Publications

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Submitted
A Structured Approach to Document Spreadsheets (in preparation), Cunha, Jácome, and Canteiro Diogo , (Submitted) jvlc.pdf
2017
Systematic Spreadsheet Construction Processes, Mendes, Jorge, Cunha Jácome, Duarte Francisco, Engels Gregor, Saraiva João, and Sauer Stefan , IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), 11-14 Oct., Raleigh, North Carolina, USA, (2017) paper.pdf
2016
Static Energy Consumption Analysis in Variability Systems, Couto, Marco, Cunha Jácome, Fernandes João Paulo, Pereira Rui, and Saraiva João Alexandre , 2nd Green in Software Engineering Workshop (GInSEng’16), an event of the 4th International Conference on ICT for Sustainability (ICT4S), 29 Aug. - 1 Sep., Amsterdam, The Netherlands, (2016) Abstractginseng_2016_paper_1-2.pdf

Energy consumption is becoming an evident concern to software developers. This is even more notorious due to the propagation of mobile devices. Such propagation of devices is also influencing software development: a software system is now developed has a set of similar products sharing common features.
In this short paper, we describe our methodology aim at static and accurately predict the energy consumption of software products in such variability systems, typically called software product lines.

2015
SpreadsheetDoc: An Excel Add-in for Documenting Spreadsheets, Canteiro, Diogo, and Cunha Jácome , Proceedings of the 6th National Symposium of Informatics (INForum’15), Covilhã, Portugal, (2015) inforum2015.pdf
2014
Spreadsheet Engineering, Cunha, Jácome, Fernandes João Paulo, and Saraiva João , Central European Functional Programming School - 5th Summer School, CEFP 2013, Revised Selected Papers, July, Springer, Heidelberg, (2014) Abstractdsl13_notes.pdf

These tutorial notes present a methodology for spreadsheet engineering. First, we present data mining and database techniques to reason about spreadsheet data. These techniques are used to compute relationships between spreadsheet elements (cells/columns/rows). These relations are then used to infer a model defining the business logic of the spreadsheet. Such a model of a spreadsheet data is a visual domain specific language that we embed in a well-known spreadsheet system. The embedded model is the building block to define techniques for model-driven spreadsheet development, where advanced techniques are used to guarantee the model-instance synchronization. In this model-driven environment, any user data update as to follow the the model-instance conformance relation, thus, guiding spreadsheet users to introduce correct data. Data refinement techniques are used to synchronize models and instances after users update/evolve the model. These notes briefly describe our model-driven spreadsheet environment, the MDSheet environment, that implements the presented methodology. To evaluate both proposed techniques and the MDSheet tool, we have conducted, in laboratory sessions, an empirical study with the summer school participants. The results of this study are presented in these notes.

Smelling Faults in Spreadsheets, Abreu, Rui, Cunha Jácome, Fernandes João Paulo, Martins Pedro, Perez Alexandre, and Saraiva João , Proceedings of the 30th IEEE International Conference on Software Maintenance and Evolution, Washington, DC, USA, p.111–120, (2014) Abstracticsme14.pdf

Despite being staggeringly error prone, spreadsheets are a highly flexible programming environment that is widely used in industry. In fact, spreadsheets are widely adopted for decision making, and decisions taken upon wrong (spreadsheet-based) assumptions may have serious economical impacts on businesses, among other consequences. This paper proposes a technique to automatically pinpoint potential faults in spreadsheets. It combines a catalog of spreadsheet smells that provide a first indication of a potential fault, with a generic spectrum-based fault localization strategy in order to improve (in terms of accuracy and false positive rate) on these initial results. Our technique has been implemented in a tool which helps users detecting faults. To validate the proposed technique, we consider a well-known and well-documented catalog of faulty spreadsheets. Our experiments yield two main results: we were able to distinguish between smells that can point to faulty cells from smells and those that are not capable of doing so; and we provide a technique capable of detecting a significant number of errors: two thirds of the cells labeled as faulty are in fact (documented) errors.

SSaaPP: SpreadSheets as a Programming Paradigm – Project's Final Report, Abreu, Rui, Alves Tiago, Belo Orlando, Campos José C., Cunha Jácome, Fernandes João Paulo, Martins Pedro, Mendes Jorge, Pacheco Hugo, Peixoto Christophe, Pereira Rui, Perez Alexandre, Ribeiro Hugo, Riboira André, Saraiva João, Silva André, Silva João Carlos, and Visser Joost , Number TR-HASLab:02:2014, (2014) Abstracttr_ssaapp.pdf

This technical report describes the research goals and results of the SpreadSheet as a Programming Paradigm research project. This was a project funded by Funda{\c c}ão para a Ciencia e Tecnologia – FCT: the Portuguese research foundation, under reference FCOMP-01-0124-FEDER-010048, that ran from May 2010 till July 2013. This report includes the complete document reporting the results achieved during the project execution, which was submitted to FCT for evaluation on October 2013. It describes the goals of the project, and the different research tasks presenting the deliver- ables of each of them. It also presents the management and result dissemination work performed during the project's execution. The document includes also a self assess- ment of the achieved results, and a complete list of scientific publications describing the contributions of the project. Finally, this document includes the FCT evaluation report.

2012
SmellSheet Detective: A Tool for Detecting Bad Smells in Spreadsheets, Cunha, Jácome, Fernandes João Paulo, Mendes Jorge, Martins Pedro, and Saraiva João , Proceedings of the 2012 IEEE Symposium on Visual Languages and Human-Centric Computing, Washington, DC, USA, p.243–244, (2012) Abstractvlhcc12-td.pdf

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.