Motivators of adopting social computing in global software development: Initial results

context: Real-time collaboration is critical for developing high quality software systems at low cost in a geographically distributed Global Software Development (GSD) environment. It is anticipated that emerging Social Computing tools can play an important role in facilitating realtime effective collaboration among teams working in the GSD. Objective: The objective of this research paper is to identify motivators for adopting social computing in GSD organizations. Method: We adopted a Systematic Literature Review (SLR) approach by applying customized search strings derived from our research questions. Results: We have identified factors such as real-time communication and coordination, information sharing, knowledge acquisition and expert feedback as key motivators for adoption of social computing in GSD. Conclusion: Based on the SLR results, we suggest that GSD organizations should embrace social computing as a tool for real-time collaboration between distributed GSD teams. The results of this initial study also suggest the need for developing the social computing strategies and policies to guide the effective social computing adoption by GSD teams

How Do Developers Refactor Code to Improve Code Reusability?

. Refactoring is the de-facto practice to optimize software health. While there has been several studies proposing refactoring strategies to optimize software design through applying design patterns and removing design defects, little is known about how developers actually refactor their code to improve its reuse. Therefore, we extract, from 1,828 open source projects, a set of refactorings which were intended to improve the software reusability. We analyze the impact of reusability refactorings on state-of-the-art reusability metrics, and we compare the distribution of reusability refactoring types, with the distribution of the remaining mainstream refactorings. Overall, we found that the distribution of refactoring types, applied in the context of reusability, is different from the distribution of refactoring types in mainstream development. In the refactorings performed to improve reusability, source files are subject to more design level types of refactorings. Reusability refactorings significantly impact, high-level code elements, such as packages, classes, and methods, while typical refactorings, impact all code elements, including identifiers, and parameter

EVE: An Environment for On-board Processing

The Information Technology and Systems Center (ITSC) at The University of Alabama in Huntsville (UAH) is investigating and developing an innovative processing system capable of handling the unique constraints and characteristics of the on-board satellite data and information environment. The EnVironmEnt for On-Board Processing (EVE) system will serve as a proof-of-concept of advanced information systems technology for remote sensing platforms. EVE’s on-board, real-time processing will provide capabilities focused on the areas of autonomous data mining, classification and feature extraction. These will contribute to Earth Science research applications, including natural hazard detection and prediction, fusion of multi-sensor measurements, ntelligent sensor control, and the generation of customized data products for direct distribution to users. EVE is being engineered to provide high performance data processing in a real-time operational environment. A ground-based testbed is being created to provide testing of EVE and associated Earth Science applications in a heterogeneous embedded hardware and software environment

EVE: On-Board Process Planning and Execution

The Information Technology and Systems Center (ITSC) at The University of Alabama in Huntsville(UAH) has designed and is now developing an innovative processing framework aimed at helping science users exploit the unique constraints and characteristics of the on-board satellite data and information environment. The Environment for On-Board Processing (EVE) system will serve as a proof-of-concept of advanced information systems technology for remote sensing platforms. Because data will be processed as it’s collected, such a system will produce custom data products on-board and in real-time. First, the EVE editor allows science users to build processing plans, which are compatible with the constraints of on-orbit computing environments. The EVE on-board, real-time processing infrastructure in turn, will upload, schedule, and control the execution of these plans. Operations within the plans provide capabilities focused on the areas of autonomous data mining, classification and feature extraction. These will contribute to Earth Science research applications, including natural hazard detection and prediction, fusion of multi-sensor measurements, intelligent sensor control, and the generation of customized data products for direct distribution to users. A ground-based testbed is being created to provide testing of EVE and associated Earth Science applications in a heterogeneous embedded hardware and software environment

EVE: An Environment for On-board Processing

The Information Technology and Systems Center (ITSC) at The University of Alabama in Huntsville (UAH) is investigating and developing an innovative processing system capable of handling the unique constraints and characteristics of the on-board satellite data and information environment. The EnVironmEnt for On-Board Processing (EVE) system will serve as a proof-of-concept of advanced information systems technology for remote sensing platforms. EVE’s on-board, real-time processing will provide capabilities focused on the areas of autonomous data mining, classification and feature extraction. These will contribute to Earth Science research applications, including natural hazard detection and prediction, fusion of multi-sensor measurements, ntelligent sensor control, and the generation of customized data products for direct distribution to users. EVE is being engineered to provide high performance data processing in a real-time operational environment. A ground-based testbed is being created to provide testing of EVE and associated Earth Science applications in a heterogeneous embedded hardware and software environment

EVE: On-Board Process Planning and Execution

Abstract The Information Technology and Systems Center (ITSC) at The University of Alabama in Huntsville is developing an innovative processing framework aimed at assisting science users in the use of the unique constraints and characteristics of the on-board satellite data and information environment. The Environment for On-Board Processing (EVE) system serves as a proof-of-concept of advanced information systems technology for remote sensing platforms. With EVE, data is processed as it is collected, enabling the production of custom data products on-board and in real-time. The web-based drag-and-drop EVE editor allows science users to build processing plans, which are compatible with the constraints of on-board computing environments. The EVE onboard, real-time processing infrastructure, will upload, schedule, and control the execution of these plans. Operations within the plans provide capabilities focused on the areas of autonomous data mining, classification and feature extraction using both streaming and buffered data sources. These will contribute to science research applications, including natural hazard detection and prediction, fusion of multi-sensor measurements, intelligent sensor control, and the generation of customized data products for direct distribution to users. A ground-based testbed has been created to provide testing of EVE and associated science applications in a heterogeneous, embedded hardware and software environment. Testbed components include platforms that represent both space based and ground based sensor platforms, including wireless sensor mesh architectures

Earth Science Markup Language: A Solution for Generic Access to Heterogeneous Data Sets

The Earth Science community is processing and analyzing a large amount and variety of data. These data are generally stored in different data formats, which forces the scientists to spend a significant amount of time in writing specialized, data format specific readers. However, this preprocessing burden can by alleviated by using the Earth Science Markup Language (ESML). ESML is a specialized markup language for Earth Science metadata. Based on the eXtensible Markup Language (XMLTM), ESML allows data descriptions to be written in a standard fashion

On-Board Mining in the Sensor Web

The Information Technology and Systems Center (ITSC) at The University of Alabama in Huntsville (UAH) has designed and is now developing an innovative processing framework aimed at assisting science users exploit the unique constraints and characteristics of the on-board satellite data and information environment. The Environment for On-Board Processing (EVE) system will serve as a proof-of-concept of advanced information systems technology for remote sensing platforms. Because data will be processed as it is collected, such a system will produce custom data products on-board and in real-time. First, the EVE editor allows science users to build processing plans, which are compatible with the constraints of on-board computing environments. The EVE on-board, real-time processing infrastructure in turn, will upload, schedule, and control the execution of these plans. Operations within the plans provide capabilities focused on the areas of autonomous data mining, classification and feature extraction using both streaming and buffered data sources. These will contribute to science research applications, including natural hazard detection and prediction, fusion of multi-sensor measurements, intelligent sensor control, and the generation of customized data products for direct distribution to users. A ground-based testbed is being created to provide testing of EVE and associated Earth Science applications in a heterogeneous embedded hardware and software environment

Earth Science Markup Language: A Solution for Generic Access to Heterogeneous Data Sets

The Earth Science community is processing and analyzing a large amount and variety of data. These data are generally stored in different data formats, which forces the scientists to spend a significant amount of time in writing specialized, data format specific readers. However, this preprocessing burden can by alleviated by using the Earth Science Markup Language (ESML). ESML is a specialized markup language for Earth Science metadata. Based on the eXtensible Markup Language (XMLTM), ESML allows data descriptions to be written in a standard fashion