Abstract
Currently, systematic techniques for assessing macro mechanisms for transferring software engineering technologies are non-existent. This leads to inefficient allocation of research resources and increased risk to software technology intensive programs. Consequently, software technology transition today is an ill-defined and non-repeatable, inefficient process for bringing advanced software engineering technologies to market. This paper develops two dynamical models of a software technology transition from both macroscopic and microscopic views. The models are developed utilizing information theory, communication theory, chaos control theory, and learning curve principles. The combination of those scientifically sound mechanisms provides a basis for assessing, and/or prescribing a portfolio of technologies and the implementing macro infrastructure. This provides the theoretical framework for a practical method for a program manager to establish a high capacity transition channel, which accelerates technology maturation and insertion. Experiments based on very large number of data have been performed. Data samples assess the following technologies: software engineering, software technology transfer, Ada, Java, abstract data types, rate monotonic analysis, cost models, software standards, and software work breakdown structures.
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