Software Process Selection Based Upon Abstract Machines for Slow Intelligence Systems

摘要

The abstract-machine model was developed by Chang to formalize the decision cycles of slow intelligence systems. It turns out that the selection of software process can also be regarded as a slow intelligence system. In this paper, we formalize abstract-machine prototypes for different software process models (SPMs) such as waterfall model, incremental model, spiral model, extreme programming model and scrum model. A Software Process Generator (SPG) was implemented to generate SPMs based upon design considerations. Initial evaluation by undergraduate students using SPG to learn software processes suggests further improvements to make it a useful learning tool.