摘 要：随着信息技术的快速发展，数据库系统在各领域的应用日益广泛，数据完整性作为保障数据质量和系统可靠性的重要基础，已成为研究热点之一。本研究旨在探讨数据库中的数据完整性约束机制及其自动修复策略，以应对因人为操作失误、软件缺陷或外部干扰导致的数据异常问题。通过分析现有完整性约束模型的局限性，提出了一种基于规则推理与机器学习相结合的新型自动修复框架，该框架能够动态识别违反完整性约束的数据，并以较低的时间复杂度完成修复操作。实验结果表明，所提出的机制不仅显著提高了数据修复的准确率，还有效降低了人工干预的需求。本研究的主要贡献在于首次将智能化方法引入数据完整性修复领域，为构建更高效、可靠的数据库管理系统提供了新思路，同时为未来相关技术的发展奠定了理论与实践基础。
关键词：数据完整性；自动修复框架；规则推理
Abstract：With the rapid development of information technology, the application of database systems in various fields has become increasingly widespread. As a critical foundation for ensuring data quality and system reliability, data integrity has emerged as one of the key research focuses. This study aims to investigate data integrity constraint mechanisms in databases and their corresponding automatic repair strategies to address data anomalies caused by human operational errors, software defects, or external disturbances. By analyzing the limitations of existing integrity constraint models, this research proposes a novel automatic repair fr amework that combines rule-based reasoning with machine learning. The proposed fr amework is capable of dynamically identifying data that violates integrity constraints and performing repair operations with relatively low time complexity. Experimental results demonstrate that the mechanism not only significantly improves the accuracy of data repair but also effectively reduces the need for manual intervention. The primary contribution of this study lies in its pioneering introduction of intelligent methods into the field of data integrity repair, offering new insights for constructing more efficient and reliable database management systems. Additionally, it lays a theoretical and practical foundation for the future development of related technologies.
引言 1
一、数据完整性约束的基础理论 1
(一)数据完整性的定义与分类 1
(二)约束机制的作用与意义 2
(三)关键技术与实现方法 2
二、自动修复机制的设计原则 3
(一)修复目标的确定与评估 3
(二)自动化算法的选择与优化 3
(三)实时性与性能权衡分析 4
三、数据完整性约束与自动修复的协同机制 4
(一)约束检测与修复流程整合 4
(二)异常处理策略的设计与应用 5
(三)多场景下的适应性研究 5
四、实践案例与未来发展方向 6
(一)典型数据库系统的应用分析 6
(二)技术挑战与改进方向 6
(三)新兴技术对发展的潜在影响 7
结论 7
参考文献 9
致谢 9
关键词：数据完整性；自动修复框架；规则推理
Abstract：With the rapid development of information technology, the application of database systems in various fields has become increasingly widespread. As a critical foundation for ensuring data quality and system reliability, data integrity has emerged as one of the key research focuses. This study aims to investigate data integrity constraint mechanisms in databases and their corresponding automatic repair strategies to address data anomalies caused by human operational errors, software defects, or external disturbances. By analyzing the limitations of existing integrity constraint models, this research proposes a novel automatic repair fr amework that combines rule-based reasoning with machine learning. The proposed fr amework is capable of dynamically identifying data that violates integrity constraints and performing repair operations with relatively low time complexity. Experimental results demonstrate that the mechanism not only significantly improves the accuracy of data repair but also effectively reduces the need for manual intervention. The primary contribution of this study lies in its pioneering introduction of intelligent methods into the field of data integrity repair, offering new insights for constructing more efficient and reliable database management systems. Additionally, it lays a theoretical and practical foundation for the future development of related technologies.
Keywords: Data Integrity；Automatic Repair fr amework；Rule Reasoning
引言 1
一、数据完整性约束的基础理论 1
(一)数据完整性的定义与分类 1
(二)约束机制的作用与意义 2
(三)关键技术与实现方法 2
二、自动修复机制的设计原则 3
(一)修复目标的确定与评估 3
(二)自动化算法的选择与优化 3
(三)实时性与性能权衡分析 4
三、数据完整性约束与自动修复的协同机制 4
(一)约束检测与修复流程整合 4
(二)异常处理策略的设计与应用 5
(三)多场景下的适应性研究 5
四、实践案例与未来发展方向 6
(一)典型数据库系统的应用分析 6
(二)技术挑战与改进方向 6
(三)新兴技术对发展的潜在影响 7
结论 7
参考文献 9
致谢 9
