NJIT eTD: The New Jersey Institute of Technology's electronic Theses & Dissertations
Title:
Characterizing the evolution of operating systems
Author:
Peng, Yi
Document Type:
Dissertation
Department:
Department of Computer Science
Degree:
Doctor of Philosophy
Major:
Computer Science
Advisory Committee:
Mili, Ali
Leung, Joseph Y-T.
Theodoratos, Dimitri
Oria, Vincent
Li, Fu
Thesis Date:
2005, January
Keywords:
Tech watch
Operating systems
Software engineering trends
Windows
Linux
IBM Aix
Availability:
Unrestricted
Abstract:

Examining the development and trends in software engineering technology is a huge undertaking. It is constantly evolving and affected by a large number of factors, which are themselves driven by a wide range of sub-factors. This dissertation is part of a long term project intended to analyze software engineering technology trends and how they evolve. This project is intended to analyze operating system trends and what are the factors that drive how they evolve. Basically, the following questions will be answered: "How to watch, predict, adapt to, and affect operating system's evolution trends?"

In previous research, YF Chen used statistical models to analyze the evolution of programming languages. Building upon Chen's work, the author uses operating systems as the subject, derives the statistical models and applies them to analyze the trend and the relationships between different factors that characterize an operating system.

After the history of several operating systems is reviewed, it shows that two kinds of factors, intrinsic factors and extrinsic factors, could affect the evolution of an operating system. Intrinsic factors are used to describe the general design criteria of an operating system. On the other hand, extrinsic factors are the factors that are not directly related to the general attributes of an operating system. In order to describe the relationship of these factors and how they affect operating system trends, they need to be quantified. For intrinsic factors, data are collected from different trustable data sources and analyzed. For extrinsic factors, historical data are collected and established as a data warehouse. The operating system trends are described and evaluated by using all the data that have been collected and analyzed.

In this dissertation, statistical methods are used to describe historical operating system trends and predict the future trends. Several statistics models are constructed to describe the relationships among these factors. Canonical correlation is used to do the factor analysis. Multivariate multiple regression method has been used to construct the statistics models for the evolution of operating system trends. The models are validated by comparing the predicted data with the actual data.

Complete Thesis:
njit-etd2005-034 (142 pages ~ 12,849 KB pdf)
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Created April 25, 2005
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