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

Related publications (32)

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Modeling Mode-Dependent Lane Discipline in Hybrid Traffic

Nikolaos Geroliminis, Georgios Anagnostopoulos

Complex interactions can be observed in hybrid transportation systems, where cars share the same road space with other modes such as motorcycles, bicycles or even e-scooters. In this work we further built upon the concept of mode dependent lane discipline. ...

2024

Tension-tension fatigue behavior of basalt composite hybrid joints

Thomas Keller, Lulu Liu, Xin Wang

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

Mathieu Hursin, Yi Zhang

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, Yuqing Zhang, Jiayuan Zhang

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 ...

Berkeley2023

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

Arvin: Greybox Fuzzing Using Approximate Dynamic CFG Analysis

Mathias Josef Payer, Sirus Shahini

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

Modelling mode dependent lane discipline in hybrid traffic

Nikolaos Geroliminis, Georgios Anagnostopoulos

Time to collision (TTC) is a key indicator of human locomotion, encompassing both pedestrian and vehicular traffic. Applications of the TTC concept span a wide spectrum from safety to traffic flow dynamics. However, there exists no generic formulation for ...

2023

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

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 ...

National Academies2023

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 ...

Berkeley2023