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Publicações por João Alexandre Saraiva

2015

Embedding, Evolution, and Validation of Model-Driven Spreadsheets

Autores
Cunha, J; Fernandes, JP; Mendes, J; Saraiva, J;

Publicação
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING

Abstract
This paper proposes and validates a model-driven software engineering technique for spreadsheets. The technique that we envision builds on the embedding of spreadsheet models under a widely used spreadsheet system. This means that we enable the creation and evolution of spreadsheet models under a spreadsheet system. More precisely, we embed ClassSheets, a visual language with a syntax similar to the one offered by common spreadsheets, that was created with the aim of specifying spreadsheets. Our embedding allows models and their conforming instances to be developed under the same environment. In practice, this convenient environment enhances evolution steps at the model level while the corresponding instance is automatically co-evolved. Finally, we have designed and conducted an empirical study with human users in order to assess our technique in production environments. The results of this study are promising and suggest that productivity gains are realizable under our model-driven spreadsheet development setting.

2016

Evaluating refactorings for spreadsheet models

Autores
Cunha, J; Fernandes, JP; Martins, P; Mendes, J; Pereira, R; Saraiva, J;

Publicação
Journal of Systems and Software

Abstract
Software refactoring is a well-known technique that provides transformations on software artifacts with the aim of improving their overall quality. We have previously proposed a catalog of refactorings for spreadsheet models expressed in the ClassSheets modeling language, which allows us to specify the business logic of a spreadsheet in an object-oriented fashion. Reasoning about spreadsheets at the model level enhances a model-driven spreadsheet environment where a ClassSheet model and its conforming instance (spreadsheet data) automatically co-evolves after applying a refactoring at the model level. Research motivation was to improve the model and its conforming instance: the spreadsheet data. In this paper we define such refactorings using previously proposed evolution steps for models and instances. We also present an empirical study we designed and conducted in order to confirm our original intuition that these refactorings have a positive impact on end-user productivity, both in terms of effectiveness and efficiency. The results are not only presented in terms of productivity changes between refactored and non-refactored scenarios, but also the overall user satisfaction, relevance, and experience. In almost all cases the refactorings improved end-users productivity. Moreover, in most cases users were more engaged with the refactored version of the spreadsheets they worked with.

2015

GreenDroid: A Tool for Analysing Power Consumption in the Android Ecosystem

Autores
Couto, M; Cunha, J; Fernandes, JP; Pereira, R; Saraiva, J;

Publicação
2015 IEEE 13th International Scientific Conference on Informatics

Abstract
This paper presents GreenDroid, a tool for monitoring and analyzing power consumption for the Android ecosystem. This tool instruments the source code of a giving Android application and is able to estimate the power consumed when running it. Moreover, it uses advanced classification algorithms to detect abnormal power consumption and to relate them to fragments in the source code. A set of graphical results are produced that help software developers to identify abnormal power consumption in their source code.

2016

Model inference for spreadsheets

Autores
Cunha, J; Erwig, M; Mendes, J; Saraiva, J;

Publicação
Autom. Softw. Eng.

Abstract
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. © 2014, Springer Science+Business Media New York.

2016

Parsing and Reflective Printing, Bidirectionally

Autores
Zhu, ZR; Zhang, YZ; Ko, HS; Martins, P; Saraiva, J; Hu, ZJ;

Publicação
PROCEEDINGS OF THE 2016 ACM SIGPLAN INTERNATIONAL CONFERENCE ON SOFTWARE LANGUAGE ENGINEERING (SLE'16)

Abstract
Language designers usually need to implement parsers and printers. Despite being two intimately related programs, in practice they are often designed separately, and then need to be revised and kept consistent as the language evolves. It will be more convenient if the parser and printer can be unified and developed in one single program, with their consistency guaranteed automatically. Furthermore, in certain scenarios (like showing compiler optimisation results to the programmer), it is desirable to have a more powerful reflective printer that, when an abstract syntax tree corresponding to a piece of program text is modified, can reflect the modification to the program text while preserving layouts, comments, and syntactic sugar. To address these needs, we propose a domain-specific language BIYACC, whose programs denote both a parser and a reflective printer for an unambiguous context-free grammar. BIYACC is based on the theory of bidirectional transformations, which helps to guarantee by construction that the pairs of parsers and reflective printers generated by BIYACC are consistent. We show that BIYACC is capable of facilitating many tasks such as Pombrio and Krishnamurthi's "resugaring", simple refactoring, and language evolution.

2017

Products go Green: Worst-Case Energy Consumption in Software Product Lines

Autores
Couto, M; Borba, P; Cunha, J; Fernandes, JP; Pereira, R; Saraiva, J;

Publicação
Proceedings of the 21st International Systems and Software Product Line Conference, SPLC 2017, Volume A, Sevilla, Spain, September 25-29, 2017

Abstract
The optimization of software to be (more) energy efficient is becoming a major concern for the software industry. Although several techniques have been presented to measure energy consumption for software, none has addressed software product lines (SPLs). Thus, to measure energy consumption of a SPL, the products must be generated and measured individually, which is too costly. In this paper, we present a technique and a prototype tool to statically estimate the worst case energy consumption for SPL. The goal is to provide developers with techniques and tools to reason about the energy consumption of all products in a SPL, without having to produce, run and measure the energy in all of them. Our technique combines static program analysis techniques and worst case execution time prediction with energy consumption analysis. This technique analyzes all products in a feature-sensitive manner, that is, a feature used in several products is analyzed only once, while the energy consumption is estimated once per product. We implemented our technique in a tool called Serapis. We did a preliminary evaluation using a product line for image processing implemented in C. Our experiments considered 7 products from such line and our initial results show that the tool was able to estimate the worst-case energy consumption with a mean error percentage of 9.4% and standard deviation of 6.2% when compared with the energy measured when running the products. © 2017 ACM.

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