have to be created for each target language individually. In this paper, we present a generalized method to instantiate variability mining for arbitrary block-based modeling languages. The identified variability information allows developers to understand the variability of their grown software family. This knowledge helps efficiently maintaining the variants and allows migrating from clone-and-own approaches to more elaborate reuse strategies, such as software product lines. We demonstrate the feasibility of our method by instantiating variability mining techniques for two block-based languages.
Year
DOI
Venue
2016
10.1109/SANER.2016.13
2016 IEEE 23rd International Conference on Software Analysis, Evolution, and Reengineering (SANER)
Keywords
Field
DocType
variability mining,block-based language,conceptual framework,clone-and-own
Programming language,MATLAB,Reuse,Computer science,Modeling language,Software system,Software,Conceptual framework
Conference
Volume
Citations 
PageRank 
1
7
0.43
References 
Authors
32
4
Name
Order
Citations
PageRank
David Wille1223.98
Sandro Schulze225923.43
Christoph Seidl320720.15
Ina Schaefer4163499.16