These tutorial notes present a methodology for spreadsheet engineering. First, we present data mining and database techniques to reason about spreadsheet data. These techniques are used to compute relationships between spreadsheet elements (cells/columns/rows), which are later used to infer a model defining the business logic of the spreadsheet. Such a model of a spreadsheet data is a visual domain specific language that we embed in a well-known spreadsheet system. The embedded model is the building block to define techniques for model-driven spreadsheet development, where advanced techniques are used to guarantee the model-instance synchronization. In this modeldriven environment, any user data update has to follow the model-instance conformance relation, thus, guiding spreadsheet users to introduce correct data. Data refinement techniques are used to synchronize models and instances after users update/evolve the model. These notes briefly describe ourmodel-driven spreadsheet environment, the MDSheet environment, that implements the presented methodology. To evaluate both proposed techniques and the MDSheet tool, we have conducted, in laboratory sessions, an empirical study with the summer school participants. The results of this study are presented in these notes.
|Title of host publication||Central European Functional Programming School|
|Subtitle of host publication||5th Summer School, CEFP 2013, Cluj-Napoca, Romania, July 8-20, 2013, Revised Selected Papers|
|Number of pages||54|
|Publication status||Published - 21 Mar 2015|