Building Trust in AI -A Simplified Guide to Ensure Software Quality

Sahithi Devalla, Manas Kumar Yogix
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Abstract

In recent years, Artificial Intelligence (AI) has emerged as an innovative technology in a variety of areas, including software development. The demand for high-quality software has grown in tandem with the increasing complexity of applications and user expectations.AI-driven approaches are revolutionizing traditional software development methodologies by automating and augmenting various stages of the development life cycle, leading to improved efficiency, reduced costs, and enhanced software quality. This research explores the crucial role of AI in developing high-quality software and its impact on the software development process. Firstly, it discusses how AI technologies like machine learning, natural language processing, and deep learning can facilitate requirements gathering, analysis, and validation, leading to better understanding and refinement of user needs. Next, it delves into the significance of AI in automating the coding process, such as generating code snippets, fixing bugs, and optimizing performance, thus accelerating development and reducing human errors. Moreover, the paper highlights the pivotal role of AI in software testing and quality assurance. AI-powered testing tools can execute comprehensive tests more efficiently, detect defects, and predict potential software vulnerabilities, thereby enhancing the overall reliability and robustness of the software product. Additionally, AI techniques can enable real-time monitoring and analytics, allowing developers to identify and address issues promptly during the software's operational phase. Furthermore, the paper addresses the ethical considerations and challenges associated with AI in software development, including bias in training data, interpretability of AI-driven decisions, and potential job displacement for software developers.
在人工智能中建立信任——确保软件质量的简化指南
近年来,人工智能(AI)已经成为包括软件开发在内的各个领域的创新技术。随着应用程序的复杂性和用户期望的增加,对高质量软件的需求也随之增长。人工智能驱动的方法通过自动化和增加开发生命周期的各个阶段来彻底改变传统的软件开发方法,从而提高效率、降低成本和增强软件质量。本研究探讨了人工智能在开发高质量软件中的关键作用及其对软件开发过程的影响。首先,它讨论了机器学习、自然语言处理和深度学习等人工智能技术如何促进需求收集、分析和验证,从而更好地理解和细化用户需求。接下来,它深入研究了AI在自动化编码过程中的意义,例如生成代码片段,修复错误和优化性能,从而加速开发并减少人为错误。此外,本文还强调了人工智能在软件测试和质量保证中的关键作用。人工智能测试工具可以更高效地执行综合测试,检测缺陷,预测潜在的软件漏洞,从而提高软件产品的整体可靠性和鲁棒性。此外,人工智能技术可以实现实时监控和分析,使开发人员能够在软件运行阶段及时识别和解决问题。此外,本文还讨论了与软件开发中人工智能相关的伦理考虑和挑战,包括训练数据中的偏见、人工智能驱动决策的可解释性以及软件开发人员的潜在工作替代。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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