PROFUZZ: Directed Graybox Fuzzing via Module Selection and ...
Bibliographic Information
- Publication type: Proceedings Article
- Publication date: 2025-10-26
- Venue: ICCAD (IEEE/ACM International Conference on Computer-Aided Design), inferred from DOI prefix
10.1109/iccad66269.2025.11240782 - DOI: 10.1109/iccad66269.2025.11240782
- Source page: https://colab.ws/articles/10.1109%2Ficcad66269.2025.11240782
Overview
The article introduces PROFUZZ, a method in the directed graybox fuzzing (DGF) family that adds a module selection step to the fuzzing pipeline. DGF is a variant of coverage-guided fuzzing that biases input generation toward reaching a set of user-specified target program locations rather than maximizing overall code coverage.
The provided title is truncated in the available evidence, so the full subtitle and the exact module-selection mechanism are not recorded here. The venue (ICCAD) and the related concepts in the article's metadata indicate that PROFUZZ targets the CPU / microprocessor design domain, where fuzzing-based stimulus generation is used to construct test inputs that exercise targeted hardware modules.
Related Concepts
The article is associated with the following concepts in the evidence graph:
- CPU — the design under test or verification target.
- Microprocessor — closely related target class; CPU and microprocessor are commonly used together in hardware-verification contexts.
- Stimulus generation — the activity of producing test inputs (stimuli) for hardware designs; fuzzing is one such stimulus-generation technique.
Notes and Limitations
The available evidence is limited to bibliographic metadata (title fragment, publication type, and publication date) and to the related-concept graph. Detailed technical claims about PROFUZZ's module-selection algorithm, experimental results, and target benchmarks are not present in the supplied chunks and therefore are not asserted in this article.