Business Rule Mining from Spreadsheets

TL;DR

This paper advocates for automated extraction of business rules from spreadsheets, which are often overlooked sources of organizational knowledge, aiming to improve documentation and migration processes.

Contribution

It introduces the concept of mining business rules specifically from spreadsheets and discusses the challenges involved in developing such an automated system.

Findings

Spreadsheets contain valuable business rules.

Automated extraction from spreadsheets is feasible but challenging.

This work highlights the need for further research in this area.

Abstract

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.