@inproceedings{54e3c72b8a674a8c9271012354bcf03c,
title = "Extended Abstract of Candidate Test Set Reduction for Adaptive Random Testing: An Overheads Reduction Technique",
abstract = "This document 1 is an extended abstract of a Science of Computer Programming paper, {"}Candidate Test Set Reduction for Adaptive Random Testing: An Overheads Reduction Technique,{"}presented as a J1C2 (Journal publication first, Conference presentation following) at the 30th IEEE International Conference on Software Analysis, Evolution and Reengineering (Saner 2023).The paper presents a candidate set reduction strategy to enhance the Fixed-Sized-Candidate-Set version of Adaptive Random Testing (FSCS-ART). The proposed method reduces the number of randomly-generated candidate test cases by retaining valuable, unused candidates from previous iterations. As the computational costs associated with a stored/retained candidate are less than the costs associated with a randomly-generating one, the overall computational overheads of FSCS-ART are reduced. The reported experimental studies show that the proposed method has a comparable failure-detection effectiveness to FSCS-ART, but less computational overheads.",
keywords = "Adaptive Random Testing, FSCS-ART, Random Testing, Software Testing, Test Set Reduction",
author = "Rubing Huang and Haibo Chen and Weifeng Sun and Dave Towey",
note = "Funding Information: ACKNOWLEDGMENT This work is supported the Macau Science and Technology Development Fund, Macau SAR, under Grant 0046/2021/A, and the Faculty Research Grants (FRG) of Macau University of Science and Technology, under Grant FRG-22-103-FIE. This work is also in part supported by the National Natural Science Foundation of China under Grants 61872167 and 61502205, and in part by the Science and Technology Program of the Ministry of Housing and Urban-Rural Development of China under Grant 2020-S-001. Publisher Copyright: {\textcopyright} 2023 IEEE.; 30th IEEE International Conference on Software Analysis, Evolution and Reengineering, SANER 2023 ; Conference date: 21-03-2023 Through 24-03-2023",
year = "2023",
doi = "10.1109/SANER56733.2023.00102",
language = "English",
series = "Proceedings - 2023 IEEE International Conference on Software Analysis, Evolution and Reengineering, SANER 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "853--854",
editor = "Tao Zhang and Xin Xia and Nicole Novielli",
booktitle = "Proceedings - 2023 IEEE International Conference on Software Analysis, Evolution and Reengineering, SANER 2023",
address = "United States",
}