摘要
软件可靠性作为衡量软件质量的核心指标之一，在现代信息化社会中具有重要意义，尤其是在关键任务系统和复杂技术领域中，其评估与保障技术的研究显得尤为迫切。本研究旨在针对当前软件可靠性评估方法存在的局限性以及保障技术的不足，提出一种基于多维度数据分析的综合评估框架，并结合机器学习算法优化预测模型，从而提升评估精度和保障效率。研究通过构建动态故障注入实验环境，模拟真实运行条件下的多种失效场景，验证了所提方法在不同复杂度软件系统中的适用性。结果表明，该框架能够显著提高软件可靠性的预测准确率，并有效降低后期维护成本。此外，本文创新性地引入了不确定性量化技术，用于分析和处理评估过程中的随机性和模糊性问题，为决策者提供了更为可靠的参考依据。主要贡献在于提出了一个灵活且可扩展的评估体系，同时为软件可靠性领域的理论发展和技术应用提供了新的思路和实践指导。
关键词：软件可靠性；多维度数据分析；机器学习；不确定性量化；动态故障注入
Abstract
Software reliability, as one of the core indicators for measuring software quality, plays a significant role in modern information society, particularly in critical mission systems and complex technical domains, where the research on its evaluation and assurance technologies becomes increasingly urgent. This study aims to address the limitations of current software reliability assessment methods and the inadequacies of assurance techniques by proposing an integrated evaluation fr amework based on multidimensional data analysis, which is further optimized through machine learning algorithms to enhance assessment accuracy and assurance efficiency. By constructing a dynamic fault-injection experimental environment to simulate various failure scenarios under real operational conditions, the applicability of the proposed method across software systems with different complexities has been validated. The results demonstrate that this fr amework can substantially improve the prediction accuracy of software reliability while effectively reducing maintenance costs in later stages. Additionally, this paper innovatively incorporates uncertainty quantification technology to analyze and handle stochasticity and fuzziness during the assessment process, thereby providing decision-makers with more reliable references. The primary contribution lies in the proposal of a flexible and extensible evaluation system, offering new insights and practical guidance for both the theoretical development and technical application in the field of software reliability.
Keywords：Software Reliability; Multi-dimensional Data Analysis; Machine Learning; Uncertainty Quantification; Dynamic Fault Injection
目 录
摘要 I
Abstract II
一、绪论 1
(一) 软件可靠性评估的研究背景与意义 1
(二) 国内外软件可靠性研究现状分析 1
(三) 本文研究方法与技术路线 1
二、软件可靠性评估模型研究 2
(一) 可靠性评估模型的理论基础 2
(二) 常见可靠性评估模型对比分析 2
(三) 新型可靠性评估模型的设计与验证 3
三、软件可靠性保障技术探索 4
(一) 软件测试在可靠性保障中的作用 4
(二) 静态分析技术对可靠性的支持 4
(三) 动态监测技术的应用与优化 5
四、软件可靠性综合评价体系构建 6
(一) 可靠性评价指标体系的设计原则 6
(二) 多维度可靠性评价方法研究 6
(三) 实际案例中评价体系的应用效果 7
结 论 8
参考文献 9
