loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Sayandeep Mitra ; Kritika Anand and Pavan Kumar Chittimalli

Affiliation: Tata Research Development and Design Centre, India

Keyword(s): Business Rules, Verification, Directed Graph, SMT, Clustering, SBVR, Anomalies.

Related Ontology Subjects/Areas/Topics: Biomedical Engineering ; Data Engineering ; Enterprise Information Systems ; Health Information Systems ; Information Systems Analysis and Specification ; Knowledge Management ; Model Driven Architectures and Engineering ; Ontologies and the Semantic Web ; Society, e-Business and e-Government ; Software Engineering ; Web Information Systems and Technologies

Abstract: In modern times, business rules have grown exponentially with enterprises becoming more complex in diverse fields. Due to this growth, different forms of anomalies creep into the business rules, causing business enterprise to take wrong decisions, which can impact it’s performance and reputation. It is time and resource consuming to examine the rules manually due to the large number of rules intermingled with each other. The process of manual verification is also not free of human induced errors. Thus, automatic verification of business rules is the need of the hour. We present a tool to detect different anomalies in business rules represented in SBVR format. The tool uses a combination of Directed Graphs and SMT solvers to perform the verification task. We show the implementation of our tool along with it’s evaluation on industry level benchmarks.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 52.90.50.252

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Mitra, S.; Anand, K. and Chittimalli, P. (2018). Identifying Anomalies in SBVR-based Business Rules using Directed Graphs and SMT-LIBv2. In Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 2: ICEIS; ISBN 978-989-758-298-1; ISSN 2184-4992, SciTePress, pages 215-222. DOI: 10.5220/0006669802150222

@conference{iceis18,
author={Sayandeep Mitra. and Kritika Anand. and Pavan Kumar Chittimalli.},
title={Identifying Anomalies in SBVR-based Business Rules using Directed Graphs and SMT-LIBv2},
booktitle={Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 2: ICEIS},
year={2018},
pages={215-222},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006669802150222},
isbn={978-989-758-298-1},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 2: ICEIS
TI - Identifying Anomalies in SBVR-based Business Rules using Directed Graphs and SMT-LIBv2
SN - 978-989-758-298-1
IS - 2184-4992
AU - Mitra, S.
AU - Anand, K.
AU - Chittimalli, P.
PY - 2018
SP - 215
EP - 222
DO - 10.5220/0006669802150222
PB - SciTePress