Bidirectional Transformation of Model-Driven Spreadsheets

Abstract

Spreadsheets play an important role in software organizations. Indeed, in large software organizations, spreadsheets are not only used to define sheets containing data and formulas, but also to collect information from different systems, to adapt data coming from one system to the format required by another, to perform operations to enrich or simplify data, etc. In fact, over time many spreadsheets turn out to be used for storing and processing increasing amounts of data and supporting increasing numbers of users. Unfortunately, spreadsheet systems provide poor support for modularity, abstraction, and transformation, thus, making the maintenance, update and evolution of spreadsheets a very complex and error-prone task. We present techniques for model-driven spreadsheet engineering where we employ bidirectional transformations to maintain spreadsheet models and instances synchronized. In our setting, the business logic of spreadsheets is defined by ClassSheet models to which the spreadsheet data conforms, and spreadsheet users may evolve both the model and the data instances. Our techniques are implemented as part of the MDSheet framework: an extension for a traditional spreadsheet system.

A bidirectional model-driven spreadsheet environment

“…Later, we have proposed to automatically co-evolve spreadsheet instances upon a model transformation [5], a feature that has also been integrated in a tool [6]. Finally, we have defined the theoretical setting to reason about spreadsheet models and instances in the reverse direction: we allow for data instance evolutions while models are automatically co-evolved [7].…”

Data Compatibility to Enhance Sustainable Capabilities for Autonomous Analytics in IoT

“…XPATH (Standard for XPath is available from the W3C Website https://www.w3.org/TR/xpath20/) Expressions are a possible course of action. Each report of a particular standard is changed into examination of an acknowledged structure in the midst of the phonetic change stage [16]. During the second stage, i.e., endorsed to-definitive semantic change, the acknowledged structure is changed into an integrated semantic standard structure, which is RDF for our condition.…”

“…Many researchers that are working in IoT are syncing the Semantic Web data model as a part of IoT Architecture [21]. Syncing of different data models requires the modeling of a transformation mechanism having the capability of showing the fast impact of change appearing on any end of the data producer or receiver [16]. To make the system of IoT and semantic annotation more powerful, which works bidirectionally [29], two different data models need to have to a common language.…”

“…The dominant part of the framework takes a shot at conventional devices and databases. Information and preparing models need to focus on conquering similarity issues by adopting data transformation mechanisms [16]. The Semantic Web introduced RDF as a data model having the capability of capturing hierarchal relationships among different resources.…”

Model-based programming environments for spreadsheets

“…We have used such spreadsheet models, namely the ClassSheet models [19], to realize model-driven software evolution in the context of spreadsheets [20][21][22].…”