Model-based Spreadsheet Engineering

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Details

Spreadsheets play an important role in software organizations: they are not only used to define sheets containing data and formulas, but also to collect information from different systems, to perform operations to enrich or simplify data, etc. Unfortunately, spreadsheet systems provide poor support for modularity, abstraction, and transformation, thus making the maintenance of spreadsheets a complex and error-prone task. An emerging solution to handle complex software systems is model-driven engineering. Its basic principle is to consider models as first class entities and to classify any software artifact as either a model or a model instance. In our work, we adapted to spreadsheets several techniques that are inspired by model-driven approaches to generic software systems. In fact, most spreadsheets lack a proper specification or a model. Using reverse engineering techniques we are able to derive various models from legacy spreadsheets: they can be used for several improvements, namely refactoring, safe evolution, migration or even generation of edit assistance. The techniques presented in this book have been integrated in HaExcel, a framework to improve spreadsheet productivity.

Autorentext

Jácome Cunha is a Postdoctoral researcher at the Department of Informatics, University of Minho, Portugal. He obtained his PhD in 2011, following his research on the analysis, transformation, and modeling of spreadsheets. He has co-authored a significant number of scientific publications that have been presented at the best events in his field.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783848430369
    • Sprache Englisch
    • Auflage Aufl.
    • Größe H11mm x B220mm x T150mm
    • Jahr 2012
    • EAN 9783848430369
    • Format Kartonierter Einband (Kt)
    • ISBN 978-3-8484-3036-9
    • Titel Model-based Spreadsheet Engineering
    • Autor Jácome Cunha
    • Untertitel Using Relational Models to Improve Spreadsheets
    • Gewicht 308g
    • Herausgeber LAP Lambert Academic Publishing
    • Anzahl Seiten 220
    • Genre Informatik

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