ICSE 2024
Fri 12 - Sun 21 April 2024 Lisbon, Portugal
Thu 18 Apr 2024 11:00 - 11:15 at Fernando Pessoa - Fuzzing 1 Chair(s): Marcel Böhme

Parametric fuzzing combines evolutionary and generator-based fuzzing to create structured test inputs that exercise unique execution behaviors. Parametric fuzzers internally represent inputs as bit strings referred to as “parameter sequences”. Interesting parameter sequences are saved by the fuzzer and perturbed to create new inputs without the need for type-specific operators. However, existing work on parametric fuzzing only uses mutation operators, which modify a single input; it does not incorporate crossover, an evolutionary operator that blends multiple inputs together. Crossover operators aim to combine advantageous traits from multiple inputs. However, the nature of parametric fuzzing limits the effectiveness of traditional crossover operators. In this paper, we propose linked crossover, an approach for using dynamic execution information to identify and exchange analogous portions of parameter sequences. We created an implementation of linked crossover for Java and evaluated linked crossover’s ability to preserve advantageous traits. We also evaluated linked crossover’s impact on fuzzer performance on seven real-world Java projects and found that linked crossover consistently performed as well as or better than three state-of-the-art parametric fuzzers and two other forms of crossover on both long and short fuzzing campaigns.

Thu 18 Apr

Displayed time zone: Lisbon change

11:00 - 12:30
11:00
15m
Talk
Crossover in Parametric Fuzzing
Research Track
Katherine Hough Northeastern University, Jonathan Bell Northeastern University
Pre-print Media Attached
11:15
15m
Talk
SpecBCFuzz: Fuzzing LTL Solvers with Boundary Conditions
Research Track
Luiz Carvalho University of Luxembourg, Renzo Degiovanni Luxembourg Institute of Science and Technology, Maxime Cordy University of Luxembourg, Luxembourg, Nazareno Aguirre University of Rio Cuarto and CONICET, Yves Le Traon University of Luxembourg, Luxembourg, Mike Papadakis University of Luxembourg
11:30
15m
Talk
EDEFuzz: A Web API Fuzzer for Excessive Data ExposuresACM SIGSOFT Distinguished Paper Award
Research Track
Lianglu Pan University of Melbourne, Shaanan Cohney University of Melbourne, Toby Murray University of Melbourne, Thuan Pham The University of Melbourne
11:45
15m
Talk
ECFuzz: Effective Configuration Fuzzing for Large-Scale Systems
Research Track
Junqiang Li University of Electronic Science and Technology of China, Senyi Li University of Electronic Science and Technology of China, Keyao Li University of Electronic Science and Technology of China, Falin Luo University of Electronic Science and Technology of China, Hongfang Yu University of Electronic Science and Technology of China, Shanshan Li National University of Defense Technology, Xiang Li Academy of Military Sciences
DOI Media Attached File Attached
12:00
15m
Talk
Mind the Gap: What Working With Developers on Fuzz Tests Taught Us About Coverage Gaps
Software Engineering in Practice
Carolin Brandt Delft University of Technology, Marco Castelluccio Mozilla, Christian Holler Mozilla Corporation, Jason Kratzer Mozilla Corporation, Andy Zaidman Delft University of Technology, Alberto Bacchelli University of Zurich
DOI Pre-print
12:15
7m
Talk
CLFuzz: Vulnerability Detection of Cryptographic Algorithm Implementation via Semantic-Aware Fuzzing
Journal-first Papers
Yuanhang Zhou Tsinghua University, Fuchen Ma Tsinghua University, Yuanliang Chen Tsinghua University, Meng Ren Tsinghua University, Yu Jiang Tsinghua University
12:22
7m
Talk
FormatFuzzer: Effective Fuzzing of Binary File Formats
Journal-first Papers
Rafael Dutra CISPA Helmholtz Center for Information Security, Rahul Gopinath University of Sydney, Andreas Zeller CISPA Helmholtz Center for Information Security