A Generative Approach to Searching Algorithmic Programs Development
Haihe Shi, Jinyun Xue · 2011
Using highly configurable semi-automatic approach to algorithmic programs development can improve correctness and productivity. This paper explores a way to use generative techniques to produce the algorithmic programs for searching problem. Based on PAR method and PAR platform, it is to formally develop generic type component and algorithm components, and to design a formal algorithm generative model that models an invariant behavior in terms of variant behaviors, and then to automatically generate a variety of specialized searching algorithmic programs through replacing the generic identifiers with a few concrete operations. Through the super framework and underlying components, the reliability and productivity of domain specific algorithms are dramatically improved.