On the discovery of business processes orchestration patterns

COORDINSPECTOR is a Software Tool aiming at extracting the coordination layer of a software system. Such a reverse engineering process provides a clear view of the actually invoked services as well as the logic behind such invocations. The analysis process is based on program slicing techniques and the generation of, System Dependence Graphs and Coordination Dependence Graphs. The tool analyzes Common Intermediate Language (CIL), the native language of the Microsoft .Net Framework, thus making suitable for processing systems developed in any .Net Framework compilable language. COORDINSPECTOR generates graphical representations of the coordination layer together with business process orchestrations specified in WSBPEL 2.0

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

Domain-Specific Language for Coordination patterns

The integration and composition of software systems requires a good architectural design phase to speed up communications between (remote) components. However, during implementation phase, the code to coordinate such components often ends up mixed in the main business code. This leads to maintenance problems, raising the need for, on the one hand, separating the coordination code from the business code, and on the other hand, providing mechanisms for analysis and comprehension of the architectural decisions once made. In this context our aim is at developing a domain-specific language, CoordL, to describe typical coordination patterns. From our point of view, coordination patterns are abstractions, in a graph form, over the composition of coordination statements from the system code. These patterns would allow us to identify, by means of pattern-based graph search strategies, the code responsible for the coordination of the several components in a system. The recovering and separation of the architectural decisions for a better comprehension of the software is the main purpose of this pattern language

Robust temporal alignment of multimodal cardiac sequences

Given the dynamic nature of cardiac function, correct temporal alignment of pre-operative models and intraoperative images is crucial for augmented reality in cardiac image-guided interventions. As such, the current study focuses on the development of an image-based strategy for temporal alignment of multimodal cardiac imaging sequences, such as cine Magnetic Resonance Imaging (MRI) or 3D Ultrasound (US). First, we derive a robust, modality-independent signal from the image sequences, estimated by computing the normalized crosscorrelation between each frame in the temporal sequence and the end-diastolic frame. This signal is a resembler for the left-ventricle (LV) volume curve over time, whose variation indicates di erent temporal landmarks of the cardiac cycle. We then perform the temporal alignment of these surrogate signals derived from MRI and US sequences of the same patient through Dynamic Time Warping (DTW), allowing to synchronize both sequences. The proposed framework was evaluated in 98 patients, which have undergone both 3D+t MRI and US scans. The end-systolic frame could be accurately estimated as the minimum of the image-derived surrogate signal, presenting a relative error of 1:6 1:9% and 4:0 4:2% for the MRI and US sequences, respectively, thus supporting its association with key temporal instants of the cardiac cycle. The use of DTW reduces the desynchronization of the cardiac events in MRI and US sequences, allowing to temporally align multimodal cardiac imaging sequences. Overall, a generic, fast and accurate method for temporal synchronization of MRI and US sequences of the same patient was introduced. This approach could be straightforwardly used for the correct temporal alignment of pre-operative MRI information and intra-operative US images.