Automatic generation and maintenance of correct spreadsheets
Proceedings of the 27th international conference on Software engineering
Visual Specifications of Correct Spreadsheets
VLHCC '05 Proceedings of the 2005 IEEE Symposium on Visual Languages and Human-Centric Computing
ClassSheets: automatic generation of spreadsheet applications from object-oriented specifications
Proceedings of the 20th IEEE/ACM international Conference on Automated software engineering
Bidirectional Transformations: A Cross-Discipline Perspective
ICMT '09 Proceedings of the 2nd International Conference on Theory and Practice of Model Transformations
Automatically extracting class diagrams from spreadsheets
ECOOP'10 Proceedings of the 24th European conference on Object-oriented programming
Type-safe evolution of spreadsheets
FASE'11/ETAPS'11 Proceedings of the 14th international conference on Fundamental approaches to software engineering: part of the joint European conferences on theory and practice of software
MDSheet: a framework for model-driven spreadsheet engineering
Proceedings of the 34th International Conference on Software Engineering
Bidirectional transformation of model-driven spreadsheets
ICMT'12 Proceedings of the 5th international conference on Theory and Practice of Model Transformations
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Spreadsheets are increasingly used as programming languages, in the construction of large and complex systems. The fact is that spreadsheets, being a highly flexible framework, lack important programming language features such as abstraction or encapsulation. This flexibility, however, comes with a price: spreadsheets are populated with significant amounts of errors. One of the approaches that try to overcome this problem advocates the use of model-driven spreadsheet development: a spreadsheet model is defined, from which a concrete spreadsheet is generated. Although this approach has been proved effective in other contexts, still it needs to accommodate for future evolution of both the model and its instance, so that they remain synchronized at all moments. In this paper, we propose a pair of transformation sets, one working at the model level and the other at the instance level, such that each transformation in one set is related to a transformation in the other set. With our approach, we ensure model/data compliance while allowing for model and data evolution.