Code synthesis is routinely used in industry to generate GUIs, form lling applications, and database support code and is even used with COBOL. In this paper we consider the question of whether code synthesis could also be applied to the data mining phase of knowledge discovery. We view this as a rapid prototyping method. Rapid prototyping of statistical data analysis algorithms would allow experienced analysts to experiment with di erent statistical models before choosing one, but without requiring prohibitively expensive programming e orts. It would also smooth the steep learning curve often faced by novice users of data mining tools and libraries. Finally, it would accelerate dissemination of essential research results and the development of applications. In this paper, we present a framework and the basic software for the automated synthesis of data analysis programs. We use a speci cation language that generalizes Bayesian networks, a popular notation used in many communities. Usi...
Wray L. Buntine, Bernd Fischer 0002, Thomas Pressb