@inproceedings{e72965b9c3904fbc8b639b73df9555d3,
title = "Summary of SWFC-ART: A Cost-effective Approach for Fixed-Size-Candidate-Set Adaptive Random Testing through Small World Graphs",
abstract = "This extended abstract presents an approach to enhance the Fixed-Sized-Candidate-Set Adaptive Random Testing (FSCS-ART) sampling strategy. SWFC-ART, the proposed approach, stores the previously-executed, non-failure-causing test cases into a Hierarchical Navigable Small World Graph (HNSWG) data structure and uses an efficient and consistent Nearest Neighbor Search (NNS) mechanism, especially for high-dimensional input domains. Our experiments show that SWFC-ART reduces the computational overhead of FSCS-ART from quadratic to log-linear order while retaining the failure-detection effectiveness of FSCS-ART.",
keywords = "Adaptive Random Testing, Efficiency, Hierarchical Navigable Small World Graphs, Random Testing, Software Testing",
author = "Muhammad Ashfaq and Rubing Huang and Dave Towey and Michael Omari and Dmitry Yashunin and Kudjo, {Patrick Kwaku} and Tao Zhang",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 15th IEEE International Conference on Software Testing, Verification and Validation, ICST 2022 ; Conference date: 04-04-2022 Through 13-04-2022",
year = "2022",
doi = "10.1109/ICST53961.2022.00053",
language = "English",
series = "Proceedings - 2022 IEEE 15th International Conference on Software Testing, Verification and Validation, ICST 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "460",
booktitle = "Proceedings - 2022 IEEE 15th International Conference on Software Testing, Verification and Validation, ICST 2022",
address = "United States",
}