An expert code generator using rule-based and frames knowledge representation techniques

This paper aims to demonstrate the development of an expert code generator using rule-based and frames knowledge representation techniques (ECG-RF). The ECG-RF system presented in this paper is a passive code generator that carries out the task of automatic code generation in fixed-structure software. To develop an ECG-RF system, the artificial intelligence (AI) of rule-based system and frames knowledge representation techniques was applied to a code generation task. ECG-RF fills a predefined frame of a certain fixed-structure program with code chunks retrieved from ECG-RF's knowledge base. The filling operation is achieved by ECG-RF's inference engine and is guided by the information collected from the user via a graphic user interface (GUI). In this paper, an ECG-RF system for generating a device driver program is presented and implemented with VBasic software. The results show that the ECG-RF design concept is reasonably reliable.