TY - GEN
T1 - Towards privacy-aware software reuse
AU - Reinhartz-Berger, Iris
AU - Zamansky, Anna
AU - Koschmider, Agnes
N1 - Publisher Copyright: Copyright © 2019 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved
PY - 2019
Y1 - 2019
N2 - As software becomes more complex, reusing and integrating artifacts from existing projects that may be taken from open or organization-proprietary repositories is becoming an increasingly important practice. This practice requires an in-depth understanding of the projects to be reused and particularly their common and variable features and their non-functional requirements. Different approaches have been suggested to analyze similarity and variability of different kinds of artifacts (mainly, requirements and code), e.g., clone detection and feature mining. These approaches, however, mainly address functional aspects of the software artifacts, while mostly neglecting aspects dictated by non-functional requirements. The recent progress with the General Data Protection Regulation (GDPR) highlights the importance of handling privacy concerns in software development. However, existing approaches do not directly refer to privacy challenges in software reuse. In this paper we propose integrating these two lines of research and introduce a privacy-aware software reuse approach. Particularly, we suggest to extend VarMeR - Variability Mechanisms Recommender - which analyzes software similarity based on exhibited behaviors and recommends on polymorphism-inspired reuse mechanisms, with privacy awareness considerations. These considerations are reflected in “privacy levels” of the reused artifacts.
AB - As software becomes more complex, reusing and integrating artifacts from existing projects that may be taken from open or organization-proprietary repositories is becoming an increasingly important practice. This practice requires an in-depth understanding of the projects to be reused and particularly their common and variable features and their non-functional requirements. Different approaches have been suggested to analyze similarity and variability of different kinds of artifacts (mainly, requirements and code), e.g., clone detection and feature mining. These approaches, however, mainly address functional aspects of the software artifacts, while mostly neglecting aspects dictated by non-functional requirements. The recent progress with the General Data Protection Regulation (GDPR) highlights the importance of handling privacy concerns in software development. However, existing approaches do not directly refer to privacy challenges in software reuse. In this paper we propose integrating these two lines of research and introduce a privacy-aware software reuse approach. Particularly, we suggest to extend VarMeR - Variability Mechanisms Recommender - which analyzes software similarity based on exhibited behaviors and recommends on polymorphism-inspired reuse mechanisms, with privacy awareness considerations. These considerations are reflected in “privacy levels” of the reused artifacts.
KW - Compliance
KW - Privacy
KW - Reuse
KW - Variability Analysis
UR - http://www.scopus.com/inward/record.url?scp=85064591615&partnerID=8YFLogxK
U2 - 10.5220/0007566204500455
DO - 10.5220/0007566204500455
M3 - Conference contribution
T3 - MODELSWARD 2019 - Proceedings of the 7th International Conference on Model-Driven Engineering and Software Development
SP - 450
EP - 455
BT - MODELSWARD 2019 - Proceedings of the 7th International Conference on Model-Driven Engineering and Software Development
A2 - Hammoudi, Slimane
A2 - Pires, Luis Ferreira
A2 - Selic, Bran
T2 - 7th International Conference on Model-Driven Engineering and Software Development, MODELSWARD 2019
Y2 - 20 February 2019 through 22 February 2019
ER -