Object-based Control/Data-flow Analysis

Not only does a clear distinction between control and data flow enhance the readability of models, but it also allows different tools to operate on the two distinct parts of the model. This paper shows how the modelling based on control/data-flow analysis can benefit from an object-based approach. We have developed a translation mechanism that is faithful and gives an extra dimension (hierarchy) to the existing paradigm of control and data flow interacting in a model. Our methodology provides a comprehensible separation of these two parts, which can be used to feed another analysis or synthesis tools, while still being able to reason about both parts through formal methods of verification

Rigid tool affordance matching points of regard

In this abstract we briefly introduce the analysis of simple rigid object affordance by experimentally establishing the relation between the point of regard of subjects before grasping an object and the finger tip points of contact once the object is grasped. The analysis show that there is a strong relation between these data, in so justifying the hypothesis that people figures out how objects are afforded according to their functionality

The Secrets of Salient Object Segmentation

In this paper we provide an extensive evaluation of fixation prediction and salient object segmentation algorithms as well as statistics of major datasets. Our analysis identifies serious design flaws of existing salient object benchmarks, called the dataset design bias, by over emphasizing the stereotypical concepts of saliency. The dataset design bias does not only create the discomforting disconnection between fixations and salient object segmentation, but also misleads the algorithm designing. Based on our analysis, we propose a new high quality dataset that offers both fixation and salient object segmentation ground-truth. With fixations and salient object being presented simultaneously, we are able to bridge the gap between fixations and salient objects, and propose a novel method for salient object segmentation. Finally, we report significant benchmark progress on three existing datasets of segmenting salient objectsComment: 15 pages, 8 figures. Conference version was accepted by CVPR 201

Composing concurrent objects

Adopting the object-oriented paradigm for the development of large and complex software systems offers several advantages, of which increased extensibility and reusability are the most prominent ones. The object-oriented model is also quite suitable for modelling concurrent systems. However, it appears that extensibility and reusability of concurrent applications is far from trivial. In addition, very little attention has been paid by the conventional object-oriented development methodologies to the analysis and design of\ud synchronisation constraints for concurrent objects.\ud To address these problems, in this thesis the framework of composition-filters, an extension to the object-oriented model, is adopted. An analysis is presented of the problems involved in reusing and extending concurrent objects, in particular the so-called inheritance anomalies. Based on this analysis, a set of criteria for effective extensible concurrent objectoriented\ud programming languages is formulated.\ud The thesis introduces techniques for the creation of concurrency and the synchronisation of concurrent activities, fully integrated within the (object-oriented) composition-filters model. Important properties of the proposed object model are: all objects are -potentially- active, intra-object concurrency is supported and synchronisation specifications are fully separated\ud from method implementations. The applicability and expressive power of the proposed technique are demonstrated, and it is shown how reusability and extensibility of concurrent objects are achieved

An Object-Oriented Framework for Robust Multivariate Analysis

Taking advantage of the S4 class system of the programming environment R, which facilitates the creation and maintenance of reusable and modular components, an object-oriented framework for robust multivariate analysis was developed. The framework resides in the packages robustbase and rrcov and includes an almost complete set of algorithms for computing robust multivariate location and scatter, various robust methods for principal component analysis as well as robust linear and quadratic discriminant analysis. The design of these methods follows common patterns which we call statistical design patterns in analogy to the design patterns widely used in software engineering. The application of the framework to data analysis as well as possible extensions by the development of new methods is demonstrated on examples which themselves are part of the package rrcov.

A theorem prover-based analysis tool for object-oriented databases

We present a theorem-prover based analysis tool for object-oriented database systems with integrity constraints. Object-oriented database specifications are mapped to higher-order logic (HOL). This allows us to reason about the semantics of database operations using a mechanical theorem prover such as Isabelle or PVS. The tool can be used to verify various semantics requirements of the schema (such as transaction safety, compensation, and commutativity) to support the advanced transaction models used in workflow and cooperative work. We give an example of method safety analysis for the generic structure editing operations of a cooperative authoring system