Research Assistant


After working on Android application analysis during the SCG seminar and master’s thesis, I now continue to contribute within this field during my PhD research.

My interest includes large Android app collections that are mined for security issues. These issues are evaluated based on different feature sets and thus contain a valuable source for later software assessments.

Supervisors: Dr. Mohammad Ghafari, Prof. Dr. Oscar Nierstrasz

Project Proposals

Seminar

• Investigation of apps Android AIDL use
• Learning from nature: How nature resolves security issues
• Investigating password policies of web services
• Individual projects available on request

BSc

• Interactive visualizations for debugging
• Migration from insecure to secure API uses
• Individual projects available on request

MSc

• Improvement of Security Smell detections and evaluation on Android practitioners
• Predicting insecure code in answers of Q&A web sites
• Real time classification of, and adaptation to programmer tasks in IDEs
• Targeted attacks supported by recovered data structures of web API’s
• Individual projects available on request

Previous Proposals

• Seminar: Purpose of different programming languages in Android projects
• Seminar: Privacy concerns in public web APIs
• Seminar: Android Studio plug-in for code reviews

Contact

Publications

2019

1. Nitish Patkar, Pascal Gadient, Mohammad Ghafari, and Oscar Nierstrasz. Towards a Catalogue of Mobile Elicitation Techniques. In 25th International Conference on Requirements Engineering: Foundation for Software Quality (REFSQ), 2019. DOI PDF →

2018

1. Pascal Gadient, Mohammad Ghafari, Patrick Frischknecht, and Oscar Nierstrasz. Security Code Smells in Android ICC. In Empirical Software Engineering, 2018. DOI PDF →

2017

1. Pascal Gadient. Security in Android Applications. Masters thesis, University of Bern, August 2017. PDF →
2. Mohammad Ghafari, Pascal Gadient, and Oscar Nierstrasz. Security Smells in Android. In 17th IEEE International Working Conference on Source Code Analysis and Manipulation (SCAM), p. 121-130, September 2017. DOI PDF →