Business Rule Mining from Spreadsheets
This addresses the need for organizations to mine business rules from spreadsheets for migration and documentation, but it is incremental as it extends existing rule mining from conventional software to spreadsheets.
The paper tackles the problem of extracting business rules from spreadsheets, proposing an automated system to convert them into human-readable natural language, but it does not report any results or concrete numbers as it is a position paper.
Business rules represent the knowledge that guides the operations of a business organization. They are implemented in software applications used by organizations, and the activity of extracting them from software is known as business rule mining. It has various purposes amongst which migration and generating documentation are the most common. However, apart from conventional software, organizations also use spreadsheets for a large part of their operations and decision-making activities. Therefore we believe that spreadsheets are also rich in business rules. We thus propose to develop an automated system for extracting business rules from spreadsheets in a human comprehensible natural language format. This position paper describes our motivation, the problem description, related work, and challenges we foresee.