- author = "Yueke Zhang and Yu Huang",
- title = "Leveraging Fuzzy System to Reduce Uncertainty of Decision Making in Software Engineering Automation",
- booktitle = "GI @ GECCO 2022",
- year = "2022",
- editor = "Bobby R. Bruce and Vesna Nowack and Aymeric Blot and Emily Winter and W. B. Langdon and Justyna Petke",
- pages = "1948--1949",
- address = "Boston, USA",
- publisher_address = "New York, NY, USA",
- month = "9 " # jul,
- organisation = "SIGEVO",
- publisher = "Association for Computing Machinery",
- keywords = "genetic algorithms, genetic programming, genetic improvement, decision making, uncertainty, fuzzy systems, SBFL, spectrum-based fault localisation, FL, Ochiai, Ample, Zoltar, math Defect4j, Dempester-Shafer, DST, SE automation",
- isbn13 = "978-1-4503-9268-6/22/07",
-
URL = "
http://www.cs.ucl.ac.uk/staff/W.Langdon/gecco2022/gi2022/papers/Zhang_2022_GI.pdf",
-
DOI = "
doi:10.1145/3520304.3533991",
-
slides_url = "http://geneticimprovementofsoftware.com/slides/gi2022gecco/zhang-leveraging-fuzzy-system-gi-gecco-22.pdf",
-
video_url = "
https://www.youtube.com/watch?v=xwD_f_YOBn8&list=PLI8fiFpB7BoIHgl5CsdtjfWvHlE5N6pje&index=8",
- size = "2 pages",
- abstract = "Decision making in automated GI-based software engineering tasks can significantly affect the performance of the system. However, modern SE usually presents high uncertainty in such decision making process due to the existence of multiple solutions that reply on different heuristics. We propose to apply the theory of Fuzzy System to obtain a final decision with lower uncertainty and higher accuracy. We also demonstrate a motivating example and discuss the challenges and opportunities for applying fuzzy system to SE tasks.",
-
notes = "http://geneticimprovementofsoftware.com/events/gecco2022
GECCO-2022 A Recombination of the 31st International Conference on Genetic Algorithms (ICGA) and the 27th Annual Genetic Programming Conference (GP)",
