Thanks to their flexibility and intuitive programming model, spreadsheets are widely used in industry, often for business- critical applications. Similar to software developers, pro- fessional spreadsheet users demand support for maintaining and transferring their spreadsheets.
In this paper, we first study the problems and information needs of professional spreadsheet users by means of a survey conducted at a large financial company. Based on these needs, we then present an approach that extracts this information from spreadsheets and presents it in a compact and easy to understand way, using leveled dataflow diagrams. Our approach comes with three different views on the dataflow and allows the user to analyze the dataflow diagrams in a top-down fashion also using slicing techniques.
To evaluate the usefulness of the proposed approach, we conducted a series of interviews as well as nine case studies in an industrial setting. The results of the evaluation clearly indicate the demand for and usefulness of our approach in ease the understanding of spreadsheets.
Many professional software developers might cringe when thinking about spreadsheets, or simply not take them seriously because they're not "real programming". They are, however, a fact of business and often get the job done. While they can be developed much faster, they also bear a great potential for errors. Felienne and her co-authors embraced this reality and decided to do something about it -- using approaches from software engineering.
Ignoring any assumptions regarding the problems of spreadsheet users, they used Grounded Theory in an industry setting to find out which problems really existed in business. One thing they found was that existing spreadsheets often need to be understood by new users. Diving deeper, they found that the comprehensibility of such inherited spreadsheets was often seriously lacking -- posing a great risk from a business perspective.
The authors then developed a tool to help with this issue. It creates dataflow diagrams that make dependencies in spreadsheet formulas visible. An evaluation with business users showed that these diagrams are indeed comprehensible and useful -- that is, they help end-users in understanding unfamiliar spreadsheets. Another interesting finding was that the creators of -- in their view -- simple spreadsheets only realized the actual complexity of their own creations after having used the tool.
The best part is: Felienne, Martin, and Arie demonstrated the practical relevance again by launching a successful startup based on this research! The company is now part of the Dutch startup incubator "YesDelft", has partnerships with several IT service companies, and has paying customers. How's that for practical relevance of research?Comments powered by Disqus