Fault Tree Analysis: Identifying Maximum Probability Minimal Cut Sets with MaxSAT

基于零样本学习和MaxSAT故障定位的反例引导程序修复

Counterexample Guided Program Repair Using Zero-Shot Learning and MaxSAT-based Fault Localization

针对入门编程作业自动化程序修复的局限，提出结合MaxSAT故障定位与大语言模型零样本学习的反例引导方法，提升修复能力且实现更小修复，优于现有工具。

用SAT和MaxSAT解决二维单尺寸库存切割问题

Solving the Two-dimensional single stock size Cutting Stock Problem with SAT and MaxSAT

本文提出基于SAT的框架，通过扩展物品类型并利用非重叠约束减少计算复杂度，采用三种方法优化库存切割，实验表明其在求解效率和最优性方面优于其他工具。

RBF-HS: Recursive Best-First Hitting Set Search

Various model-based diagnosis scenarios require the computation of most preferred fault explanations. Existing algorithms that are sound (i.e., output only actual fault explanations) and complete (i.e., can return all explanations), however, require exponential space to achieve this task. As a remedy, we propose two novel diagnostic search algorithms, called RBF-HS (Recursive Best-First Hitting Set Search) and HBF-HS (Hybrid Best-First Hitting Set Search), which build upon tried and tested techniques from the heuristic search domain. RBF-HS can enumerate an arbitrary predefined finite number o…

故障树中的实际因果关系

Actual causality in fault trees

基于Halpern & Pearl的实际因果关系理论，研究故障树在故障诊断中的应用，通过图结构和逻辑结构分类因果关系，并揭示最小割集如何产生实际原因。

模糊故障树的形式化

Fuzzy Fault Trees Formalized

本文为模糊故障树分析定义了严格的模糊不可靠性值框架，并提出一种基于α-截集方法的自底向上算法，高效计算系统模糊可靠性，保留非线性特征，并通过两个案例验证。

Causality and Temporal Dependencies in the Design of Fault Management Systems

Reasoning about causes and effects naturally arises in the engineering of safety-critical systems. A classical example is Fault Tree Analysis, a deductive technique used for system safety assessment, whereby an undesired state is reduced to the set of its immediate causes. The design of fault management systems also requires reasoning on causality relationships. In particular, a fail-operational system needs to ensure timely detection and identification of faults, i.e. recognize the occurrence of run-time faults through their observable effects on the system. Even more complex scenarios arise …