Domain Specific Modeling Languages (DSML) significantly improve productivity in designing Computer Based System (CBS), by enabling them to be modeled at higher levels of abstraction. It is common for large and complex systems with distributed teams, to use DSMLs, to express and communicate designs of such systems uniformly, using a common language. DSMLs enable domain experts, with no or minimal software development background, to model solutions, using the language and terminologies used in their respective domains. Although, there are already a number of DSMLs available for modeling CBSs, their need is felt strongly across multiple domains, which still are not well supported with DSMLs. Developing a new DSML, however, is non trivial, as it requires (a) significant knowledge about the domain for which the DSML needs to be developed, as well as (b) skills to create new languages. In the current practice, DSMLs are developed by experts, who have substantial understanding of the domain of interest and strong background in computer science. One of the many challenges in the development of DSMLs, is the collection of domain knowledge and its utilization, based on which the abstract syntax, the backbone of the DSML is defined. There is a clear gap in the current state of art and practice, with respect to overcoming this challenge. We propose a methodology, which makes it easier for people with different backgrounds such as domain experts, solution architects, to contribute towards defining the abstract syntax of the DSML. The methodology outlines a set of steps to systematically capture knowledge about the domain of interest, and use that to arrive at the abstract syntax of the DSML. The key contribution of our work is in abstracting a CBS from a domain into a Domain Specific Machine, embodied in domain specific concepts. The methodology outlines, how the Domain Specific Machine, when coupled with guidelines from current practices of developing DSMLs, results in the definition of the abstract syntax of the intended DSML. We discuss our methodology in detail, in this paper.

As more and more enterprises are looking forward to leveraging the connected network of Facebook to capture inputs and feedback on their brands, it is becoming increasingly important to mine the unstructured information from Facebook. The recent advances in open source software technologies in the map reducing paradigm opens up a whole new opportunity for such advanced analytics. This paper illustrates the use of open source technologies for brand sentiment analysis from Facebook data.

At the Rochester Institute of Technology, the undergraduate introductory software engineering course has been redesigned from a lecture-lab format to a project-centric studio format. The new format blends the lecture material with the project work. As a result, students drive their own learning experience based on scaffolding created by the course design. The challenges faced and the techniques and strategies utilized in the planning and delivery of the course will be discussed, including the utilization of online learning support infrastructure. This paper presents instructor experiences, analysis of student feedback, lessons learned and recommendations for other educators considering an active learning approach for their courses.

Abstract Multicast services have been used to transmit multimedia data to large receiver groups. Only recently have counterpart network services been introduced to provide similar scalability and anonymity in the opposite direction (i.e. messages from a group of senders destined for a common receiver). In this paper, we explore how these many‐to‐one services, specifically the concast service, can be used to improve the scalability and performance of multimedia applications. In particular, we show how such services can be used in both the control and data planes to overcome well‐known scalability problems (e.g. with Real Time Protocol) that are difficult to solve effectively with end‐system approaches alone. We validate our solutions by presenting experimental results taken from prototype video and audio applications we designed and implemented. Our initial results show substantial reductions in congestion‐induced loss using these generic services. Copyright © 2003 John Wiley & Sons, Ltd.

Multicast services have been used for many years to transmit multimedia data to large receiver groups. However, only recently have counterpart network services been introduced that provide similar scalability and anonymity in the opposite direction (i.e., messages from a group of senders destined for a common receiver). In this paper, we explore how these emerging services, specifically a concast service (many-to-one communication service), can be used to improve the scalability and performance of multimedia applications. In particular, we show how such services can be used in both the control and data planes to overcome well-known scalability problems (e.g., with RTP) that are difficult to solve effectively with end-system approaches alone. We validate our solutions by presenting experimental results taken from prototype video and audio applications we designed and implemented. Our initial results show a reduction of as much as two orders of magnitude in packet loss rates using these generic services.

The timing constraint mechanism in a real-time programming language called FLEX is described. A FLEX program can use the constraint primitives to express timing and resource requirements. If the required time or resources are not available at run-time, a FLEX program can dynamically produce monotonic imprecise results. Both time and system resources are defined as first-class objects in the language so that they can be evaluated just like any other first-class object. By unifying time, resources, and normal objects, the semantics and the executions of real-time programs are more manageable. Some implementation issues for FLEX are discussed, and some performance data are presented.>