16 citations · 20 across the 3 of their papers we have counts for
8 papers
Program Repair
Xiang Gao, Yannic Noller, Abhik Roychoudhury
Automated program repair is an emerging technology which consists of a suite of techniques to automatically fix bugs or vulnerabilities in programs. In this paper, we present a com…
QFuzz: Quantitative Fuzzing for Side Channels
Yannic Noller, Saeid Tizpaz-Niari
Side channels pose a significant threat to the confidentiality of software systems. Such vulnerabilities are challenging to detect and evaluate because they arise from non-function…
NNrepair: Constraint-based Repair of Neural Network Classifiers
Muhammad Usman, Divya Gopinath, Youcheng Sun +2
We present NNrepair, a constraint-based technique for repairing neural network classifiers. The technique aims to fix the logic of the network at an intermediate layer or at the la…
NEUROSPF: A tool for the Symbolic Analysis of Neural Networks
Muhammad Usman, Yannic Noller, Corina Pasareanu +2
This paper presents NEUROSPF, a tool for the symbolic analysis of neural networks. Given a trained neural network model, the tool extracts the architecture and model parameters and…
Evolutionary Grammar-Based Fuzzing
Martin Eberlein, Yannic Noller, Thomas Vogel +1
A fuzzer provides randomly generated inputs to a targeted software to expose erroneous behavior. To efficiently detect defects, generated inputs should conform to the structure of…
DifFuzz: Differential Fuzzing for Side-Channel Analysis
Shirin Nilizadeh, Yannic Noller, Corina S. Pasareanu
Side-channel attacks allow an adversary to uncover secret program data by observing the behavior of a program with respect to a resource, such as execution time, consumed memory or…