運用DCDC Model來遞增性分析高階程式之異常使用

Abstract

工作流程是由一組系統化組成的工作，經過特定的順序執行之後，能夠達成所要的目標或是產品。其中資料是實作和執行工作流程不可或缺的元素。然而工作流程可能會因為不適當的資料操作而產生預期外的結果，例如，遺失執行所需的資料或是收到多份同名資料產生衝突等等。因此在設計流程的過程中，資料分析結果便能提供相關的幫助。這篇論文提出了一個流程模組去描述一個Well-formed工作流程，這一名叫DCDC Model的模組顯示出四類的資料使用異常。因此我們提出了一些漸進式的演算法去偵測出這些資料使用異常，以輔助使用者在工作流程之編輯。

Workflow is a set of tasks which are systematized to achieve certain business goal(s), complete where each task is executed in a particular order under automatic control. Artifacts, collections of data items, are necessary for workflow implementation and support process execution. However, a workflow may yield unexpected results in execution due to improper artifact manipulation; e.g. activities miss artifact, or artifact conflict occurs at an activity in run time. Therefore, the analyses on artifact usage in design phase are very important. This thesis presents a process model, named DCDC model, to describe a well-formed workflow. There are four types of artifact usage anomalies in DCDC identified. To help the edit of a process, the corresponding incremental algorithms are presented to detect these anomalies. Their time complexities are also studied.