Towards Privacy-aware Software Reuse

Iris Reinhartz-Berger, Anna Zamansky, Agnes Koschmider

2019

Abstract

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.

Paper Citation

in Harvard Style

Reinhartz-Berger I., Zamansky A. and Koschmider A. (2019). Towards Privacy-aware Software Reuse.In Proceedings of the 7th International Conference on Model-Driven Engineering and Software Development - Volume 1: MODELSWARD, ISBN 978-989-758-358-2, pages 450-455. DOI: 10.5220/0007566204500455

in Bibtex Style

@conference{modelsward19,
author={Iris Reinhartz-Berger and Anna Zamansky and Agnes Koschmider},
title={Towards Privacy-aware Software Reuse},
booktitle={Proceedings of the 7th International Conference on Model-Driven Engineering and Software Development - Volume 1: MODELSWARD,},
year={2019},
pages={450-455},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007566204500455},
isbn={978-989-758-358-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 7th International Conference on Model-Driven Engineering and Software Development - Volume 1: MODELSWARD,
TI - Towards Privacy-aware Software Reuse
SN - 978-989-758-358-2
AU - Reinhartz-Berger I.
AU - Zamansky A.
AU - Koschmider A.
PY - 2019
SP - 450
EP - 455
DO - 10.5220/0007566204500455