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ICST 2022
Mon 4 - Fri 8 April 2022
Wed 6 Apr 2022 12:15 - 12:30 at Margaret Hamilton - ICST Fuzzing and Random Testing Chair(s): Marcel Böhme

Adaptive random testing (ART) improves the failure-detection effectiveness of random testing by leveraging properties of the clustering of failure-causing inputs of most faulty programs: ART uses a sampling mechanism that evenly spreads test cases within a software’s input domain. The widely-used Fixed-Sized-Candidate-Set ART (FSCS-ART) sampling strategy faces a quadratic time cost, which worsens as the dimensionality of the software input domain increases. In this paper, we propose an approach based on small world graphs that can enhance the computational efficiency of FSCS-ART: SWFC-ART. To efficiently perform nearest neighbor queries for candidate test cases, SWFC-ART incrementally constructs a hierarchical navigable small world graph for previously executed, non-failure-causing test cases. Moreover, SWFC-ART has shown consistency in programs with high dimensional input domains. Our simulation and empirical studies show that SWFC-ART reduces the computational overhead of FSCS-ART from quadratic to log-linear order while maintaining the failure-detection effectiveness of FSCS-ART, and remaining consistent in high dimensional input domains. We recommend using SWFC-ART in practical software testing scenarios, where real-life programs often have high dimensional input domains and low failure rates.

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