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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.

The use of powerful mobile devices, like smartphones, tablets and laptops, are changing the way programmers develop software. While in the past the primary goal to optimize software was the run time optimization, nowadays there is a growing awareness of the need to reduce energy consumption. This paper presents a technique and a tool to detect anomalous energy consumption in Android applications, and to relate it directly with the source code of the application. We propose a dynamically calibrated model for energy consumption for the Android ecosystem, and that supports different devices. The model is then used as an API to monitor the application execution: first, we instrument the application source code so that we can relate energy consumption to the application source code; second, we use a statistical approach, based on fault-localization techniques, to localize abnormal energy consumption in the source code.

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.

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.

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, so that models and their conforming instances are 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.

This paper presents ES-SQL, an embedded tool for visually constructing queries over spreadsheets. This tool provides an expressive query environment which has knowledge on the business logic of spreadsheets, and by this knowledge it assists the user in defining the intended queries.

This paper presents a tool, dubbed FaultySheet Detective, for aiding in spreadsheet fault localization, which combines the detection of bad smells with a generic spectrum-based fault localization algorithm.

This paper presents a graphical interface to query model-driven spreadsheets, based on experience with previous work and empirical studies in querying systems, to simplify query construction for typical end-users with little to no knowledge of SQL. We briefly show our previous text based model-driven querying system. Afterwards, we detail our graphical model-driven querying interface, explaining each part of the interface and showing an example. To validate our work, we executed an empirical study, comparing our graphical querying approach to an alternative querying tool, which produced positive results.

This paper showcases MDSheet, a framework aimed at improving the engineering of spreadsheets. This framework is model-driven, and has been fully integrated under a spreadsheet system. Also, its practical interest has been demonstrated by several empirical studies.

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Software refactoring is a well-known technique that provides transformations on software artifacts with the aim of improving their overall quality. In this paper we present a set of refactorings for ClassSheets, a modeling language that allows to specify the business logic of a spreadsheet in an object-oriented fashion. The set of refactorings that we propose allows us to improve the quality of these spreadsheet models. Moreover, it is implemented in a setting that guarantees that all model refactorings are automatically carried to all the corresponding (spreadsheet) instances, thus providing an automatic evolution of the data so it is always synchronized with the model.

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.

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.

This paper presents a domain-specific querying language for model-driven spreadsheets. We briefly show the design of the language and present in detail its implementation, from the denormalization of data and translation of our user-friendly query language to a more efficient query, to the execution of the query using Google. To validate our work, we executed an empirical study, comparing QuerySheet with an alternative spreadsheet querying tool, which produced positive results.

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.

A spreadsheet usually starts as a simple and single- user software artifact, but, as frequent as in other software systems, quickly evolves into a complex system developed by many actors. Often, different users work on different aspects of the same spreadsheet: while a secretary may be only involved in adding plain data to the spreadsheet, an accountant may define new business rules, while an engineer may need to adapt the spreadsheet content so it can be used by other software systems. Unfortunately, spreadsheet systems do not offer modular mechanisms, and as a consequence, some of the previous tasks may be defined by adding intrusive “code” to the spreadsheet.

In this paper we go through the design and implementation of an aspect-oriented language for spreadsheets so that users can work on different aspects of a spreadsheet in a modular way. For example, aspects can be defined in order to introduce new business rules to an existing spreadsheet, or to manipulate the spreadsheet data to be ported to another system. Aspects are defined as aspect-oriented program specifications that are dynamically woven into the underlying spreadsheet by an aspect weaver. In this aspect-oriented style of spreadsheet development, different users develop, or reuse, aspects without adding intrusive code to the original spreadsheet. Such code is added/executed by the spreadsheet weaving mechanism proposed in this paper.

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 well spreadsheets as they do not allow to express 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.

Software refactoring is a well-known technique that provides transformations on software artifacts with the aim of improving their overall quality.

In the past, we have proposed a catalog of refactoring 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 (the spreadsheet data) automatically co-evolves after a refactoring is applied at the model level. Our motivation for such research 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 presented not only in terms of productivity changes between refactored and non-refactored scenarios, but also in terms of overall user satisfaction, relevance, and experience.

In almost all cases the refactorings indeed improved end-users productivity. Moreover, in most cases users were more engaged with the refactored version of the spreadsheets they worked with.

This paper presents a detailed study of the energy consumption of the different Java Collection Framework (JFC) implementations. For each method of an implementation in this framework, we present its energy consumption when handling different amounts of data. Knowing the greenest methods for each implementation, we present an energy optimization approach for Java programs: based on calls to JFC methods in the source code of a program, we select the greenest implementation. Finally, we present preliminary results of optimizing a set of Java programs where we obtained 6.2% energy savings.