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ICST 2022
Mon 4 - Fri 8 April 2022
Wed 6 Apr 2022 11:45 - 12:00 at Margaret Hamilton - ICST Fuzzing and Random Testing Chair(s): Marcel Böhme

—Most programs with command-line interface (CLI) have dozens of command-line options (e.g., -l, -F, -R for ls) to alternate the operation of the programs. Thus, depending on the option configurations (i.e., a list of options like -l -F and -F -R) applied during fuzzing, the test coverage and crash detection results can vary significantly. In this paper, we propose a novel fuzzing technique POWER that detects more crashes than the cutting-edge fuzzers by actively constructing and carefully selecting various program option configurations. The salient idea of POWER is to enforce diverse executions of a target program by selecting a set of the option configurations each of which is far “different/distant”from the others in the set. Another core idea of POWER is to apply different fuzzing strategies to different input domains (i.e., option configurations and input files) to increase testing effectiveness within limited time budget. The experiment results on the 30 real-world programs show that POWER detects significantly more crash bugs than the state-of-the-art fuzzing techniques.

Wed 6 Apr

Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

11:30 - 12:45
ICST Fuzzing and Random TestingResearch Papers / Journal-First Papers / Industry at Margaret Hamilton
Chair(s): Marcel Böhme MPI-SP, Germany and Monash University, Australia
Metamorphic Fuzzing of C++ Libraries
Research Papers
Andrei Lascu Imperial College London, Alastair F. Donaldson Imperial College London, Tobias Grosser University of Edinburgh, Torsten Hoefler ETH Zurich
POWER: Program Option-Aware Fuzzer for High Bug Detection Ability
Research Papers
Ahcheong Lee KAIST, Irfan Ariq KAIST, Yunho Kim Hanyang University, Moonzoo Kim KAIST / VPlusLab Inc.
Comparing Fuzzers on a Level Playing Field with FuzzBench
Dario Asprone University College London (UCL), Jonathan Metzman Google, Abhishek Arya Google, Giovani Guizzo University College London, Federica Sarro University College London
SWFC-ART: A cost-effective approach for Fixed-Size-Candidate-Set Adaptive Random Testing through small world graphs
Journal-First Papers
Muhammad Ashfaq Jiangsu University, Rubing Huang Macau University of Science and Technology (MUST), Dave Towey University of Nottingham Ningbo China, Michael Omari Takoradi Technical University, Dmitry Yashunin Harman X, Patrick Kwaku Kudjo University of Professional Studies, Accra-Ghana, Tao Zhang Macau University of Science and Technology (MUST)
Link to publication DOI
Live Q&A
Discussion and Q&A
Research Papers