A Method to Improving Artifact Anomaly Detection in a Temporal Structured Workflow

Mahmoud M. Abouzeid, Pei Shu Huang, Feng Jian Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

During the design phase of a workflow process, detecting anomalous operations on artifacts is important for preventing errors and unexpected behaviors of the process dynamically. For temporal structured workflows (TSWs), which involve specifying the min and max execution time intervals for each activity, there are few studies on analyzing artifact anomalies compared to non-Temporal workflows. Additionally, the existing approaches designed for TSWs are inaccurate in detecting these anomalies either. To improve the analysis of TSWs, this paper presents an improved methodology based on an extended SP-Tree structure, called TSP-Tree. Our approach involves two steps: first, transforming a TSW into a TSP-Tree, and then applying several algorithms to TSP-Tree to detect artifact anomalies.

Original languageEnglish
Title of host publicationProceedings - 2023 IEEE International Conference on Software Services Engineering, SSE 2023
EditorsClaudio Ardagna, Nimanthi Atukorala, Carl K. Chang, Rong N. Chang, Jing Fan, Geoffrey Fox, Sumi Helal, Zhi Jin, Qinghua Lu, Tiberiu Seceleanu, Stephen S. Yau
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages242-250
Number of pages9
ISBN (Electronic)9798350340754
DOIs
StatePublished - 2023
Event2023 IEEE International Conference on Software Services Engineering, SSE 2023 - Hybrid, Chicago, United States
Duration: 2 Jul 20238 Jul 2023

Publication series

NameProceedings - 2023 IEEE International Conference on Software Services Engineering, SSE 2023

Conference

Conference2023 IEEE International Conference on Software Services Engineering, SSE 2023
Country/TerritoryUnited States
CityHybrid, Chicago
Period2/07/238/07/23

Keywords

  • artifact anomalies
  • temporal artifact anomaly detection
  • temporal structured workflow

Fingerprint

Dive into the research topics of 'A Method to Improving Artifact Anomaly Detection in a Temporal Structured Workflow'. Together they form a unique fingerprint.

Cite this