Showing papers on "Gnome published in 2012"

Human Sensor Networks for Improved Modeling of Natural Disasters

Abstract: In this paper, we present a novel approach that views social media (SM) data as a human sensor network. These data can serve as a low-cost augmentation to an observing system, which can be incorporated into geophysical models together with other scientific data such as satellite observations and sensor measurements. As a use case scenario, we analyze the Deepwater Horizon oil spill disaster. We gather SM data that mention sightings of oil from Flickr, geolocate them, and use them as boundary forcings in the General NOAA Oil Modeling Environment (GNOME) software for oil spill predictions. We show how SM data can be incorporated into the GNOME model to obtain improved estimates of the model parameters such as rates of oil spill, couplings between surface winds and ocean currents, diffusion coefficient, and other model parameters.

Investigating the architectural drivers of defects in open-source software systems : an empirical study of defects and reopened defects in GNOME

Abstract: In major software systems that are developed by competent software engineers, the existence of defects in production is unlikely to be an acceptable situation. And yet, we find that in several such systems, defects remain a reality. Furthermore, the number of changes that are fixed only to then be reopened is noticeable. The implications of having defects in a system can be frustrating for all stakeholders, and when they require constant rework, they can lead to the problematic code-test-code-test mode of development. For management, such conditions can result in slipped schedules and an increase in development costs and for upper management and users, they can result in losing confidence in the product. This study looks at the drivers of defects in the mature open-source project GNOME and explores the relationship between the various drivers of these defects and software quality. Using defect-activity and source-code data for 32 systems over a period of eight years, the work presents a multiple regression model capable of explaining 16.2% of defects and a logistic regression model capable of explaining between 13.6% and 18.1% of reopened defects. The study also shows that although defects in general and reopened defects appear to move together, defects in general correlate with a measure of complexity that captures how components connect to each other whereas reopened defects correlate with a measure that captures the inner complexities of components, thereby suggesting that different types of defects are correlated with different forms of complexity. Thesis advisor: Alan D. MacCormack Title: Adjunct Professor, Harvard Business School, Harvard University Formerly, Visiting Associate Professor, Sloan School of Management

Gnome, sweet gnome

Abstract: I read the article "Weighty issues" (May p3) on the travels of Kern the gnome with interest, and was struck by the implication that the gnome's mass depends on its location on the Earth.