Abstract
Intensive research and development has been conducted in the design and creation of groupware systems for distributed users. While for some activities, these groupware tools are widely used, for other activities the impact in the groupware community has been smaller and can be improved. One reason for this fact is that the mostly common used applications do not support collaborative features and users are reluctant to change to a different application. In this paper we discuss how available file system mechanisms can help to address this problem. In this context, we present Forby, a system that allows to provide groupware features to distributed users by combining filesystem monitoring and distributed event dissemination. To demonstrate our solution, we present three systems that rely on Forby for providing groupware features to users running unmodified applications.

Abstract
Data aggregation plays an important role in the design of scalable systems, allowing the determination of meaningful system-wide properties to direct the execution of distributed applications. In the particular case of wireless sensor networks, data collection is often only practicable if aggregation is performed. Several aggregation algorithms have been proposed in the last few years, exhibiting different properties in terms of accuracy, speed and communication tradeoffs. Nonetheless, existing approaches are found lacking in terms of fault tolerance. In this paper, we introduce a novel fault-tolerant averaging based data aggregation algorithm. It tolerates substantial message loss (link failures), while competing algorithms in the same class can be affected by a Single lost message. The algorithm is based on manipulating flows (in the graph theoretical sense), that are updated using idempotent messages, providing it with unique robustness capabilities. Furthermore, evaluation results obtained by comparing it with other averaging approaches have revealed that it outperforms them in terms of time and message complexity.

Abstract
Functional programs often combine separate parts using intermediate data structures for communicating results. These programs are modular, easier to understand and maintain, but suffer from inefficiencies due to the generation of those gluing data structures. To eliminate such redundant data structures, some program transformation techniques have been proposed. One such technique is shortcut fusion, and has been studied in the context of both pure and monadic functional programs. Recently, we have extended standard shortcut fusion: in addition to intermediate structures, the program parts may now communicate context information, and it still is possible to eliminate those structures. This is achieved by transforming the original function composition into a circular program. This new technique, however, has been studied in the context of purely functional programs only. In this paper, we propose an extension to this new form of fusion,but in the context of monadic programming: we derive monadic circular p ograms from strict ones, maintaining the global effects. Later, the circularities in the derived programs are traded by highorder definitions, using a well-known program transformation technique. We finally obtain very efficient deforested programs. An important feature of our extensions is that they can beuniformly defined for a wide class of data types and monads, using generic calculation rules. ©2009 ACM.

Abstract
Graphical user interfaces (GUIs) make software easy to use by providing the user with visual controls. Therefore, correctness of GUI's code is essential to the correct execution of the overall software. Models can help in the evaluation of interactive applications by allowing designers to concentrate on its more important aspects. This paper presents a generic model for language-independent reverse engineering of graphical user interface based applications, and we explore the integration of model-based testing techniques in our approach, thus allowing us to perform fault detection. A prototype tool has been constructed, which is already capable of deriving and testing a user interface behavioral model of applications written in Java/Swing. Copyright 2009 ACM.

Abstract
This paper presents techniques and tools to transform spreadsheets into relational databases and back. A set of data refinement rules is introduced to map a tabular datatype into a relational database schema. Having expressed the transformation of the two data models as data refinements, we obtain for free the functions that migrate the data. We use well-known relational database techniques to optimize and query the data. Because data refinements define bidirectional transformations we can map such database back to an optimized spreadsheet. We have implemented the data refinement rules and we constructed HASKELL-based tools to manipulate, optimize and refactor Excel-like spreadsheets. ©2009 ACM.

Abstract
Spreadsheets can be viewed as a highly flexible end-users programming environment which enjoys wide-spread adoption. But spreadsheets lack many of the structured programming concepts of regular programming paradigms. In particular, the lack of data structures in spreadsheets may lead spreadsheet users to cause redundancy. loss, or corruption of data during edit actions. In this paper, we demonstrate how implicit structural properties of spreadsheet data can be exploited to offer edit assistance to spreadsheet users. Our approach is based on the discovery of functional dependencies among data items which allow automatic reconstruction of a relational database schema. From this schema. new formulas and visual objects are embedded into the spreadsheet to offer features for auto-completion, guarded deletion, and controlled insertion. Schema discovery and spreadsheet enhancement are carried out automatically in the background and do not disturb normal user experience.