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The inability to communicate effectively because of communication barriers severely restricts deaf and mute This paper highlights the challenges of generalizing models and dealing with contradictory evidence. Additionally, it explores the potential to enhance software failure prediction by integrating multiple research efforts. Traditional methods of failure prediction could not be highly task-specific due to the fact that not all tasks had access to the same data. To overcome these challenges and achieve better prediction accuracy, you can employ feature selection techniques, data resampling strategies, and machine learning processes. The project includes exploring the use of different datasets and enhancing model training to accelerate problem detection and ensure that solutions are compatible with different software configurations. Software quality assurance methods can be improved and made more adaptable as a direct result of the findings.
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Copyright © 2025, This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC-BY-NY-SA). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Corresponding Author: Subbalakshmamma Thaadi, ramaa4u.iitm@gmail.com
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Conflict of interest: The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s note: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
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