Supporting process reuse in PROMENADE

Process reuse (the ability to construct new processes by assembling already built ones) and process harvesting (the ability to build generic processes that may be further reused, from existing ones) are two crucial issues in process technology. Both activities involve defining a set of mechanisms, like abstraction, adaptation, composition, etc. which are appropriate to achieve their goals. In this report, we define a general framework to process reuse and harvesting that proposes a complete set of mechanisms to deal with both activities. This general framework is particularized to the context of a process modelling language to model software processes, called PROMENADE. A definition of the identified reuse and harvesting mecha-nisms is proposed in the context of PROMENADE. Finally, two process reuse case studies which composes various reuse mechanisms are presented.Postprint (published version

Enhancing the orbital utilization of expendable launch vehicles

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1988, and (M.S.)--Massachusetts Institute of Technology, Technology and Policy, 1988.Vita.Includes bibliographical references.by Douglas Allen Comstock.M.S

Managing Evolutionary Method Engineering by Method Rationale

This paper explores how to integrate formal meta-models with an informal method rationale to support evolutionary (continuous) method development. While the former provides an exact and computer-executable specification of a method, the latter enables concurrent learning, expansion, and refinement of method use (instances of meta-models) and meta-models (evolution of method specifications). We explain the need for method rationale by observing the criticality of evolving method knowledge in helping software organizations to learn, as well as by the recurrent failure to introduce rigid and stable methods. Like a design rationale, a method rationale establishes a systematic and organized trace of method evolution. Method rationale is located at two levels of type-instance hierarchy depending on its type of use and the scope of the changes traced. A method construction rationale garners a history of method knowledge evolution as part of the method engineering process, which designs and adapts the method to a given organizational context. A method use rationale maintains knowledge of concrete use contexts and their history and justifies further method deployment in alternative contexts, reveals limitations in its past use, and enables sharing of method use experience. The paper suggests how a method rationale helps share knowledge of methods between method users and engineers, explores how method engineers coordinate the evolution of the existing method base through it, and suggests ways to improve learning through method rationale

Automated Analysis of Stateful Feature Models

In CAiSE 2005, we interpreted the extraction of relevant information from extended feature models as an automated reasoning problem based on constraint programming. Such extraction is driven by a catalogue of basic and compound operations. Much has been done since, renaming the problem as the automated analysis of feature models, a widely accepted problem in the Software Product Line (SPL) community. In this chapter, we review this seminal contribution and its impact in the community, highlighting the key milestones up to a more complete problem formulation that we coin as the Automated Analysis of Stateful Feature Models (AASFM). Finally, we envision some breakthroughs and challenges in the AASFM.Ministerio de Ciencia e Innovación TIN2009- 07366Junta de Andalucía TIC-590

STATE PROPAGATION FOR BUSINESS PROCESS MONITORING ON DIFFERENT LEVELS OF ABSTRACTION

Modeling and execution of business processes is often performed on different levels of abstraction. For example, when a business process is modeled using a high-level notation near to business such as Event-driven Process Chains (EPC), a technical refinement step is required before the process can be executed. Also, model-driven process design allows modeling a process on high-level, while executing it in a more detailed and executable low-level representation such as processes defined in the Business Process Execution Language (BPEL) or as Java code. However, current approaches for graphical monitoring of business processes are limited to scenarios in which the process that is being executed and the process that is being monitored are either one and the same or on the same level of abstraction. In this paper, we present an approach to facilitate business-oriented process monitoring while considering process design on high-level. We propose process views for business process monitoring as projections of activities and execution states in order to support business process monitoring of running process instances on different levels of abstraction. In particular, we discuss state propagation patterns which can be applied to define advanced monitoring solutions for arbitrary graph-based process languages

Silicon Photonic Platforms and Systems for High-speed Communications

Data communication is a critical component of modern technology in our society. There is an increasing reliance on information being at our fingers tips and we expect a low-latency, high-bandwidth connection to deliver entertainment or enhanced productivity. In order to serve this demand, communications devices are being pressed for smaller form factors, higher data throughput, lower power consumption and lower cost. Similar demands exist in a number of applications including metro/long-haul telecommunications, shorter datacenter links and supercomputing. Silicon photonics promises to be a technology that will solve some of the difficulties with improving communication devices. Building photonics in silicon allows for reuse of the same fabrication technology that is used by the CMOS electronics industry, potentially allowing for large volumes, high yields and low costs. Part I of this thesis details the design of components needed in a high-speed silicon photonic platform to meet the current challenges for high-speed communications. The author’s work in modeling photodetectors resulted in improving photodetector bandwidth from 30 GHz to 67 GHz, the fastest reported at the time of publication. Details regarding the optimization and test of modulators are also presented with the first-reported 50 Gbps modulator at 1310-nm. A large scale parallel channel demonstration of high-speed silicon photonics is then presented showing the potential scalability for silicon photonics systems. A full transceiver requires a number of components other than the photodetector and modulator that are the core active pieces of a silicon photonics platform. Part II includes work on the design and test of silicon photonic components providing functionality beyond the photodetector and modulator. A novel design integrating Metal-Semiconductor Field Effect Transistors (MESFETs) into a silicon photonics platform without process change is shown. This integration enables enhanced control functionality with minimal overhead. The critical final piece for a silicon photonics platform, adding a light source, is demonstrated along with performance results of the resulting tunable, extended C-band laser. In Part III, previous work on an enhanced silicon photonics platform with complementary components is used to build a high-speed integrated coherent link and then tested with a silicon photonics-based tunable laser. The transceiver was shown to operate at 34 Gbaud dual-polarization 16-QAM for a total of 272 Gbps over a single channel. This was the first published demonstration of an integrated coherent where all of the optics were built in a silicon photonics platform

Fast feature matching for detailed point cloud generation

Structure from motion is a very popular technique for obtaining three-dimensional point cloud-based reconstructions of objects from un-organised sets of images by analysing the correspondences between feature points detected in those images. However, the point clouds stemming from usual feature point extractors such as SIFT are frequently too sparse for reliable surface recovery. In this paper we show that alternate feature descriptors such as A-KAZE, which provide denser coverage of images, yield better results and more detailed point clouds. Unfortunately, the use of a dramatically increased number of points per image poses a computational challenge. We propose a technique based on epipolar geometry restrictions to significantly cut down on processing time and an efficient implementation thereof on a GPU