发表机构
SDU University; United Arab Emirates University (UAEU)（SDU大学; 阿联酋大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对计算可追溯性缺失问题，提出基于 Java 的 CompProv 框架，在原子操作级别捕获代数溯源并生成自包含计算溯源图，经三个案例验证支持精确重放和敏感性分析，实现不泄露专有逻辑的数值完整性审计。
AI 中文摘要
科学研究和金融建模中计算结果的可信度越来越依赖于可验证的可追溯性，而不仅仅是对所报告输出的信任。现有的溯源系统在文件、数据集或流水线阶段的粒度上运行，未能记录连接算法输入与输出的内部代数变换序列；一个舍入误差、一次未记录的替换或一个缺失的中间值都可能传播到最终结果，且无法恢复其踪迹。本工作提出 CompProv，一个基于 Java 的、面向审计的溯源框架，通过将数值封装在高精度包装对象中，在单个代数操作的原子级别捕获谱系，生成可序列化的计算溯源图（CPG），该图作为自包含工件持久化，而非被丢弃的副产品。该框架通过三个异构案例研究进行评估：去中心化金融的 NAV 计算、在明确记录的输入假设下对计量学中干涉仪量块校准的重建，以及水文模型性能评估。确定性重放在全新环境中精确重现了每个结果，基于 CPG 的输入替换支持敏感性分析，而无需暴露底层源代码。这些结果表明，只要重放环境中存在 CompProv 运行时和包装类，CPG 即可在不披露专有业务逻辑的情况下审计数值完整性，并且其自包含结构支持在执行环境已弃用后的时间可审计性。该框架为可审计设计的计算系统建立了操作级基础，并将扩展到高吞吐量计算确定为未来工作的方向。
英文摘要
The reliability of computational results in scientific research and financial modeling increasingly depends on verifiable traceability, not merely on trust in a reported output. Existing provenance systems operate at the granularity of files, datasets, or pipeline stages, leaving the internal sequence of algebraic transformations connecting an algorithm's inputs to its outputs unrecorded; a rounding error, an undocumented substitution, or a missing intermediate value can propagate to a final result with no recoverable trace. This work presents CompProv, a Java-based, audit-oriented provenance framework that captures lineage at the atomic level of individual algebraic operations by encapsulating numerical values in high-precision wrapper objects, producing a serializable Calculation Provenance Graph (CPG) that persists as a self-contained artifact rather than a discarded byproduct. The framework is evaluated through three heterogeneous case studies: a decentralized-finance NAV calculation, a reconstruction of an interferometric gauge-block calibration in metrology under explicitly documented input assumptions, and a hydrological model performance evaluation. Deterministic replay reproduced each result exactly in a fresh environment, and CPG-based input substitution supported sensitivity analysis without exposing the underlying source code. These results indicate that, provided the CompProv runtime and wrapper classes are available in the replay environment, a CPG allows numerical integrity to be audited without disclosing proprietary business logic, and that its self-contained structure supports temporal auditability once an execution environment has become deprecated. This framework establishes an operation-level foundation for auditable-by-design computational systems, with scaling to high-throughput computing identified as a direction for future work.
