Discovering coordination patterns

A large and growing amount of software systems rely on non-trivial coordination logic for making use of third party services or components. Therefore, it is of outmost importance to understand and capture rigorously this continuously growing layer of coordination as this will make easier not only the veri cation of such systems with respect to their original speci cations, but also maintenance, further development, testing, deployment and integration. This paper introduces a method based on several program analysis techniques (namely, dependence graphs, program slicing, and graph pattern analysis) to extract coordination logic from legacy systems source code. This process is driven by a series of pre-de ned coordination patterns and captured by a special purpose graph structure from which coordination speci cations can be generated in a number of di erent formalisms

Slicing for architectural analysis

Current software development often relies on non-trivial coordination logic for combining autonomous services, eventually running on different platforms. As a rule, however, such a coordination layer is strongly woven within the application at source code level. Therefore, its precise identification becomes a major methodological (and technical) problem and a challenge to any program understanding or refactoring process. The approach introduced in this paper resorts to slicing techniques to extract coordination data from source code. Such data are captured in a specific dependency graph structure from which a coordination model can be recovered either in the form of an Orc specification or as a collection of code fragments corresponding to the identification of typical coordination patterns in the system. Tool support is also discussed

Dense motion field estimation from myocardial boundary displacements

Minimally invasive cardiovascular interventions guided by multiple imaging modalities are rapidly gaining clinical acceptance for the treatment of several cardiovascular diseases. These images are typically fused with richly detailed pre-operative scans through registration techniques, enhancing the intra-operative clinical data and easing the image-guided procedures. Nonetheless, rigid models have been used to align the different modalities, not taking into account the anatomical variations of the cardiac muscle throughout the cardiac cycle. In the current study, we present a novel strategy to compensate the beat-to-beat physiological adaptation of the myocardium. Hereto, we intend to prove that a complete myocardial motion field can be quickly recovered from the displacement field at the myocardial boundaries, therefore being an efficient strategy to locally deform the cardiac muscle. We address this hypothesis by comparing three different strategies to recover a dense myocardial motion field from a sparse one, namely, a diffusion-based approach, thin-plate splines, and multiquadric radial basis functions. Two experimental setups were used to validate the proposed strategy. First, an in silico validation was carried out on synthetic motion fields obtained from two realistic simulated ultrasound sequences. Then, 45 mid-ventricular 2D sequences of cine magnetic resonance imaging were processed to further evaluate the different approaches. The results showed that accurate boundary tracking combined with dense myocardial recovery via interpolation/ diffusion is a potentially viable solution to speed up dense myocardial motion field estimation and, consequently, to deform/compensate the myocardial wall throughout the cardiac cycle. Copyright © 2015 John Wiley & Sons, Ltd.