Jácome Cunha

Algebraic theories for modeling components and their interactions offer abstraction over the specifics of component states and interfaces. For example, such theories deal with forms of sequential composition of two components in a manner independent of the type of data stored in the states of the components, and independent of the number and types of methods offered by the interfaces of the combinators. General purpose programming languages do not offer this level of abstraction, which implies that a gap must be bridged when turning component models into implementations. In this paper, we present an approach to prototyping of component-based systems that employs so-called type-level programming (or compile-time computation) to bridge the gap between abstract component models and their type-safe implementation in a functional programming language. We demonstrate our approach using Barbosa's model of components as generalized Mealy machines. For this model, we develop a combinator library in Haskell, which uses type-level programming with two effects. Firstly, wiring between components is computed during compilation. Secondly, the well-formedness of the component compositions is guarded by Haskell's strong type system.

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.

Spreadsheets are notoriously error-prone. To help avoid the introduction of errors when changing spreadsheets, models that capture the structure and inter-dependencies of spreadsheets at a conceptual level have been proposed. Thus, spreadsheet evolution can be made safe within the confines of a model. As in any other model/instance setting, evolution may not only require changes at the instance level but also at the model level. When model changes are required, the safety of instance evolution can not be guarded by the model alone. Coupled transformation of models and instances are supported by the 2LT platform and have been applied for transformation of algebraic datatypes, XML schemas, and relational database models. We have extended 2LT to spreadsheet evolution. We have designed an appropriate representation of spreadsheet models, including the fundamental notions of formulæ, references, and blocks of cells. For these models and their instances, we have designed coupled transformation rules that cover specific spreadsheet evolution steps, such as extraction of a block of cells into a separate sheet or insertion of columns in all occurrences of a repeated block of cells. Each model-level transformation rule is coupled with instance level migration rules from the source to the target model and vice versa. These coupled rules can be composed to create compound transformations at the model level that induce compound transformations at the instance level. With this approach, spreadsheet evolution can be made safe, even when model changes are involved.