MatGap: A Systematic Approach to Perform Match and Gap Analysis among SBVR-Based Domain Specific Business Rules

摘要

In the modern age, the need for automation has led to Business Organizations representing their functionality as structured Business Rules. SBVR has come up as an universally popular format for representation of Business Rules. The presence of different Business Organizations working in a particular real life domain results in generation of different rules for each of the organization. Due to the varying business practices, like mergers & acquisitions, upgrades, incorporation of a new application, etc., it becomes necessary to compare a set of Business Rules of a particular organization with the rules of a reference model, to get a measure of similarity among the business functionality of the two. Presently, this comparison is carried out manually by business experts or by executing the rules of one organization with the data of another and checking if they are compliant. Both the approaches are extremely tedious and expensive as modern organizations have huge rule sets and data sets.We present MatGap, a tool which performs a systematic Match and Gap Analysis between two sets of SBVR-based Business Rules applicable to a specific domain, using Global Vectors(GloVe) model and SMT-LIBv2. The analysis report gives a measure of Match among the rules and entities, thus providing the best alignment and aids to identify the representational Gaps(if any) among the rules and entities. The tool also checks whether the embedded logic in the reference Business Rule set is covered by the other Rule set, thus highlighting the business functionality gap that is present in the latter.