研究数据表示如何影响计算结果，提出可追溯的决策记录系统。
On Decision-Valued Maps and Representational Dependence
- 定义决策值映射，记录不同数据表示对结果的影响
- 构建DecisionDB实现决策的精准回放与审计
- 适用于需要可解释性与可复现性的高可靠系统
同一数据的不同表示形式在相同计算引擎下可能产生不同的离散结果，部分表示保持原结果，部分则彻底改变。决策值映射记录每种表示是否保留原始结果，并将其与对应离散输出关联。本文形式化了决策值映射，并提出DecisionDB基础设施，通过内容生成的标识符与只写存储的产物，实现决策的记录、回放与审计。确定性回放能精确恢复每个记录的决策标识符，且三个识别字段均与持久化值一致。贡献在于将表示空间划分为保持区域与边界，并将决策重用视为可机械验证的条件。
原文摘要 · Abstract (English)
A computational engine applied to different representations of the same data can produce different discrete outcomes, with some representations preserving the result and others changing it entirely. A decision-valued map records which representations preserve the outcome and which change it, associating each member of a declared representation family with the discrete result it produces. This paper formalizes decision-valued maps and describes DecisionDB, an infrastructure that logs, replays and audits these relationships using identifiers computed from content and artifacts stored in write-once form. Deterministic replay recovers each recorded decision identifier exactly from stored artifacts, with all three identifying fields matching their persisted values. The contribution partitions representation space into persistence regions and boundaries, and treats decision reuse as a mechanically checkable condition.
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