Publications related to Discover deeper bugs with dynamic symbolic execution and coverage-based fuzz testing

Related publications (41)

Tension-tension fatigue behavior of basalt composite hybrid joints

The tension–tension fatigue behavior of pseudo-ductile hybrid bonded-bolted double lap basalt composite joints, composed of pseudo-ductile adhesives and adherends with multi-directional fiber architecture, was experimentally investigated. The fatigue damag ...

2024

To Infinity, and Beyond (Coverage)

Ahmad Hazimeh

The pursuit of software security and reliability hinges on the identification and elimination of software vulnerabilities, a challenge compounded by the vast and evolving complexity of modern systems. Fuzzing has emerged as an indispensable technique for b ...

EPFL2024

Enhancing higher education through hybrid and flipped learning: Experiences from the GRE@T-PIONEeR project

Yi Zhang, Mathieu Hursin

GRE@T-PIONEeR is a Horizon 2020 project coordinated by Chalmers University of Technology, running over the period 2020-2024. 18 university teachers from 8 different universities located in 6 different countries gathered forces to develop and offer advanced ...

Elsevier Science Sa2024

FISHFUZZ: Catch Deeper Bugs by Throwing Larger Nets

Mathias Josef Payer, Flavio Toffalini, Han Zheng

Fuzzers effectively explore programs to discover bugs. Greybox fuzzers mutate seed inputs and observe their execution. Whenever a seed reaches new behavior (e.g., new code or higher execution frequency), it is stored for further mutation. Greybox fuzzers d ...

Usenix Assoc2023

DatAFLow: Toward a Data-Flow-Guided Fuzzer

Mathias Josef Payer

Coverage-guided greybox fuzzers rely on control-flow coverage feedback to explore a target program and uncover bugs. Compared to control-flow coverage, data-flow coverage offers a more fine-grained approximation of program behavior. Data-flow coverage capt ...

2023

A Practical Wave Optics Reflection Model for Hair and Fur

Mengqi Xia

Traditional fiber scattering models, based on ray optics, are missing some important visual aspects of fiber appearance. Previous work [Xia et al. 2020] on wave scattering from ideal extrusions demonstrated that diffraction produces strong forward scatteri ...

2023

Arvin: Greybox Fuzzing Using Approximate Dynamic CFG Analysis

Mathias Josef Payer

Fuzzing has emerged as the most broadly used testing technique to discover bugs. Effective fuzzers rely on coverage to prioritize inputs that exercise new program areas. Edge-based code coverage of the Program Under Test (PUT) is the most commonly used cov ...

ASSOC COMPUTING MACHINERY2023

A hybrid microscopic model for multimodal traffic with empirical observations from aerial footage

Nikolaos Geroliminis, Georgios Anagnostopoulos

Microscopic traffic flow models can be distinguished in lane-based or lane-free depending on the degree of lane-discipline. This distinction holds true only if motorcycles are neglected in lane-based traffic. In cities, as opposed to highways, this is an o ...

2023

ACTOR: Action-Guided Kernel Fuzzing

Mathias Josef Payer

Fuzzing reliably and efficiently finds bugs in software, including operating system kernels. In general, higher code coverage leads to the discovery of more bugs. This is why most existing kernel fuzzers adopt strategies to generate a series of inputs that ...

Usenix Assoc2023

High-order accurate well-balanced energy stable adaptive moving mesh finite difference schemes for the shallow water equations with non-flat bottom topography

Junming Duan, Zhenying Zhang

This paper proposes high-order accurate well-balanced (WB) energy stable (ES) adaptive moving mesh finite difference schemes for the shallow water equations (SWEs) with non flat bottom topography. To enable the construction of the ES schemes on moving mesh ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2023

Machine-learning predictor of nerve fiber firing rate allows the automatic optimization of electrical stimulation protocols

Silvestro Micera, Simone Romeni, Gabriele Marino

Computational models have been widely employed to study the electrical stimulation of the nervous system. Still, most applications either study fundamental mechanisms underlying stimulation, or address qualitative scientific questions. When quantitative qu ...

IEEE2023

DatAFLow: Toward a Data-flow-guided Fuzzer

Mathias Josef Payer

This Replicating Computational Report (RCR) describes (a) our datAFLow fuzzer and (b) how to replicate the results in "datAFLow: Toward a Data-Flow-Guided Fuzzer." Our primary artifact is the datAFLow fuzzer. Unlike traditional coverage-guided greybox fuzz ...

2023

A Large-Scale Characterization of How Readers Browse Wikipedia

Robert West, Tiziano Piccardi, Akhil Arora

Despite the importance and pervasiveness of Wikipedia as one of the largest platforms for open knowledge, surprisingly little is known about how people navigate its content when seeking information. To bridge this gap, we present the first systematic large ...

ASSOC COMPUTING MACHINERY2023

Event-based sampled ECG morphology reconstruction through self-similarity

David Atienza Alonso, Giovanni Ansaloni, Tomas Teijeiro Campo, Silvio Zanoli

Background and Objective: Event-based analog-to-digital converters allow for sparse bio-signal acquisition, enabling local sub-Nyquist sampling frequency. However, aggressive event selection can cause the loss of important bio-markers, not recoverable with ...

2023

Thermal-hydraulic analysis of alternative cable-in-conduit conductors for the European DEMO hybrid central solenoid

Kamil Sedlák, Xabier Sarasola Martin, Roberto Guarino, Nikolay Bykovskiy

A hybrid design of the Central Solenoid is under study within the conceptual design phase of the European DEMO fusion reactor. It is based on HTS conductors in the innermost high-field layers, and Nb3Sn and NbTi conductors for field values below 15 T. Sinc ...

2022

Filter-Informed Spectral Graph Wavelet Networks for Multiscale Feature Extraction and Intelligent Fault Diagnosis

Olga Fink

Intelligent fault diagnosis has been increasingly improved with the evolution of deep learning (DL) approaches. Recently, the emerging graph neural networks (GNNs) have also been introduced in the field of fault diagnosis with the goal to make better use o ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Nonlinear Frequency Conversion in the Hybrid Si3N4 - LiNbO3 Integrated Platform

Tobias Kippenberg, Junqiu Liu, Rui Ning Wang, Mikhail Churaev, Viacheslav Snigirev, Terence Albert Emile Blésin

We demonstrate optical frequency comb generation in hybrid high-Q optical microresonators fabricated using direct wafer bonding of photonic Damascene silicon nitride wafer with thin-film lithium niobate-on-insulator (LNOI). The devices enable direct phase ...

IEEE2021

Nonlinear Frequency Conversion in the Hybrid Silicon Nitride - Lithium Niobate Integrated Platform

Tobias Kippenberg, Junqiu Liu, Rui Ning Wang, Mikhail Churaev, Viacheslav Snigirev, Terence Albert Emile Blésin

We demonstrate optical frequency comb generation in hybrid high-Q optical microresonators fabricated using direct wafer bonding of photonic Damascene silicon nitride wafer with thin-film lithium niobate-on-insulator (LNOI). The devices enable direct phase ...

IEEE2021

The COUGHVID crowdsourcing dataset: A corpus for the study of large-scale cough analysis algorithms

David Atienza Alonso, Tomas Teijeiro Campo, Lara Orlandic

Overview Cough audio signal classification has been successfully used to diagnose a variety of respiratory conditions, and there has been significant interest in leveraging Machine Learning (ML) to provide widespread COVID-19 screening. Th ...

Zenodo2021

New Methods for the Integrative Dynamic Modeling of Biomolecular Structures

Sylvain Träger

The true understanding of most cellular functions is only really achievable through the structural determination of their underlying macromolecular assemblies. However, their size, large number of individual components and metastable states make their eluc ...

EPFL2021