4 papers
Today's Cat Is Tomorrow's Dog: Accounting for Time-Based Changes in the Labels of ML Vulnerability Detection Approaches
Ranindya Paramitha, Yuan Feng, Fabio Massacci
Vulnerability datasets used for ML testing implicitly contain retrospective information. When tested on the field, one can only use the labels available at the time of training and…
Using ML filters to help automated vulnerability repairs: when it helps and when it doesn't
Maria Camporese, Fabio Massacci
[Context:] The acceptance of candidate patches in automated program repair has been typically based on testing oracles. Testing requires typically a costly process of building the…
A Systematic Literature Review on Automated Exploit and Security Test Generation
Quang-Cuong Bui, Emanuele Iannone, Maria Camporese +7
The exploit or the Proof of Concept of the vulnerability plays an important role in developing superior vulnerability repair techniques, as it can be used as an oracle to verify th…
Forecasting the risk of software choices: A model to foretell security vulnerabilities from library dependencies and source code evolution
Carlos E. Budde, Ranindya Paramitha, Fabio Massacci
Software security mainly studies vulnerability detection: is my code vulnerable today? This hinders risk estimation, so new approaches are emerging to forecast the occurrence of fu…