Computer Science ›› 2021, Vol. 48 ›› Issue (7): 99-104.doi: 10.11896/jsjkx.200700125

Special Issue: Big Data & Data Scinece

• Database & Big Data & Data Science • Previous Articles     Next Articles

Dynamic Data Refining Strategy for Soundness Verification Based on WFT-net

TAO Xiao-yan, YAN Chun-gang, LIU Guan-jun   

  1. College of Computer Science and Technology,Tongji University,Shanghai 201804,China
    The Key Laboratory of the Ministry of Education for Embedded System and Service Computing,Tongji University,Shanghai 201804,China
  • Received:2020-07-20 Revised:2020-08-20 Online:2021-07-15 Published:2021-07-02
  • About author:TAO Xiao-yan,born in 1987,Ph.D.Her main research interests include model checking,service computing and business process management.(txyccl@163.com)
    YAN Chun-gang,born in 1963,postgraduate,Ph.D,professor,Ph.D supervisor.Her main research interests include computer collaboration and ser-vice computing,trusted computing and Petri net modeling and analysis.
  • Supported by:
    National Key Research and Development Program of China(2018YFB2100801).

Abstract: The workflow net with data tables (WFT-net) has been proposed to verify the soundness of business processes,to ensure the correctness of business logics and the satisfiability of data requirements.In some cases,the static data refining strategy may not reflect all possible execution situations of the business process,which can cause problems such as poor detection accuracy.To this end,a new dynamic data refining strategy is proposed in this paper.First,a method for evaluating the status of tables and predicates associated with the written data element in the current state of the WFT-net is given,to capture real-time changes in data-flow status,and to fully reflect all reachable states in process execution,so as to avoid the loss of the execution path.In addition,when the process execution is caught in a loop that will cause the data-flow status to be updated infinitely,the data assignment rules are appropriately adjusted to avoid the consequent infinite state.Then,the soundness of the business process is verified based on its all possible execution situations.At last,experimental results based on different business process instances show that the dynamic data refining strategy is able to improve the accuracy of soundness verification.

Key words: Data refinement, Data tables, Loop structure, Petri net, Soundness

CLC Number: 

  • TP306
[1]DUMAS M,LA ROSA M,MENDLING J,et al.Business process management [M].Berlin:Springer-Verlag,2013.
[2]DEHNERT J,ZIMMERMANN A.On the suitability of correctness criteria for business process models[C]//International Conference on Business Process Management.Springer,Berlin,Heidelberg,2005:386-391.
[3]VAN DER AALST W M P.Structural characterizations ofsound workflow nets [J].Computing science reports,1996,96(23):18-22.
[4]CLEMPNER J B.Classical workflow nets and workflow nets with reset arcs:using Lyapunov stability for soundness verification[J].Journal of Experimental & Theoretical Artificial Intelligence,2017,29(1):43-57.
[5]BI H H,ZHAO J L.Applying propositional logic to workflow verification [J].Information Technology and Management,2004,5(3/4):293-318.
[6]BARKAOUI K,BEN AYED R,SBAI Z.Workflow soundness verification based on structure theory of Petri nets [J].International Journal of Computing and Information Sciences,2007,5(1):51-61.
[7]COMBI C,OLIBONI B,WESKE M,et al.Conceptual modeling of inter-dependencies between processes and data[C]//Proceedings of the 33rd Annual ACM Symposium on Applied Computing.2018:110-119.
[8]TSOURY A,SOFFER P,REINHARTZ B I.Towards impactanalysis of data in business processes[M]//Enterprise,Business-Process and Information Systems Modeling.Springer,Cham,2016:125-140.
[9]SUN S X,ZHAO J L.Formal workflow design analytics using data flow modeling [J].Decision Support Systems,2013,55(1):270-283.
[10]AWAD A,DECKER G,LOHMANN N.Diagnosing and repairing data anomalies in process models[C]//International Conference on Business Process Management.Springer,Berlin,Heidelberg,2009:5-16.
[11]MEDA H S,SEN A K,BAGCHI A.Detecting data flow errors in workflows:A systematic graph traversal approach[C]//17th Annual Workshop on Information Technologies & Systems (WITS) Paper.2007.
[12]SIDOROVA N,STAHL C,TRČKA N.Soundness verification for conceptual workflow nets with data:Early detection of errors with the most precision possible [J].Information Systems,2011,36(7):1026-1043.
[13]BORREGO D,ESHUIS R,GÓMEZ-LÓPEZ M T,et al.Diagnosing correctness of semantic workflow models [J].Data & Knowledge Engineering,2013,87:167-184.
[14]DE LEONI M,FELLI P,MONTALI M.A holistic approach for soundness verification of decision-aware process models[C]//International Conference on Conceptual Modeling.Springer,Cham,2018:219-235.
[15]WANG Z X,WANG J M,ZHU X C,et al.Verification of workflow nets with transition conditions [J].Journal of Zhejiang University Science C,2012,13(7):483-509.
[16]TAO X Y,LIU G J,YANG B,et al.Workflow nets with tables and their soundness [J].IEEE Transactions on Industrial Informatics,2019,16(3):1503-1515.
[17]SMITH G,DERRICK J.Verifying data refinements using amodel checker [J].Formal Aspects of Computing,2006,18(3):264-287.
[1] LI Qing, LIU Wei, GUAN Meng-zhen, DU Yu-yue, SUN Hong-wei. Modeling and Analysis of Emergency Decision Making Based on Logical Probability GamePetri Net [J]. Computer Science, 2022, 49(4): 294-301.
[2] ZHOU Qin, LUO Fei, DING Wei-chao, GU Chun-hua, ZHENG Shuai. Double Speedy Q-Learning Based on Successive Over Relaxation [J]. Computer Science, 2022, 49(3): 239-245.
[3] LAI Xiang-wei, ZHENG Wan-bo, WU Yan-qing, XIA Yun-ni, RAN Qi-hua, DONG Yin-huan. Task Collaborative Process Network Model and Time Analysis of Mine Accident Emergency Rescue Digital Plan [J]. Computer Science, 2021, 48(6A): 596-602.
[4] NING Yu-hui, YAO Xi. Design and Implementation of Emergency Command System [J]. Computer Science, 2021, 48(6A): 613-618.
[5] WANG Wu-song, FANG Huan, ZHENG Xue-wen. Process Variants Merging Method Based on Group-fair Control Flow Structure [J]. Computer Science, 2021, 48(12): 170-180.
[6] YANG Hao-ran, FANG Xian-wen. Business Process Consistency Analysis of Petri Net Based on Probability and Time Factor [J]. Computer Science, 2020, 47(5): 59-63.
[7] LI Su-ting,ZHANG Yan. Axiomatizing Covariation-Contravariation Simulation Under GSOS Operators [J]. Computer Science, 2020, 47(1): 51-58.
[8] SUN Shu-ya, FANG Huan, FANG Xian-wen. Log-induced Morphological Fragments Process Clustering Method [J]. Computer Science, 2019, 46(8): 71-77.
[9] SONG Jian,FANG Xian-wen,WANG Li-li. Process Model Mining Method Based on Process Cut [J]. Computer Science, 2019, 46(7): 315-321.
[10] SU Qing,LIN Hao,HUANG Jian-feng,HE Fan,LIN Zhi-yi. Study on Dynamic-graph Watermarking Based on Petri Net Coding [J]. Computer Science, 2019, 46(7): 120-125.
[11] SONG Jian, FANG Xian-wen, WANG Li-li, LIU Xiang-wei. Method of Mining Hidden Transition of Business Process Based on Behavior Profiles [J]. Computer Science, 2019, 46(12): 334-340.
[12] CAO Rui, FANG Xian-wen, WANG Li-li. Method of Mining Conditional Infrequent Behavior Based on Communication Behavior Profile [J]. Computer Science, 2018, 45(8): 310-314.
[13] HE Lu-lu, FANG Huan. Change Propagation Method of Service-oriented Business Process Model with Data Flows Based on Petri Net [J]. Computer Science, 2018, 45(6A): 545-548.
[14] ZHAO Pei-hai, WANG Mi-mi. Consistency Detction Method of Models Based on Three-dimensional Behavior Relation Graph [J]. Computer Science, 2018, 45(6): 156-160.
[15] GAO Ya-nan, FANG Xian-wen and WANG Li-li. Optimized Analysis of Business Process Configuration Based on Petri Net Behavior Closeness [J]. Computer Science, 2017, 44(Z6): 539-542.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!