Technical debt is a well-known challenge in software development, and its negative impact on software quality, maintainability, and performance is widely recognized. In recent years, artificial intelligence (AI) has proven to be a promising approach to assist in managing technical debt. This paper presents a comprehensive literature review of existing research on the use of AI powered tools for technical debt avoidance in software development. In this literature review we analyzed 15 related research papers which covers various AI-powered techniques, such as code analysis and review, automated testing, code refactoring, predictive maintenance, code generation, and code documentation, and explores their effectiveness in addressing technical debt. The review also discusses the benefits and challenges of using AI for technical debt management, provides insights into the current state of research, and highlights gaps and opportunities for future research. The findings of this review suggest that AI has the potential to significantly improve technical debt management in software development, and that existing research provides valuable insights into how AI can be leveraged to address technical debt effectively and efficiently. However, the review also highlights several challenges and limitations of current approaches, such as the need for high-quality data and ethical considerations and underscores the importance of further research to address these issues. The paper provides a comprehensive overview of the current state of research on AI for technical debt avoidance and offers practical guidance for software development teams seeking to leverage AI in their development processes to mitigate technical debt effectively

翻译：技术债务是软件开发中一个广为人知的挑战，其对软件质量、可维护性和性能的负面影响已得到广泛认可。近年来，人工智能（AI）已被证明是一种辅助管理技术债务的很有前景的方法。本文对现有关于在软件开发中使用AI驱动工具避免技术债务的研究进行了全面文献综述。在本综述中，我们分析了15篇相关研究论文，涵盖了各种AI驱动技术，如代码分析与审查、自动化测试、代码重构、预测性维护、代码生成和代码文档，并探讨了它们在解决技术债务方面的有效性。本综述还讨论了使用AI管理技术债务的优势和挑战，提供了对当前研究状态的见解，并指出了未来研究的空白和机会。本综述的发现表明，AI有潜力显著改善软件开发中的技术债务管理，且现有研究为如何有效且高效地利用AI解决技术债务提供了宝贵见解。然而，本综述也强调了当前方法的若干挑战和局限性，例如对高质量数据的需求以及伦理考量，并强调了进一步研究以解决这些问题的重要性。本文全面概述了AI用于避免技术债务的研究现状，并为寻求在其开发过程中利用AI有效减轻技术债务的软件开发团队提供了实践指导。