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João Paulo Fernandes - One of the best experts on this subject based on the ideXlab platform.
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VL/HCC - Embedding Model-Driven Spreadsheet Queries in Spreadsheet Systems
2014 IEEE Symposium on Visual Languages and Human-Centric Computing (VL HCC), 2014Co-Authors: Rui Pereira, João Paulo Fernandes, Jorge Mendes, João Saraiva, Jácome CunhaAbstract:Spreadsheets are widely used not only to define mathematical expressions, but also to store large and complex data. To query such data is usually a difficult task to perform, usually for end user. In this work we embed the textual query language in the model-driven Spreadsheet environment as a Spreadsheet itself. The result is an expressive and powerful query environment that has knowledge of the business logic defined by the Spreadsheet data (the Spreadsheet model) to guide end users constructing correct queries.
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towards a catalog of Spreadsheet smells
International Conference on Computational Science and Its Applications, 2012Co-Authors: Jácome Cunha, João Paulo Fernandes, Hugo Ribeiro, João SaraivaAbstract: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.
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Embedding and evolution of Spreadsheet models in Spreadsheet systems
Proceedings - 2011 IEEE Symposium on Visual Languages and Human Centric Computing VL HCC 2011, 2011Co-Authors: Jácome Cunha, Jorge Mendes, João Saraiva, João Paulo FernandesAbstract: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. 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.
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VL/HCC - Embedding and evolution of Spreadsheet models in Spreadsheet systems
2011 IEEE Symposium on Visual Languages and Human-Centric Computing (VL HCC), 2011Co-Authors: Jácome Cunha, Jorge Mendes, João Saraiva, João Paulo FernandesAbstract: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. 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.
Jácome Cunha - One of the best experts on this subject based on the ideXlab platform.
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Model inference for Spreadsheets
Automated Software Engineering, 2016Co-Authors: Jácome Cunha, Jorge Mendes, Martin Erwig, João SaraivaAbstract:Many errors in Spreadsheet formulas can be avoided if Spreadsheets are built automatically from higher-level models that can encode and enforce consistency constraints in the generated Spreadsheets. Employing this strategy for legacy Spreadsheets is difficult, because the model has to be reverse engineered from an existing Spreadsheet and existing data must be transferred into the new model-generated Spreadsheet. We have developed and implemented a technique that automatically infers relational schemas from Spreadsheets. This technique uses particularities from the Spreadsheet realm to create better schemas. We have evaluated this technique in two ways: first, we have demonstrated its applicability by using it on a set of real-world Spreadsheets. Second, we have run an empirical study with users. The study has shown that the results produced by our technique are comparable to the ones developed by experts starting from the same (legacy) Spreadsheet data. Although relational schemas are very useful to model data, they do not fit Spreadsheets well, as they do not allow expressing layout. Thus, we have also introduced a mapping between relational schemas and ClassSheets. A ClassSheet controls further changes to the Spreadsheet and safeguards it against a large class of formula errors. The developed tool is a contribution to Spreadsheet (reverse) engineering, because it fills an important gap and allows a promising design method (ClassSheets) to be applied to a huge collection of legacy Spreadsheets with minimal effort.
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VL/HCC - Embedding Model-Driven Spreadsheet Queries in Spreadsheet Systems
2014 IEEE Symposium on Visual Languages and Human-Centric Computing (VL HCC), 2014Co-Authors: Rui Pereira, João Paulo Fernandes, Jorge Mendes, João Saraiva, Jácome CunhaAbstract:Spreadsheets are widely used not only to define mathematical expressions, but also to store large and complex data. To query such data is usually a difficult task to perform, usually for end user. In this work we embed the textual query language in the model-driven Spreadsheet environment as a Spreadsheet itself. The result is an expressive and powerful query environment that has knowledge of the business logic defined by the Spreadsheet data (the Spreadsheet model) to guide end users constructing correct queries.
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towards a catalog of Spreadsheet smells
International Conference on Computational Science and Its Applications, 2012Co-Authors: Jácome Cunha, João Paulo Fernandes, Hugo Ribeiro, João SaraivaAbstract: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.
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Embedding and evolution of Spreadsheet models in Spreadsheet systems
Proceedings - 2011 IEEE Symposium on Visual Languages and Human Centric Computing VL HCC 2011, 2011Co-Authors: Jácome Cunha, Jorge Mendes, João Saraiva, João Paulo FernandesAbstract: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. 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.
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VL/HCC - Embedding and evolution of Spreadsheet models in Spreadsheet systems
2011 IEEE Symposium on Visual Languages and Human-Centric Computing (VL HCC), 2011Co-Authors: Jácome Cunha, Jorge Mendes, João Saraiva, João Paulo FernandesAbstract: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. 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.
Felienne Hermans - One of the best experts on this subject based on the ideXlab platform.
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evaluating automatic Spreadsheet metadata extraction on a large set of responses from mooc participants
IEEE International Conference on Software Analysis Evolution and Reengineering, 2016Co-Authors: Sohon Roy, Felienne Hermans, Efthimia Aivaloglou, Jos Winter, Arie Van DeursenAbstract:Spreadsheets are popular end-user computing applicationsand one reason behind their popularity is that theyoffer a large degree of freedom to their users regarding theway they can structure their data. However, this flexibilityalso makes Spreadsheets difficult to understand. Textual documentationcan address this issue, yet for supporting automaticgeneration of textual documentation, an important pre-requisiteis to extract metadata inside Spreadsheets. It is a challengethough, to distinguish between data and metadata due to thelack of universally accepted structural patterns in Spreadsheets. Two existing approaches for automatic extraction of Spreadsheetmetadata were not evaluated on large datasets consisting ofuser inputs. Hence in this paper, we describe the collectionof a large number of user responses regarding identificationof Spreadsheet metadata from participants of a MOOC. Wedescribe the use of this large dataset to understand how usersidentify metadata in Spreadsheets, and to evaluate two existingapproaches of automatic metadata extraction from Spreadsheets. The results provide us with directions to follow in order toimprove metadata extraction approaches, obtained from insightsabout user perception of metadata. We also understand what typeof Spreadsheet patterns the existing approaches perform well andon what type poorly, and thus which problem areas to focus onin order to improve.
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SANER - Evaluating Automatic Spreadsheet Metadata Extraction on a Large Set of Responses from MOOC Participants
2016 IEEE 23rd International Conference on Software Analysis Evolution and Reengineering (SANER), 2016Co-Authors: Sohon Roy, Felienne Hermans, Efthimia Aivaloglou, Jos Winter, Arie Van DeursenAbstract:Spreadsheets are popular end-user computing applicationsand one reason behind their popularity is that theyoffer a large degree of freedom to their users regarding theway they can structure their data. However, this flexibilityalso makes Spreadsheets difficult to understand. Textual documentationcan address this issue, yet for supporting automaticgeneration of textual documentation, an important pre-requisiteis to extract metadata inside Spreadsheets. It is a challengethough, to distinguish between data and metadata due to thelack of universally accepted structural patterns in Spreadsheets. Two existing approaches for automatic extraction of Spreadsheetmetadata were not evaluated on large datasets consisting ofuser inputs. Hence in this paper, we describe the collectionof a large number of user responses regarding identificationof Spreadsheet metadata from participants of a MOOC. Wedescribe the use of this large dataset to understand how usersidentify metadata in Spreadsheets, and to evaluate two existingapproaches of automatic metadata extraction from Spreadsheets. The results provide us with directions to follow in order toimprove metadata extraction approaches, obtained from insightsabout user perception of metadata. We also understand what typeof Spreadsheet patterns the existing approaches perform well andon what type poorly, and thus which problem areas to focus onin order to improve.
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Auditing Spreadsheets: With or without a tool?
arXiv: Software Engineering, 2016Co-Authors: Simone Schalkwijk, Felienne Hermans, Michiel Van Der Ven, Hans DuitsAbstract:Spreadsheets are known to be error-prone. Over the last decade, research has been done to determine the causes of the high rate of errors in Spreadsheets. This paper examines the added value of a Spreadsheet tool (PerfectXL) that visualizes Spreadsheet dependencies and determines possible errors in Spreadsheets by defining risk areas based on previous work. This paper will firstly discuss the most common mistakes in Spreadsheets. Then we will summarize research on Spreadsheet tools, focussing on the PerfectXL tool. To determine the perceptions of the usefulness of a Spreadsheet tool in general and the PerfectXL tool in particular, we have shown the functionality of PerfectXL to several auditors and have also interviewed them. The results of these interviews indicate that Spreadsheet tools support a more effective and efficient audit of Spreadsheets; the visualization feature in particular is mentioned by the auditors as being highly supportive for their audit task, whereas the risk feature was deemed of lesser value.
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FOSE@SANER - Spreadsheets are Code: An Overview of Software Engineering Approaches Applied to Spreadsheets
2016 IEEE 23rd International Conference on Software Analysis Evolution and Reengineering (SANER), 2016Co-Authors: Felienne Hermans, Sohon Roy, Efthimia Aivaloglou, Bas Jansen, Alaaeddin Swidan, David HoepelmanAbstract:Spreadsheets can be considered to be the world's most successful end-user programming language. In fact, one could say Spreadsheets are programs. This paper starts with a comparison of Spreadsheets to software: Spreadsheets are similar in terms of applications domains, expressive power and maintainability problems. We then reflect upon what makes Spreadsheets successful: liveness, directness and an easy deployment environment seem contribute largely to their success. Being a programming language, several techniques from software engineering can be applied to Spreadsheets. We present an overview of such research directions, including Spreadsheet testing, reverse engineering, smell detection, clone detection and refactoring. Finally, open challenges and future plans for the domain of Spreadsheet software engineering are presented.
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ICSE (2) - 2nd international workshop on software engineering methods in Spreadsheets (SEMS 2015)
2015 IEEE ACM 37th IEEE International Conference on Software Engineering, 2015Co-Authors: Felienne Hermans, Peter SestoftAbstract:Spreadsheets are heavily used in industry, because they are easily written and adjusted, using an intuitive visual interface. They often start out as simple tools; however, over time Spreadsheets can become increasingly complex, up to the point where they become complicated and inflexible. In many ways, Spreadsheet are similar to software: both concern the storage and manipulation of data and the presentation of results to the user. Because of this similarity, many methods and techniques from software engineering can be applied to Spreadsheets. The role of SEMS, the International Workshop on Software Engineering Methods in Spreadsheets is to explore the possibilities of applying successful methods from software engineering to Spreadsheets. Some, like testing and visualization, have been tried before and can be built upon. For methods that have not yet been tried on Spreadsheets, SEMS will serve as a platform for early feedback. The SEMS program included an industrial keynote, "Spreadsheet stories" (success or failure), short and long research papers, a good mix of industrial and academic researchers, as well as lively discussion and debate.
João Saraiva - One of the best experts on this subject based on the ideXlab platform.
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Model inference for Spreadsheets
Automated Software Engineering, 2016Co-Authors: Jácome Cunha, Jorge Mendes, Martin Erwig, João SaraivaAbstract:Many errors in Spreadsheet formulas can be avoided if Spreadsheets are built automatically from higher-level models that can encode and enforce consistency constraints in the generated Spreadsheets. Employing this strategy for legacy Spreadsheets is difficult, because the model has to be reverse engineered from an existing Spreadsheet and existing data must be transferred into the new model-generated Spreadsheet. We have developed and implemented a technique that automatically infers relational schemas from Spreadsheets. This technique uses particularities from the Spreadsheet realm to create better schemas. We have evaluated this technique in two ways: first, we have demonstrated its applicability by using it on a set of real-world Spreadsheets. Second, we have run an empirical study with users. The study has shown that the results produced by our technique are comparable to the ones developed by experts starting from the same (legacy) Spreadsheet data. Although relational schemas are very useful to model data, they do not fit Spreadsheets well, as they do not allow expressing layout. Thus, we have also introduced a mapping between relational schemas and ClassSheets. A ClassSheet controls further changes to the Spreadsheet and safeguards it against a large class of formula errors. The developed tool is a contribution to Spreadsheet (reverse) engineering, because it fills an important gap and allows a promising design method (ClassSheets) to be applied to a huge collection of legacy Spreadsheets with minimal effort.
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VL/HCC - Embedding Model-Driven Spreadsheet Queries in Spreadsheet Systems
2014 IEEE Symposium on Visual Languages and Human-Centric Computing (VL HCC), 2014Co-Authors: Rui Pereira, João Paulo Fernandes, Jorge Mendes, João Saraiva, Jácome CunhaAbstract:Spreadsheets are widely used not only to define mathematical expressions, but also to store large and complex data. To query such data is usually a difficult task to perform, usually for end user. In this work we embed the textual query language in the model-driven Spreadsheet environment as a Spreadsheet itself. The result is an expressive and powerful query environment that has knowledge of the business logic defined by the Spreadsheet data (the Spreadsheet model) to guide end users constructing correct queries.
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towards a catalog of Spreadsheet smells
International Conference on Computational Science and Its Applications, 2012Co-Authors: Jácome Cunha, João Paulo Fernandes, Hugo Ribeiro, João SaraivaAbstract: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.
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Embedding and evolution of Spreadsheet models in Spreadsheet systems
Proceedings - 2011 IEEE Symposium on Visual Languages and Human Centric Computing VL HCC 2011, 2011Co-Authors: Jácome Cunha, Jorge Mendes, João Saraiva, João Paulo FernandesAbstract: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. 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.
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VL/HCC - Embedding and evolution of Spreadsheet models in Spreadsheet systems
2011 IEEE Symposium on Visual Languages and Human-Centric Computing (VL HCC), 2011Co-Authors: Jácome Cunha, Jorge Mendes, João Saraiva, João Paulo FernandesAbstract: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. 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.
Jorge Mendes - One of the best experts on this subject based on the ideXlab platform.
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Model inference for Spreadsheets
Automated Software Engineering, 2016Co-Authors: Jácome Cunha, Jorge Mendes, Martin Erwig, João SaraivaAbstract:Many errors in Spreadsheet formulas can be avoided if Spreadsheets are built automatically from higher-level models that can encode and enforce consistency constraints in the generated Spreadsheets. Employing this strategy for legacy Spreadsheets is difficult, because the model has to be reverse engineered from an existing Spreadsheet and existing data must be transferred into the new model-generated Spreadsheet. We have developed and implemented a technique that automatically infers relational schemas from Spreadsheets. This technique uses particularities from the Spreadsheet realm to create better schemas. We have evaluated this technique in two ways: first, we have demonstrated its applicability by using it on a set of real-world Spreadsheets. Second, we have run an empirical study with users. The study has shown that the results produced by our technique are comparable to the ones developed by experts starting from the same (legacy) Spreadsheet data. Although relational schemas are very useful to model data, they do not fit Spreadsheets well, as they do not allow expressing layout. Thus, we have also introduced a mapping between relational schemas and ClassSheets. A ClassSheet controls further changes to the Spreadsheet and safeguards it against a large class of formula errors. The developed tool is a contribution to Spreadsheet (reverse) engineering, because it fills an important gap and allows a promising design method (ClassSheets) to be applied to a huge collection of legacy Spreadsheets with minimal effort.
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VL/HCC - Embedding Model-Driven Spreadsheet Queries in Spreadsheet Systems
2014 IEEE Symposium on Visual Languages and Human-Centric Computing (VL HCC), 2014Co-Authors: Rui Pereira, João Paulo Fernandes, Jorge Mendes, João Saraiva, Jácome CunhaAbstract:Spreadsheets are widely used not only to define mathematical expressions, but also to store large and complex data. To query such data is usually a difficult task to perform, usually for end user. In this work we embed the textual query language in the model-driven Spreadsheet environment as a Spreadsheet itself. The result is an expressive and powerful query environment that has knowledge of the business logic defined by the Spreadsheet data (the Spreadsheet model) to guide end users constructing correct queries.
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Embedding and evolution of Spreadsheet models in Spreadsheet systems
Proceedings - 2011 IEEE Symposium on Visual Languages and Human Centric Computing VL HCC 2011, 2011Co-Authors: Jácome Cunha, Jorge Mendes, João Saraiva, João Paulo FernandesAbstract: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. 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.
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VL/HCC - Embedding and evolution of Spreadsheet models in Spreadsheet systems
2011 IEEE Symposium on Visual Languages and Human-Centric Computing (VL HCC), 2011Co-Authors: Jácome Cunha, Jorge Mendes, João Saraiva, João Paulo FernandesAbstract: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. 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.