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pro vyhledávání: '"Sadam Ravichandra"'
The research on developing software defect prediction (SDP) models is targeted at reducing the workload on the tester and, thereby, the time spent on the targeted module. However, while a considerable amount of research has been done on developing pr
Externí odkaz:
http://arxiv.org/abs/2301.06303
You may develop a potential prediction model, but how can I trust your model that it will benefit my software?. Using a software defect prediction (SDP) model as a tool, we address this fundamental problem in machine learning research. This is a prel
Externí odkaz:
http://arxiv.org/abs/2301.05411
In a critical software system, the testers have to spend an enormous amount of time and effort to maintain the software due to the continuous occurrence of defects. Among such defects, some severe defects may adversely affect the software. To reduce
Externí odkaz:
http://arxiv.org/abs/2210.04665
Publikováno v:
2022
Context: Cross-project defect prediction (CPDP) models are being developed to optimize the testing resources. Objectives: Proposing an ensemble classification framework for CPDP as many existing models are lacking with better performances and analysi
Externí odkaz:
http://arxiv.org/abs/2209.14057
Publikováno v:
In Expert Systems With Applications 1 April 2024 239
Publikováno v:
In The Journal of Systems & Software January 2023 195
Publikováno v:
In Journal of King Saud University - Computer and Information Sciences November 2022 34(10) Part A:8675-8691
Akademický článek
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Akademický článek
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Publikováno v:
Peer-to-Peer Networking and Applications. 14:1650-1665
Continuous publication of statistics collected from various location-based applications may compromise users’ privacy as the statistics could be procured from users’ private data. Differential Privacy (DP) is a new privacy notion that offers a st