A Double k-clustering approach for restructuring Distributed Object-Oriented software - Hamad, S.H.; Fergany, T.; Ammar, R.A.; El-Raouf, A.A.A. (2008)
There have been a large number of projects based on the Distributed Object Oriented (DOO) approach for solving complex problems in various scientific fields. The Mismatch problem is one of the most important problems facing the DOO system, where the initial design of the DOO application does not give the best class distribution. In such a case, the DOO software may need to be restructured. In this paper, we propose a methodology for efficiently restructuring the DOO software classes to be mapped on a distributed system consisting of a set of nodes. The proposed methodology consists of two phases. The first phase introduces a recursive graph clustering technique to partition the OO system into subsystems with low coupling. The second phase is concerned with mapping the generated partitions to the set of available machines in the target distributed architecture. A simulation evaluation was carried out for a set of randomly generated DOO software designs. Then the results were compared with those of the K-Partitioning algorithm in terms of the overall inter-class communication cost. © 2008 IEEE.
Keywords: Class distributions; Clustering approaches; Communication costs; Complex problems; Computer software; Distributed architectures; Distributed objects; Distributed systems; Flow of solids; Graph clustering; Initial designs; Low couplings; Mismatch problems; Object oriented programming; Oo systems; Partitioning algorithms; Problem solving; Scientific fields; Simulation evaluations; Software design; Sub systems; Two phases; dept.csc

Collaboration tools in a one-semester software engineering course: what worked? what didn't? - Lancor, Lisa (Journal of Computing Sciences in Colleges, 2008)
Keywords: dept.csc; ⛔ No DOI found

Data analyis system design for lidar experimentation - Sharma, Nimmi C P; Parikh, Jo Ann (Institute of Electrical and Electronics Engineers Inc., 2008)
A web-based lidar experimentation and data analysis system (LEDAS) was developed, with support from a National Science Foundation award, to support resource sharing of lidar equipment, datasets and data analysis routines and collaboration between members of the Connecticut State University System (CSUS) Lidar Collaboratory. The system allows users at different geographical locations to conduct remote sensing research and education over the Web through remote access and control of a single shared lidar system and web-based data analysis. Users need not have any specialized instrumentation or software at their institutions, thereby making real remote sensing research available to students and faculty from institutions which may not have the internal budgets for such facilities. An original structure providing basic functionality was developed and implemented. This paper describes the second generation data analysis system which provides significant new enhancements and capabilities. © 2008 IEEE.
Keywords: Access control; Budget control; Collaboratories; Data analysis; Data analysis system; Data reduction; Education; Geographical locations; Geology; Information analysis; National Science Foundations; Optical radar; Original structures; Remote control; Remote sensing; Resource sharing; Second generation; University system; Websites; dept.csc; lidar