More Like this

1. Rethinking Trust in Forge-Based Git Security

   Yelgundhalli, Aditya Sirish; Zielinzki, Patrick; Curtmola, Reza; Cappos, Justin (February 2025, Network and Distributed System Security (NDSS) Symposium)
2. Towards adding verifiability to web-based Git repositories

   https://doi.org/10.3233/JCS-191371  

   Afzali, Hammad; Torres-Arias, Santiago; Curtmola, Reza; Cappos, Justin (April 2020, Journal of Computer Security)
3. A wall-crossing formula for Gromov–Witten invariants under variation of git quotient

   https://doi.org/10.1007/s00208-023-02622  

   González, Eduardo; Woodward, Chris T. (April 2024, Mathematische Annalen)
4. A Tool for Rejuvenating Feature Logging Levels via Git Histories and Degree of Interest

   https://doi.org/10.1109/ICSE-Companion55297.2022.9793736  

   Tang, Yiming; Spektor, Allan; Khatchadourian, Raffi; Bagherzadeh, Mehdi (May 2022, International Conference on Software Engineering: Companion Proceedings)

   Logging is a significant programming practice. Due to the highly transactional nature of modern software applications, massive amount of logs are generated every day, which may overwhelm developers. Logging information overload can be dangerous to software applications. Using log levels, developers can print the useful information while hiding the verbose logs during software runtime. As software evolves, the log levels of logging statements associated with the surrounding software feature implementation may also need to be altered. Maintaining log levels necessitates a significant amount of manual effort. In this paper, we demonstrate an automated approach that can rejuvenate feature log levels by matching the interest level of developers in the surrounding features. The approach is implemented as an open-source Eclipse plugin, using two external plug-ins (JGit and Mylyn). It was tested on 18 open-source Java projects consisting of ~3 million lines of code and ~4K log statements. Our tool successfully analyzes 99.22\% of logging statements, increases log level distributions by ~20\%, and increases the focus of logs in bug fix contexts ~83\% of the time. For further details, interested readers can watch our demonstration video (https://www.youtube.com/watch?v=qIULoAXoDv4). 

   more » « less
5. Authentic Learning on DevOps Security with Labware: Git Hooks To Facilitate Automated Security Static Analysis

   Rahman, M; Barek, M; Akter, M; Riad, ABM; Rahman, A; Shahriar, H; Rahman, A; Wu, F (July 2024, IEEE)