Jácome Cunha

Spreadsheets are being used with many different purposes that range from toy applications to complete information systems. In any of these cases, they are often used as data repositories that can grow significantly. As the amount of data grows, it also becomes more difficult to extract concrete information out of them. This paper focuses on the problem of spreadsheet querying. In particular, we propose an expressive and composable technique where intuitive queries can be defined. Our approach builds on a model-driven spreadsheet development environment, and queries are expressed referencing entities in the model of a spreadsheet instead of in its actual data. Finally, the system that we have implemented relies on Google's query function for spreadsheets.

This paper presents a tool, named QUERYSHEET, to query spreadsheets. We defined a language to write the queries, which resembles SQL, the language to query databases. This allows to write queries which are more related to the spreadsheet content than with current approaches.

n this extended abstract we present a bidirectional model-driven framework to develop spreadsheets. By being model driven, our approach allows to evolve a spreadsheet model and automatically have the data co-evolved. The bidirectional component achieves precisely the inverse, that is, to evolve the data and automatically obtain a new model to which the data conforms.

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.

n this paper we explore the use of models in the context of spreadsheet engineering. We review a successful spreadsheet modeling language, whose semantics we further extend. With this extension we bring spreadsheet models closer to the business models of spreadsheets themselves. An addon for a widely used spreadsheet system, providing bidirectional model-driven spreadsheet development, was also improved to include the proposed model extension.

Spreadsheets are among the most popular programming languages in the world. Unfortunately, spreadsheet systems were not tailored from scratch with modern programming language features that guarantee, as much as possible, program correctness. As a consequence, spreadsheets are populated with unacceptable amounts of errors. In other programming language settings, model-based approaches have been proposed to increase productivity and program effectiveness. Within spreadsheets, this approach has also been followed, namely by ClassSheets. In this paper, we propose an extension to ClassSheets to allow the specification of spreadsheets that can be viewed as relational databases. Moreover, we present a transformation from ClassSheet models to UML class diagrams enriched with OCL constraints. This brings to the spreadsheet realm the entire paraphernalia of model validation techniques that are available for UML.

n this paper, we present MDSHEET, a framework for the embedding, evolution and inference of spreadsheet models. This framework offers a model-driven software development mechanism for spreadsheet users.

In this paper we present a quality model for spreadsheets, based on the ISO/IEC 9126 standard that defines a generic quality model for software. To each of the software characteristics defined in the ISO/IEC 9126, we associate an equivalent spreadsheet characteristic. Then, we propose a set of spreadsheet specific metrics to assess the quality of a spreadsheet in each of the defined characteristics. In order to obtain the normal distribution of expected values for a spreadsheet in each of the metrics that we propose, we have executed them against all spreadsheets in the large and widely used EUSES spreadsheet corpus. Then, we quantify each characteristic of our quality model after computing the values of our metrics, and we define quality scores for the different ranges of values. Finally, to automate the atribution of a quality score to a given spreadsheet, according to our quality model, we have integrated the computation of the metrics it includes in both a batch and a web-based tool.

This tool demo paper presents SmellSheet Detective: a tool for automatically detecting bad smells in spreadsheets. We have defined a catalog of bad smells in spreadsheet data which was fully implemented in a reusable library for the manipulation of spreadsheets. This library is the building block of the SmellSheet Detective tool, that has been used to detect smells in large, real-world spreadsheet within the EUSES corpus, in order to validate and evolve our bad smells catalog.

Spreadsheets are considered to be the most widely used programming language in the world, and reports have shown that 90% of real-world spreadsheets contain errors. In this work, we try to identify spreadsheet smells, a concept adapted from software, which consists of a surface indication that usually corresponds to a deeper problem. Our smells have been integrated in a tool, and were computed for a large spreadsheet repository. Finally, the analysis of the results we obtained led to the refinement of our initial catalog.

Spreadsheets are widely recognized as popular programming systems with a huge number of spreadsheets being created every day. Also, spreadsheets are often used in the decision processes of profit-oriented companies. While this illustrates their practical importance, studies have shown that up to 90% of real-world spreadsheets contain errors. In order to improve the productivity of spreadsheet end-users, the software engineering community has proposed to employ model-driven approaches to spreadsheet development. In this paper we describe the evaluation of a bidirectional model-driven spreadsheet environment. In this environment, models and data instances are kept in conformity, even after an update on any of these artifacts. We describe the issues of an empirical study we plan to conduct, based on our previous experience with end-user studies. Our goal is to assess if this model-driven spreadsheet development framework does in fact contribute to improve the productivity of spreadsheet users.

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Spreadsheetsarewidelyusedandstudiesshowthatmostoftheexisting ones contain non-trivial errors. To improve end-users productivity, recent research proposes the use of a model-driven engineering approach to spreadsheets. In this paper we conduct the first empirical study to assess the effectiveness and efficiency of this approach. A set of spreadsheet end users worked with two different model-based spreadsheets. We present and analyze here the results achieved.

Spreadsheets are widely used, and studies have shown that most end-user spreadsheets contain non-trivial errors. To improve end-users productivity, recent research proposes the use of a model-driven engineering approach to spreadsheets. In this paper we conduct the first systematic empirical study to assess the effectiveness and efficiency of this approach. A set of spreadsheet end users worked with two different model-based spreadsheets, and we present and analyze here the results achieved.

This paper describes the embedding of ClassSheet models in spreadsheet systems. ClassSheet models are well-known and describe the business logic of spreadsheet data. We embed this domain specific model representation on the (general purpose) spreadsheet system it models. By defining such an embedding, we provide end users a model-driven engineering spreadsheet developing environment. End users can interact with both the model and the spreadsheet data in the same environment. Moreover, we use advanced techniques to evolve spreadsheets and models and to have them synchronized. In this paper we present our work on extending a widely used spreadsheet system with such a model-driven spreadsheet engineering environment.

Spreadsheets are widely used by end users, and studies have shown that most end-user spreadsheets contain non-trivial errors. To improve end users productivity, recent research proposes the use of a model-driven engineering approach to spreadsheets. In this paper we conduct the first systematic empirical study to assess the effectiveness and efficiency of this approach. A set of spreadsheet end users worked with two different model-based spreadsheets, and we present and analyze the results achieved.