| Abstract | Software systems need to use cryptography to protect any sensitive data they collect. However, there are various classes of cryptographic components (e.g., ciphers, digests, etc.), each suitable for a specific purpose. Additionally, each class of such components comes with various algorithms and configurations. Finding the right combination of algorithms and correct settings to use is often difficult. We believe that using variability modeling to model these algorithms, their relationships, and restrictions can help non-experts navigate this complex domain. In this paper, we report on our experience modeling cryptographic components in Clafer, a modeling
language that combines feature modeling and metamodeling. We discuss design decisions we took as well as the challenges we ran into. Our work helps expand variability modeling into new domains and sheds lights on modeling requirements that appear in practice. |
|---|
