Then , this thesis analyzes the invertibilrty of transformation , and presents the formal definition of weak invertibte transformation , and calculates ( tuple - level ) derivation set of transformation by one - dimension merging and multi - dimension merging of the weak derivation set resolved by weak inverse attribute mapping 在此基础上，作者分析了转换的可逆性，给出了弱可逆转换的形式化定义，并通过对弱可逆转换中弱逆映射求解的弱起源集进行单维合并、多维合并来求解转换的(元组级)弱起源集。
Beginning with the formal definition of derivation set , this thesis finds the general laws of derivation set , proves the theorems about derivation set , proposes an approach for weak inversion and verification based on attribute mapping to trace data lineage , gives a series of arithmetic for data lineage tracing , describes the basic processes of data lineage , and then forms systematic theories and approach 作者从定义起源集入手，找出了起源集的一般规律，证明了有关起源集的定理，提出了一种“基于属性映射的弱逆与验证”的起源集跟踪方法，给出了一系列有关起源集跟踪的算法，并设计了数据志跟踪的基本过程，从而形成了一套系统的数据志跟踪理论与方法。
Upon the construction of weak derivation set , this thesis presents the concept of continuing traceability , and provides decision algorithm for the continuing traceability of a transformation sequence and tittering algorithm for the continuing traceable weak inverse attribute mapping . upon verifying weak derivation set , this thesis gives a series of verification algorithms based on the best property of attribute mapping or transformation 在构造弱起源集阶段，提出了可延续跟踪性的概念，给出了可延续跟踪性判别算法和可延续跟踪的弱逆映射的筛选算法；在验证弱起源集阶段，针对不同类型的转换和属性映射，给出了相应的验证算法。
