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Methods of Detection and Resolution of Anomalies in Business Rule: Comparative Study

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 129 - Number 10
Year of Publication: 2015
Authors:
Addamssiri Najiba, Azzeddine Dahbi, Mohammed Mouhir, Abdelouhaed Kriouile, Taoufiq Gadi
10.5120/ijca2015906989

Addamssiri Najiba, Azzeddine Dahbi, Mohammed Mouhir, Abdelouhaed Kriouile and Taoufiq Gadi. Article: Methods of Detection and Resolution of Anomalies in Business Rule: Comparative Study. International Journal of Computer Applications 129(10):1-7, November 2015. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

@article{key:article,
	author = {Addamssiri Najiba and Azzeddine Dahbi and Mohammed Mouhir and Abdelouhaed Kriouile and Taoufiq Gadi},
	title = {Article: Methods of Detection and Resolution of Anomalies in Business Rule: Comparative Study},
	journal = {International Journal of Computer Applications},
	year = {2015},
	volume = {129},
	number = {10},
	pages = {1-7},
	month = {November},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}
}

Abstract

Currently, agile enterprises are seeking to identify, represent and document the Business rules (BRs) which become one of the most effective ways to express business knowledge. So due to their impact on the information system, detecting and identifying mistakes become an important topic of great concern for the development of information systems. In this paper, we provide a review of several methods treating mistakes in business rules, and present a criteria-based comparison. This work is an outline of future work to integrate business rules filtering in the MDA approach. Also the results of this study will make easier, to provide a relevant method for verification and resolution of the consistency of business rules have a significant impact on the MDA approach.

References

  1. B. Gerhard, D. Jürgen et K. Kurt, Nonmonotonic Reasoning - An Overview, Stanford: CSLI publications, 1997.
  2. C.L. Chang, J.B. Combs, R.A. Stachowitz, "A Report on the Expert Systems Validation Associate (EVA)" Expert Systems With Applications, pp. 217-230, 1990.
  3. C. Jan, "Conflict Resolution Using Logic Programming," IEEE Transactions On Knowledge And Data Engineering, vol. 15, pp. 244 -249, 2003.
  4. C. MIN-YUAN et H. CHIN-JUNG, "A Novel Approach for Treating Uncertain Rule-based Knowledge Conflicts" J. OF INFORMATION SCIENCE AND ENGINEERING, vol. 25, pp. 649-663, 2008.
  5. D. Zhang. et N. Doan., "PREPARE: A Tool for Knowledge Base Verification" IEEE Transactions on Knowledge and Data Engineering, pp. 983-989, 1994.
  6. G. Denilson dos Santos, S. Eber Assis et J. A. Antônio, "A Method for Verifying the Consistency of Business Rules Using Alloy”, International Conference on Software Engineering & Knowledge Engineering, Vancouver, Canada, 2014.
  7. L. An et N. Wilfred, "Vague Sets or Intuitionistic Fuzzy Sets for Handling Vague Data: Which One Is Better?" Lecture Notes in Computer Science, vol. 3716 , pp. 401-416, 2005.
  8. M. Tony, "Business Rules and Information Systems: Aligning It with Business Goals” Boston, MA: Addison-Wesley, 2002.
  9. Richard, C. Hicks, "The no inference engine theory — Performing conflict resolution during development", Decision Support Systems, vol. 43, n° 12, p. 435–444, 2006
  10. S. Motoi, S. A. Carlisle and S. Edward , "An Approach to Verifying Completeness and Consistency in a Rule-Based Expert System" AI Magazine, vol. 3, pp. 16-21, 1982.
  11. T. Wei-Tek, V. Rama et Z. Du, "Verification and validation of Knowledge-Based Systems," IEEE Transactions on Knowledge and Data Engineering, vol. 11, pp. 202-212, 1999.
  12. 12 Z. Qingchuan, Z. Guangping, X. Chaoen et Y. Yang, "A rule conflict resolution method based on Vague set," Soft Computing , vol. 18, n° 13, pp. 549-555 , 2013.

Keywords

Business Rules, detection, resolution, structural errors, SBVR