Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Octavio Galland

dblp:408/8546 · DBLP profile ↗
← Back
1ranked-venue papers
1as first author
1since 2021 · last 2025
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Software engineering, system software, and programming languages
1 paper
Software testing · 100%
Network and information security
1 paper
Systems and software security · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Software testing › fuzzing
coverage-guided fuzzing
0.912025
Invivo Fuzzing by Amplifying Actual Executions · ICSE 2025
Software testing
fuzzing
0.912025
Invivo Fuzzing by Amplifying Actual Executions · ICSE 2025
Software testing › fuzzing
library fuzzing
0.912025
Invivo Fuzzing by Amplifying Actual Executions · ICSE 2025
Systems and software security
vulnerability discovery
0.312025
Invivo Fuzzing by Amplifying Actual Executions · ICSE 2025

Methods — techniques the papers use, named apart from their topics

dynamic analysis · 1.7
YearPublicationVenuePosition
2025 Invivo Fuzzing by Amplifying Actual Executions
abstract
A major bottleneck that remains when fuzzing software libraries is the need for fuzz drivers, i.e., the glue code between the fuzzer and the library. Despite years of fuzzing, critical security flaws are still found, e.g., by manual auditing, because the fuzz drivers do not cover the complex interactions between the library and the host programs using it. In this work we propose an alternative approach to library fuzzing, which leverages a valid execution context that is set up by a given program using the library (the host), and amplify its execution. More specifically, we execute the host until a designated function from a list of target functions has been reached, and then perform coverage-guided function-level fuzzing on it. Once the fuzzing quota is exhausted, we move on to fuzzing the next target from the list. In this way we not only reduce the amount of manual work needed by a developer to incorporate fuzzing into their workflow, but we also allow the fuzzer to explore parts of the library as they are used in real-world programs that may otherwise not have been tested due to the simplicity of most fuzz drivers.
Octavio Galland, Marcel Böhme
ICSE1